Nothing
tests/testthat/test-ISL.R
In SwimmeR: Data Import, Cleaning, and Conversions for Swimming Results
test_that("ISL season 2 dataframe dims", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_01112020_Budapest_Match_6.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df <- swim_parse_ISL(
read_results(file),
splits = TRUE,
relay_swimmers = TRUE)
expect_equivalent(dim(df), c(324, 20)) # 324 is the normal number of rows, although there can be more depending on ties in the skins races
} # 20 is the normal number of columns
})
test_that("ISL season 2 whole dataframe", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_09112020_Budapest_Match_10.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df_test <- file %>%
read_results() %>%
swim_parse_ISL(splits = TRUE, relay_swimmers = TRUE)
df_standard <- structure(list(Place = c(1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4,
5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1,
2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6,
7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3,
4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8,
1, 2, 3, 4, 5, 6, 7, NA, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4,
5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1,
2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6,
7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3,
4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8,
1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5,
6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2,
3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7,
8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4,
5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1,
2, 3, 4, 1, 2, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 1, 2), Lane = c(1,
6, 2, 4, 5, 3, 7, 8, 5, 1, 6, 4, 7, 8, 2, 3, 5, 6, 2, 1, 7, 4,
8, 3, 1, 5, 3, 4, 2, 7, 8, 6, 4, 5, 3, 1, 7, 6, 2, 8, 2, 4, 1,
8, 6, 5, 3, 7, 4, 5, 1, 7, 2, 6, 8, 3, 5, 1, 8, 6, 2, 7, 3, 4,
2, 1, 5, 3, 6, 4, 7, 8, 3, 7, 4, 1, 2, 6, 5, 8, 6, 4, 2, 1, 3,
7, 5, 8, 7, 2, 8, 4, 6, 3, 1, 5, 6, 5, 4, 7, 8, 3, 2, 1, 5, 7,
1, 4, 3, 6, 8, 2, 5, 4, 7, 2, 6, 1, 3, 8, 1, 4, 3, 5, 6, 7, 2,
8, 5, 7, 6, 4, 3, 2, 1, 8, 7, 1, 4, 5, 3, 2, 8, 6, 5, 4, 1, 6,
3, 2, 7, 8, 1, 7, 4, 5, 3, 8, 6, 2, 5, 6, 2, 1, 4, 8, 3, 7, 3,
7, 4, 8, 6, 5, 2, 1, 3, 5, 1, 2, 8, 7, 6, 4, 5, 4, 2, 1, 8, 6,
7, 3, 3, 2, 4, 5, 1, 6, 8, 7, 6, 5, 4, 2, 3, 1, 7, 8, 6, 5, 4,
2, 3, 1, 8, 7, 3, 4, 6, 2, 7, 5, 1, 8, 2, 5, 3, 7, 8, 6, 4, 1,
3, 2, 5, 1, 4, 7, 6, 8, 5, 6, 3, 2, 4, 1, 7, 8, 8, 3, 4, 6, 7,
5, 2, 1, 3, 2, 7, 1, 8, 4, 6, 5, 7, 8, 5, 6, 2, 3, 4, 1, 3, 5,
2, 6, 4, 7, 1, 8, 2, 3, 1, 5, 6, 4, 7, 8, 2, 7, 5, 6, 3, 8, 4,
1, 4, 3, 7, 8, 2, 1, 5, 6, 4, 3, 5, 6, 5, 4, 6, 2, 5, 1, 4, 7,
3, 8, 6, 5, 3, 4, 5, 4), Name = c("GASTALDELLO Beryl", "DAHLIA Kelsi",
"TETZLOFF Aly", "WATTEL Marie", "HINDS Natalie", "ATKINSON Alia",
"BRUCE Tain", "BLACK Haley", "DRESSEL Caeleb", "SHIELDS Tom",
"CIESLAK Marcin", "VEKOVISHCHEV Mikhail", "SZABO Szebasztian",
"RIVOLTA Matteo", "CARTER Dylan", "GUY James", "NELSON Beata",
"FLICKINGER Hali", "GASSON Helena", "DELOOF Ali", "PELLEGRINI Federica",
"DAWSON Kathleen", "BURIAN Katalin", "WILLMOTT Aimee", "MURPHY Ryan",
"KAWECKI Radoslaw", "GREENBANK Luke", "DIENER Christian", "HVAS Tomoe",
"de DEUS Leonardo", "SANTI Fabio", "SZARANEK Mark", "LAZOR Annie",
"KING Lilly", "PICKREM Sydney", "SEBASTIAN Julia", "CARRARO Martina",
"HANNIS Molly", "SMITH Kierra", "CASTIGLIONI Arianna", "LICON Will",
"PRIGODA Kirill", "PRENOT Josh", "MARTINENGHI Nicolo", "FINK Nic",
"CORDES Kevin", "GREENE Darragh", "SCOZZOLI Fabio", NA, NA, NA,
NA, NA, NA, NA, NA, "DRESSEL Caeleb", "GKOLOMEEV Kristian", "SZABO Szebasztian",
"RESS Justin", "ROONEY Maxime", "MIRESSI Alessandro", "LEVEAUX Amaury",
"VEKOVISHCHEV Mikhail", "WEITZEIL Abbey", "GASTALDELLO Beryl",
"SMOLIGA Olivia", "ANDERSON Freya", "BROWN Erika", "HOPKIN Anna",
"MUNOZ del CAMPO Lidon", "MEDEIROS Etiene", "LANZA Vini", "HEINTZ Philip",
"VAZAIOS Andreas", "SELISKAR Andrew", "PRENOT Josh", "SZARANEK Mark",
"PERIBONIO Tomas", "SANTI Fabio", "NELSON Beata", "PICKREM Sydney",
"GORBENKO Anastasia", "GASSON Helena", "WILLMOTT Aimee", "VERRASZTO Evelyn",
"FERTEL Kelly", "BLACK Haley", "MARTINENGHI Nicolo", "SILVA FRANCA Felipe",
"SCOZZOLI Fabio", "PRIGODA Kirill", "FINK Nic", "GREENE Darragh",
"LICON Will", "CORDES Kevin", "HANNIS Molly", "KING Lilly", "ATKINSON Alia",
"CARRARO Martina", "CASTIGLIONI Arianna", "LAZOR Annie", "SEBASTIAN Julia",
"GORBENKO Anastasia", NA, NA, NA, NA, NA, NA, NA, NA, "SMOLIGA Olivia",
"TOUSSAINT Kira", "MEDEIROS Etiene", "TETZLOFF Aly", "BROWN Erika",
"MARSH Alyssa", "DAWSON Kathleen", "KONOPKA REID Katrina", "MURPHY Ryan",
"GUIDO Guilherme", "DIENER Christian", "RESS Justin", "STEWART Coleman",
"de DEUS Leonardo", "HVAS Tomoe", "SANTI Fabio", "FLICKINGER Hali",
"DUMONT Valentine", "ANDERSON Haley", "HIBBOTT Holly", "WILLMOTT Aimee",
"MUREZ Andi", "SARGENT Makayla", "OLIVEIRA Larissa", "ROMANCHUK Mykhaylo",
"SCHEFFER Fernando", "DEAN Tom", "BAQLAH Khader", "GUY James",
"HEIDTMANN Jacob", "MELO Luiz Altamir", "PERIBONIO Tomas", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "GASTALDELLO Beryl",
"WEITZEIL Abbey", "ANDERSON Freya", "HOPKIN Anna", "SCHMITT Allison",
"MUNOZ del CAMPO Lidon", "NEAL Lia", "OLIVEIRA Larissa", "DRESSEL Caeleb",
"MIRESSI Alessandro", "RESS Justin", "CHIERIGHINI Marcelo", "GKOLOMEEV Kristian",
"ROONEY Maxime", "SCOTT Duncan", "VEKOVISHCHEV Mikhail", "FLICKINGER Hali",
"GASSON Helena", "LARGE Emily", "HIBBOTT Holly", "VERRASZTO Evelyn",
"BRUCE Tain", "SARGENT Makayla", "FERTEL Kelly", "SHIELDS Tom",
"WANG Eddie", "LANZA Vini", "VAZAIOS Andreas", "de DEUS Leonardo",
"PRENOT Josh", "MELO Luiz Altamir", "SZARANEK Mark", "SMOLIGA Olivia",
"TOUSSAINT Kira", "BROWN Erika", "DELOOF Ali", "DAWSON Kathleen",
"TETZLOFF Aly", "MEDEIROS Etiene", "BURIAN Katalin", "MURPHY Ryan",
"CARTER Dylan", "KAWECKI Radoslaw", "GUIDO Guilherme", "STEWART Coleman",
"GREENBANK Luke", "RIVOLTA Matteo", "SANTI Fabio", "GASTALDELLO Beryl",
"GORBENKO Anastasia", "NELSON Beata", "KAMENEVA Maria", "FLICKINGER Hali",
"WILLMOTT Aimee", "KONOPKA REID Katrina", "BLACK Haley", "DRESSEL Caeleb",
"CIESLAK Marcin", "HVAS Tomoe", "VAZAIOS Andreas", "HEINTZ Philip",
"SELISKAR Andrew", "SCOTT Duncan", "de DEUS Leonardo", "ANDERSON Freya",
"MUREZ Andi", "SCHMITT Allison", "PELLEGRINI Federica", "DUMONT Valentine",
"RASMUS Claire", "BROWN Erika", "HIBBOTT Holly", "HAAS Townley",
"VEKOVISHCHEV Mikhail", "SCHEFFER Fernando", "DEAN Tom", "BAQLAH Khader",
"CORREIA Breno", "HEIDTMANN Jacob", "MELO Luiz Altamir", "GASTALDELLO Beryl",
"MARSH Alyssa", "DAHLIA Kelsi", "WATTEL Marie", "NELSON Beata",
"HOPKIN Anna", "BRUCE Tain", "BLACK Haley", "SZABO Szebasztian",
"DRESSEL Caeleb", "CIESLAK Marcin", "SHIELDS Tom", "RIVOLTA Matteo",
"ROONEY Maxime", "LANZA Vini", "GUY James", "KING Lilly", "ATKINSON Alia",
"CARRARO Martina", "LAZOR Annie", "CASTIGLIONI Arianna", "HANNIS Molly",
"SEBASTIAN Julia", "SMITH Kierra", "MARTINENGHI Nicolo", "SCOZZOLI Fabio",
"SILVA FRANCA Felipe", "LICON Will", "PRIGODA Kirill", "CORDES Kevin",
"FINK Nic", "GREENE Darragh", NA, NA, NA, NA, NA, NA, NA, NA,
"PICKREM Sydney", "FLICKINGER Hali", "WILLMOTT Aimee", "SARGENT Makayla",
"GORBENKO Anastasia", "FERTEL Kelly", "VERRASZTO Evelyn", "DUMONT Valentine",
"SCOTT Duncan", "HEINTZ Philip", "HEIDTMANN Jacob", "PRENOT Josh",
"PERIBONIO Tomas", "ROMANCHUK Mykhaylo", "SZARANEK Mark", "DEAN Tom",
"KING Lilly", "HANNIS Molly", "CARRARO Martina", "CASTIGLIONI Arianna",
"ANDERSON Freya", "LAZOR Annie", "SEBASTIAN Julia", "GASSON Helena",
"KING Lilly", "HANNIS Molly", "CARRARO Martina", "CASTIGLIONI Arianna",
"KING Lilly", "HANNIS Molly", "MURPHY Ryan", "GUIDO Guilherme",
"CARTER Dylan", "DIENER Christian", "STEWART Coleman", "RIVOLTA Matteo",
"RESS Justin", "de DEUS Leonardo", "MURPHY Ryan", "CARTER Dylan",
"DIENER Christian", "GUIDO Guilherme", "MURPHY Ryan", "CARTER Dylan"
), Team = c("LAC", "CAC", "LAC", "LON", "CAC", "LON", "AQC",
"AQC", "CAC", "LAC", "CAC", "LON", "AQC", "AQC", "LAC", "LON",
"CAC", "CAC", "LAC", "LAC", "AQC", "LON", "AQC", "LON", "LAC",
"CAC", "LON", "LON", "LAC", "AQC", "AQC", "CAC", "LON", "CAC",
"LON", "LAC", "AQC", "CAC", "LAC", "AQC", "LAC", "LON", "LAC",
"AQC", "CAC", "CAC", "LON", "AQC", "LON", "CAC", "LAC", "AQC",
"LAC", "CAC", "AQC", "LON", "CAC", "LAC", "AQC", "CAC", "LAC",
"AQC", "LON", "LON", "LAC", "LAC", "CAC", "LON", "CAC", "LON",
"AQC", "AQC", "LON", "AQC", "LON", "LAC", "LAC", "CAC", "CAC",
"AQC", "CAC", "LON", "LAC", "LAC", "LON", "AQC", "CAC", "AQC",
"AQC", "LAC", "AQC", "LON", "CAC", "LON", "LAC", "CAC", "CAC",
"CAC", "LON", "AQC", "AQC", "LON", "LAC", "LAC", "CAC", "AQC",
"LAC", "LON", "LON", "CAC", "AQC", "LAC", "CAC", "LON", "AQC",
"LAC", "CAC", "LAC", "LON", "AQC", "LAC", "LON", "LON", "CAC",
"CAC", "AQC", "LAC", "AQC", "CAC", "AQC", "CAC", "LON", "LON",
"LAC", "LAC", "AQC", "AQC", "LAC", "LON", "CAC", "LON", "LAC",
"AQC", "CAC", "CAC", "LON", "LAC", "CAC", "LON", "LAC", "AQC",
"AQC", "LAC", "AQC", "LON", "CAC", "LON", "AQC", "CAC", "LAC",
"LAC", "LAC", "LON", "LON", "CAC", "AQC", "CAC", "AQC", "CAC",
"AQC", "CAC", "AQC", "LAC", "LAC", "LON", "LON", "CAC", "LAC",
"LON", "LON", "AQC", "AQC", "LAC", "CAC", "LAC", "CAC", "LON",
"LON", "AQC", "LAC", "AQC", "CAC", "CAC", "LON", "CAC", "LAC",
"LON", "LAC", "AQC", "AQC", "LAC", "LAC", "CAC", "LON", "CAC",
"LON", "AQC", "AQC", "LAC", "LAC", "CAC", "LON", "CAC", "LON",
"AQC", "AQC", "CAC", "CAC", "LAC", "LON", "AQC", "LAC", "LON",
"AQC", "LON", "LAC", "CAC", "AQC", "AQC", "LAC", "CAC", "LON",
"CAC", "LON", "LAC", "LON", "CAC", "AQC", "LAC", "AQC", "LAC",
"LAC", "CAC", "LON", "CAC", "LON", "AQC", "AQC", "AQC", "CAC",
"CAC", "LAC", "AQC", "LAC", "LON", "LON", "CAC", "LON", "AQC",
"LON", "AQC", "CAC", "LAC", "LAC", "AQC", "AQC", "LAC", "LAC",
"LON", "CAC", "CAC", "LON", "CAC", "LAC", "LON", "LAC", "CAC",
"AQC", "LON", "AQC", "LON", "CAC", "LON", "LAC", "LAC", "CAC",
"AQC", "AQC", "LON", "AQC", "LAC", "LAC", "CAC", "AQC", "CAC",
"LON", "CAC", "CAC", "AQC", "AQC", "LON", "LON", "LAC", "LAC",
"CAC", "CAC", "AQC", "AQC", "CAC", "CAC", "LAC", "LON", "LAC",
"LON", "CAC", "AQC", "CAC", "AQC", "LAC", "LAC", "LON", "LON",
"LAC", "LAC"), Finals = c("55.71", "55.72", "56.46", "56.50", "57.10",
"57.21", "58.17", "1:00.14", "49.02", "49.17", "49.67", "49.88",
"49.89", "49.93", "50.70", "51.64", "2:02.51", "2:03.02", "2:05.29",
"2:05.62", "2:05.64", "2:05.92", "2:06.12", "2:08.34", "1:48.60",
"1:48.79", "1:50.50", "1:50.80", "1:53.54", "1:54.07", "1:57.73",
"1:58.84", "2:17.04", "2:17.18", "2:20.22", "2:20.89", "2:21.41",
"2:21.48", "2:22.20", "2:23.95", "2:04.12", "2:04.21", "2:06.60",
"2:07.04", "2:07.18", "2:07.22", "2:07.73", "2:07.81", "3:28.65",
"3:28.69", "3:29.69", "3:33.80", "3:34.26", "3:35.41", "3:38.42",
"3:41.19", "20.52", "20.89", "21.09", "21.17", "21.45", "21.48",
"21.80", "21.82", "23.45", "23.78", "24.05", "24.28", "24.34",
"24.41", "24.55", "24.59", "1:53.70", "1:53.73", "1:53.79", "1:54.17",
"1:54.97", "1:57.04", "1:57.05", "2:01.74", "2:05.95", "2:05.97",
"2:05.98", "2:08.02", "2:10.17", "2:11.31", "2:12.33", "2:23.47",
"25.89", "26.08", "26.39", "26.45", "26.88", "26.96", "27.11",
"27.12", "29.17", "29.18", "29.44", "29.60", "29.94", "30.42",
"30.73", NA, "3:05.52", "3:05.77", "3:06.99", "3:07.31", "3:11.19",
"3:11.65", "3:12.13", "3:12.52", "25.85", "26.32", "26.71", "26.75",
"26.81", "27.29", "27.48", "27.89", "22.75", "22.89", "23.24",
"23.27", "23.29", "23.76", "24.63", "24.81", "3:59.78", "4:00.05",
"4:03.74", "4:04.58", "4:07.16", "4:09.16", "4:09.45", "4:11.10",
"3:38.93", "3:41.07", "3:41.91", "3:42.09", "3:42.30", "3:43.96",
"3:50.60", "3:52.11", "3:47.13", "3:48.15", "3:49.87", "3:52.26",
"3:52.71", "3:54.04", "3:56.47", "3:58.14", "3:21.26", "3:22.78",
"3:24.73", "3:24.77", "3:25.68", "3:27.70", "3:28.04", "3:28.40",
"51.16", "51.26", "51.52", "51.97", "53.37", "53.42", "54.09",
"54.16", "45.56", "46.23", "46.25", "46.53", "46.73", "46.85",
"46.89", "46.99", "2:04.36", "2:07.27", "2:07.45", "2:08.60",
"2:09.75", "2:10.09", "2:10.80", "2:13.57", "1:49.78", "1:50.14",
"1:52.32", "1:52.92", "1:53.15", "1:54.93", "1:55.09", "1:58.74",
"55.92", "56.30", "57.24", "57.75", "58.02", "58.21", "58.44",
"59.23", "49.93", "50.11", "50.17", "50.19", "50.23", "50.54",
"50.78", "53.11", "57.43", "57.90", "58.60", "58.64", "1:00.22",
"1:01.63", "1:03.02", "1:07.23", "50.48", "51.36", "52.11", "52.73",
"52.91", "53.18", "53.19", "55.78", "1:52.82", "1:53.98", "1:54.45",
"1:55.10", "1:55.39", "1:57.17", "1:57.82", "1:57.88", "1:41.84",
"1:42.34", "1:42.71", "1:43.31", "1:43.40", "1:43.69", "1:45.58",
"1:46.47", "25.30", "25.31", "25.35", "25.60", "25.68", "25.95",
"27.09", "27.25", "21.86", "22.06", "22.55", "22.68", "22.77",
"22.87", "22.96", "23.55", "1:03.15", "1:04.43", "1:04.54", "1:04.55",
"1:04.61", "1:04.76", "1:05.51", "1:06.61", "56.46", "57.23",
"57.47", "57.88", "57.95", "58.29", "58.35", "59.10", "3:16.14",
"3:17.22", "3:18.18", "3:19.04", "3:19.94", "3:20.05", "3:20.53",
"3:21.92", "4:25.90", "4:29.52", "4:32.93", "4:34.03", "4:37.37",
"4:38.09", "4:39.30", "4:55.35", "4:07.88", "4:07.99", "4:08.03",
"4:08.60", "4:09.71", "4:10.00", "4:10.09", "4:10.35", "29.16",
"29.77", "29.81", "29.95", "30.13", "30.34", "30.60", "30.71",
"29.63", "29.99", "30.21", "30.33", "29.24", "29.85", "22.85",
"23.12", "23.28", "23.30", "23.37", "23.50", "23.51", "23.82",
"23.54", "23.93", "24.31", "24.40", "24.18", "24.99"), Event = c("Women's 100m Butterfly",
"Women's 100m Butterfly", "Women's 100m Butterfly", "Women's 100m Butterfly",
"Women's 100m Butterfly", "Women's 100m Butterfly", "Women's 100m Butterfly",
"Women's 100m Butterfly", "Men's 100m Butterfly", "Men's 100m Butterfly",
"Men's 100m Butterfly", "Men's 100m Butterfly", "Men's 100m Butterfly",
"Men's 100m Butterfly", "Men's 100m Butterfly", "Men's 100m Butterfly",
"Women's 200m Backstroke", "Women's 200m Backstroke", "Women's 200m Backstroke",
"Women's 200m Backstroke", "Women's 200m Backstroke", "Women's 200m Backstroke",
"Women's 200m Backstroke", "Women's 200m Backstroke", "Men's 200m Backstroke",
"Men's 200m Backstroke", "Men's 200m Backstroke", "Men's 200m Backstroke",
"Men's 200m Backstroke", "Men's 200m Backstroke", "Men's 200m Backstroke",
"Men's 200m Backstroke", "Women's 200m Breaststroke", "Women's 200m Breaststroke",
"Women's 200m Breaststroke", "Women's 200m Breaststroke", "Women's 200m Breaststroke",
"Women's 200m Breaststroke", "Women's 200m Breaststroke", "Women's 200m Breaststroke",
"Men's 200m Breaststroke", "Men's 200m Breaststroke", "Men's 200m Breaststroke",
"Men's 200m Breaststroke", "Men's 200m Breaststroke", "Men's 200m Breaststroke",
"Men's 200m Breaststroke", "Men's 200m Breaststroke", "Women's 4x100m Freestyle",
"Women's 4x100m Freestyle", "Women's 4x100m Freestyle", "Women's 4x100m Freestyle",
"Women's 4x100m Freestyle", "Women's 4x100m Freestyle", "Women's 4x100m Freestyle",
"Women's 4x100m Freestyle", "Men's 50m Freestyle", "Men's 50m Freestyle",
"Men's 50m Freestyle", "Men's 50m Freestyle", "Men's 50m Freestyle",
"Men's 50m Freestyle", "Men's 50m Freestyle", "Men's 50m Freestyle",
"Women's 50m Freestyle", "Women's 50m Freestyle", "Women's 50m Freestyle",
"Women's 50m Freestyle", "Women's 50m Freestyle", "Women's 50m Freestyle",
"Women's 50m Freestyle", "Women's 50m Freestyle", "Men's 200m Individual Medley",
"Men's 200m Individual Medley", "Men's 200m Individual Medley",
"Men's 200m Individual Medley", "Men's 200m Individual Medley",
"Men's 200m Individual Medley", "Men's 200m Individual Medley",
"Men's 200m Individual Medley", "Women's 200m Individual Medley",
"Women's 200m Individual Medley", "Women's 200m Individual Medley",
"Women's 200m Individual Medley", "Women's 200m Individual Medley",
"Women's 200m Individual Medley", "Women's 200m Individual Medley",
"Women's 200m Individual Medley", "Men's 50m Breaststroke", "Men's 50m Breaststroke",
"Men's 50m Breaststroke", "Men's 50m Breaststroke", "Men's 50m Breaststroke",
"Men's 50m Breaststroke", "Men's 50m Breaststroke", "Men's 50m Breaststroke",
"Women's 50m Breaststroke", "Women's 50m Breaststroke", "Women's 50m Breaststroke",
"Women's 50m Breaststroke", "Women's 50m Breaststroke", "Women's 50m Breaststroke",
"Women's 50m Breaststroke", "Women's 50m Breaststroke", "Men's 4x100m Freestyle",
"Men's 4x100m Freestyle", "Men's 4x100m Freestyle", "Men's 4x100m Freestyle",
"Men's 4x100m Freestyle", "Men's 4x100m Freestyle", "Men's 4x100m Freestyle",
"Men's 4x100m Freestyle", "Women's 50m Backstroke", "Women's 50m Backstroke",
"Women's 50m Backstroke", "Women's 50m Backstroke", "Women's 50m Backstroke",
"Women's 50m Backstroke", "Women's 50m Backstroke", "Women's 50m Backstroke",
"Men's 50m Backstroke", "Men's 50m Backstroke", "Men's 50m Backstroke",
"Men's 50m Backstroke", "Men's 50m Backstroke", "Men's 50m Backstroke",
"Men's 50m Backstroke", "Men's 50m Backstroke", "Women's 400m Freestyle",
"Women's 400m Freestyle", "Women's 400m Freestyle", "Women's 400m Freestyle",
"Women's 400m Freestyle", "Women's 400m Freestyle", "Women's 400m Freestyle",
"Women's 400m Freestyle", "Men's 400m Freestyle", "Men's 400m Freestyle",
"Men's 400m Freestyle", "Men's 400m Freestyle", "Men's 400m Freestyle",
"Men's 400m Freestyle", "Men's 400m Freestyle", "Men's 400m Freestyle",
"Women's 4x100m Medley Relay", "Women's 4x100m Medley Relay",
"Women's 4x100m Medley Relay", "Women's 4x100m Medley Relay",
"Women's 4x100m Medley Relay", "Women's 4x100m Medley Relay",
"Women's 4x100m Medley Relay", "Women's 4x100m Medley Relay",
"Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay",
"Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay",
"Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay", "Women's 100m Freestyle",
"Women's 100m Freestyle", "Women's 100m Freestyle", "Women's 100m Freestyle",
"Women's 100m Freestyle", "Women's 100m Freestyle", "Women's 100m Freestyle",
"Women's 100m Freestyle", "Men's 100m Freestyle", "Men's 100m Freestyle",
"Men's 100m Freestyle", "Men's 100m Freestyle", "Men's 100m Freestyle",
"Men's 100m Freestyle", "Men's 100m Freestyle", "Men's 100m Freestyle",
"Women's 200m Butterfly", "Women's 200m Butterfly", "Women's 200m Butterfly",
"Women's 200m Butterfly", "Women's 200m Butterfly", "Women's 200m Butterfly",
"Women's 200m Butterfly", "Women's 200m Butterfly", "Men's 200m Butterfly",
"Men's 200m Butterfly", "Men's 200m Butterfly", "Men's 200m Butterfly",
"Men's 200m Butterfly", "Men's 200m Butterfly", "Men's 200m Butterfly",
"Men's 200m Butterfly", "Women's 100m Backstroke", "Women's 100m Backstroke",
"Women's 100m Backstroke", "Women's 100m Backstroke", "Women's 100m Backstroke",
"Women's 100m Backstroke", "Women's 100m Backstroke", "Women's 100m Backstroke",
"Men's 100m Backstroke", "Men's 100m Backstroke", "Men's 100m Backstroke",
"Men's 100m Backstroke", "Men's 100m Backstroke", "Men's 100m Backstroke",
"Men's 100m Backstroke", "Men's 100m Backstroke", "Women's 100m Individual Medley",
"Women's 100m Individual Medley", "Women's 100m Individual Medley",
"Women's 100m Individual Medley", "Women's 100m Individual Medley",
"Women's 100m Individual Medley", "Women's 100m Individual Medley",
"Women's 100m Individual Medley", "Men's 100m Individual Medley",
"Men's 100m Individual Medley", "Men's 100m Individual Medley",
"Men's 100m Individual Medley", "Men's 100m Individual Medley",
"Men's 100m Individual Medley", "Men's 100m Individual Medley",
"Men's 100m Individual Medley", "Women's 200m Freestyle", "Women's 200m Freestyle",
"Women's 200m Freestyle", "Women's 200m Freestyle", "Women's 200m Freestyle",
"Women's 200m Freestyle", "Women's 200m Freestyle", "Women's 200m Freestyle",
"Men's 200m Freestyle", "Men's 200m Freestyle", "Men's 200m Freestyle",
"Men's 200m Freestyle", "Men's 200m Freestyle", "Men's 200m Freestyle",
"Men's 200m Freestyle", "Men's 200m Freestyle", "Women's 50m Butterfly",
"Women's 50m Butterfly", "Women's 50m Butterfly", "Women's 50m Butterfly",
"Women's 50m Butterfly", "Women's 50m Butterfly", "Women's 50m Butterfly",
"Women's 50m Butterfly", "Men's 50m Butterfly", "Men's 50m Butterfly",
"Men's 50m Butterfly", "Men's 50m Butterfly", "Men's 50m Butterfly",
"Men's 50m Butterfly", "Men's 50m Butterfly", "Men's 50m Butterfly",
"Women's 100m Breaststroke", "Women's 100m Breaststroke", "Women's 100m Breaststroke",
"Women's 100m Breaststroke", "Women's 100m Breaststroke", "Women's 100m Breaststroke",
"Women's 100m Breaststroke", "Women's 100m Breaststroke", "Men's 100m Breaststroke",
"Men's 100m Breaststroke", "Men's 100m Breaststroke", "Men's 100m Breaststroke",
"Men's 100m Breaststroke", "Men's 100m Breaststroke", "Men's 100m Breaststroke",
"Men's 100m Breaststroke", "Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle",
"Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle",
"Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle",
"Women's 400m Individual Medley", "Women's 400m Individual Medley",
"Women's 400m Individual Medley", "Women's 400m Individual Medley",
"Women's 400m Individual Medley", "Women's 400m Individual Medley",
"Women's 400m Individual Medley", "Women's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins"),
Points = c(12, 7, 6, 5, 4, 3, 0, -1, 10, 7, 6, 5, 4, 3, 2,
0, 10, 7, 6, 5, 4, 3, 2, 0, 19, 7, 6, 5, 0, 0, 0, -1, 10,
7, 6, 5, 4, 3, 2, 0, 9, 7, 6, 5, 4, 3, 2, 1, 20, 14, 12,
10, 8, 6, 4, -2, 19, 7, 6, 5, 0, 0, 0, 0, 15, 7, 6, 5, 4,
0, 0, 0, 10, 7, 6, 5, 4, 3, 2, -1, 15, 7, 6, 5, 4, 0, 0,
-1, 15, 7, 6, 5, 4, 0, 0, 0, 15, 7, 6, 5, 4, 0, 0, -2, 18,
14, 12, 10, 8, 6, 4, 2, 15, 7, 6, 5, 4, 0, 0, 0, 15, 7, 6,
5, 4, 0, 0, 0, 12, 7, 6, 5, 4, 3, 0, -1, 12, 7, 6, 5, 4,
3, -1, -1, 20, 14, 12, 10, 8, 6, 4, 0, 18, 14, 12, 10, 8,
6, 4, 2, 19, 7, 6, 5, 0, 0, 0, 0, 9, 7, 6, 5, 4, 3, 2, 1,
19, 7, 6, 5, 0, 0, 0, -1, 15, 7, 6, 5, 4, 0, 0, 0, 15, 7,
6, 5, 4, 0, 0, 0, 10, 7, 6, 5, 4, 3, 2, 0, 19, 7, 6, 5, 0,
0, -1, -1, 24, 7, 6, 0, 0, 0, 0, -1, 12, 7, 6, 5, 4, 3, 0,
0, 10, 7, 6, 5, 4, 3, 2, 0, 12, 7, 6, 5, 4, 3, -1, -1, 19,
7, 6, 5, 0, 0, 0, 0, 10, 7, 6, 5, 4, 3, 2, 0, 10, 7, 6, 5,
4, 3, 2, 0, 18, 14, 12, 10, 8, 6, 4, 2, 19, 7, 6, 5, 0, 0,
0, -1, 9, 7, 6, 5, 4, 3, 2, 1, 15, 7, 6, 5, 4, 0, 0, 0, 9,
7, 6, 5, 14, 7, 10, 7, 6, 5, 4, 3, 2, 0, 9, 7, 6, 5, 14,
7), DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0), Relay_Swimmer_1 = c(NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "HOPKIN Anna",
"SMOLIGA Olivia", "MUREZ Andi", "MUNOZ del CAMPO Lidon",
"STEWART Kendyl", "NEAL Lia", "KONOPKA REID Katrina", "HIBBOTT Holly",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, "MAJCHRZAK Kacper", "MIRESSI Alessandro", "FERREIRA Marco",
"SCOTT Duncan", "CLOGG Elliot", "CIESLAK Marcin", "CORREIA Breno",
"CARTER Dylan", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "SMOLIGA Olivia", "TOUSSAINT Kira",
"DELOOF Ali", "NELSON Beata", "KAMENEVA Maria", "GASSON Helena",
"PELLEGRINI Federica", "BURIAN Katalin", "MURPHY Ryan", "RIVOLTA Matteo",
"DIENER Christian", "STEWART Coleman", "GREENBANK Luke",
"de DEUS Leonardo", "KAWECKI Radoslaw", "CHRISTOU Apostolos",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "RESS Justin", "GKOLOMEEV Kristian",
"VEKOVISHCHEV Mikhail", "CHRISTOU Apostolos", "JACKSON Tate",
"MIRESSI Alessandro", "VAZAIOS Andreas", "SZABO Szebasztian",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA),
Relay_Swimmer_2 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "ANDERSON Freya", "BROWN Erika",
"GORBENKO Anastasia", "PELLEGRINI Federica", "RASMUS Claire",
"BURCHILL Veronica", "MEDEIROS Etiene", "WEST Harriet", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "JACKSON Tate", "SPAJARI Pedro", "SHIELDS Tom", "KUSCH Marius",
"DEAN Tom", "WANG Eddie", "SANTOS Gabriel", "CHRISTOU Apostolos",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "KING Lilly", "ATKINSON Alia", "GORBENKO Anastasia",
"HANNIS Molly", "LAZOR Annie", "SEBASTIAN Julia", "CARRARO Martina",
"CASTIGLIONI Arianna", "SILVA FRANCA Felipe", "MARTINENGHI Nicolo",
"PRIGODA Kirill", "FINK Nic", "GREENE Darragh", "SCOZZOLI Fabio",
"CORDES Kevin", "LICON Will", NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"DRESSEL Caeleb", "SHIELDS Tom", "KUSCH Marius", "FERREIRA Marco",
"MAJCHRZAK Kacper", "CHIERIGHINI Marcelo", "CLOGG Elliot",
"SPAJARI Pedro", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA), Relay_Swimmer_3 = c(NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "WATTEL Marie",
"SCHMITT Allison", "MARSH Alyssa", "OLIVEIRA Larissa", "McLAUGHLIN Katie",
"FLICKINGER Hali", "BRUCE Tain", "LARGE Emily", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"HAAS Townley", "SZABO Szebasztian", "GKOLOMEEV Kristian",
"LANZA Vini", "LEVEAUX Amaury", "KAWECKI Radoslaw", "MELO Luiz Altamir",
"HVAS Tomoe", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "DAHLIA Kelsi", "WATTEL Marie", "GASTALDELLO Beryl",
"HINDS Natalie", "WEST Harriet", "STEWART Kendyl", "BRUCE Tain",
"TOURETSKI Sasha Alexandra", "SHIELDS Tom", "SZABO Szebasztian",
"KUSCH Marius", "DRESSEL Caeleb", "VEKOVISHCHEV Mikhail",
"HEINTZ Philip", "JACKSON Tate", "CARTER Dylan", NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "SMOLIGA Olivia", "GASTALDELLO Beryl",
"KAMENEVA Maria", "TETZLOFF Aly", "SCHMITT Allison", "MUNOZ del CAMPO Lidon",
"WATTEL Marie", "PELLEGRINI Federica", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA), Relay_Swimmer_4 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "KAMENEVA Maria", "HINDS Natalie", "TETZLOFF Aly",
"DUMONT Valentine", "WEITZEIL Abbey", "DAHLIA Kelsi", "TOURETSKI Sasha Alexandra",
"DAWSON Kathleen", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "DRESSEL Caeleb", "CHIERIGHINI Marcelo",
"ROONEY Maxime", "VEKOVISHCHEV Mikhail", "VAZAIOS Andreas",
"SZARANEK Mark", "HEINTZ Philip", "SELISKAR Andrew", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "BROWN Erika", "ANDERSON Freya", "WEITZEIL Abbey", "SCHMITT Allison",
"HOPKIN Anna", "TETZLOFF Aly", "MUNOZ del CAMPO Lidon", "KONOPKA REID Katrina",
"ROONEY Maxime", "MIRESSI Alessandro", "SCOTT Duncan", "MAJCHRZAK Kacper",
"LANZA Vini", "CHIERIGHINI Marcelo", "RESS Justin", "FERREIRA Marco",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "BROWN Erika", "WEITZEIL Abbey",
"ANDERSON Freya", "MUREZ Andi", "HINDS Natalie", "OLIVEIRA Larissa",
"HOPKIN Anna", "DUMONT Valentine", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA), Split_50 = c("25.85", "26.04",
"26.07", "26.09", "26.70", "26.88", "27.23", "27.46", "23.32",
"22.85", "23.39", "23.19", "23.09", "23.23", "23.30", "23.83",
"28.70", "29.45", "29.65", "29.20", "29.55", "29.08", "29.60",
"30.07", "25.50", "26.36", "26.04", "25.72", "26.72", "26.40",
"26.81", "27.38", "31.76", "30.61", "32.37", "32.09", "32.51",
"32.06", "32.35", "33.06", "28.65", "28.08", "29.21", "28.32",
"28.90", "28.62", "28.93", "28.41", "25.12", "24.98", "24.87",
"25.71", "25.48", "26.02", "26.13", "26.69", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "24.54",
"24.29", "25.39", "24.51", "25.02", "25.58", "25.39", "26.22",
"27.24", "28.09", "28.04", "27.53", "28.66", "28.58", "28.39",
"27.41", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "22.59", "22.33", "22.65", "22.68", "22.90",
"22.81", "22.95", "22.24", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "28.25", "28.68", "28.49",
"28.58", "29.01", "28.69", "28.75", "28.85", "25.93", "25.08",
"25.65", "25.89", "25.65", "25.71", "25.37", "26.27", "27.31",
"27.57", "27.29", "27.88", "28.06", "27.85", "28.78", "29.09",
"23.96", "24.95", "24.61", "24.46", "24.65", "24.92", "24.93",
"24.67", "24.77", "24.43", "25.54", "24.87", "25.57", "25.51",
"25.97", "25.87", "22.14", "22.26", "22.17", "21.88", "22.32",
"22.13", "22.66", "22.52", "28.52", "28.84", "28.88", "29.20",
"28.98", "29.03", "29.34", "29.35", "24.57", "25.02", "25.07",
"25.80", "25.13", "25.63", "25.11", "26.02", "27.21", "27.03",
"27.51", "27.77", "27.92", "28.04", "28.11", "28.90", "24.03",
"23.81", "24.42", "24.19", "24.29", "24.63", "24.74", "25.44",
"26.33", "26.27", "26.77", "26.69", "28.01", "28.37", "27.89",
"28.87", "22.96", "23.50", "23.53", "24.10", "24.04", "24.16",
"24.44", "24.85", "26.80", "26.84", "27.52", "27.42", "27.35",
"27.92", "27.37", "27.95", "23.83", "24.12", "24.58", "24.14",
"24.32", "24.49", "24.55", "24.02", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "29.59", "30.18",
"31.00", "30.73", "30.57", "30.56", "31.09", "31.71", "26.42",
"26.58", "27.08", "27.41", "27.23", "27.28", "27.39", "27.49",
"22.18", "22.31", "22.80", "22.78", "22.59", "22.15", "22.96",
"22.61", "29.50", "29.05", "29.47", "29.47", "28.84", "29.42",
"29.43", "30.29", "25.66", "26.10", "26.81", "26.33", "26.45",
"27.09", "26.61", "26.52", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), Split_100 = c("29.86", "29.68", "30.39",
"30.41", "30.40", "30.33", "30.94", "32.68", "25.70", "26.32",
"26.28", "26.69", "26.80", "26.70", "27.40", "27.81", "30.84",
"31.06", "32.11", "31.74", "31.64", "31.91", "31.97", "31.99",
"27.88", "28.29", "28.34", "28.20", "27.94", "28.75", "29.66",
"29.62", "35.25", "35.73", "35.78", "35.78", "36.64", "36.97",
"35.76", "37.01", "31.32", "31.59", "32.12", "32.48", "32.44",
"31.97", "32.29", "32.98", "52.29", "51.95", "52.16", "53.64",
"53.31", "54.46", "54.92", "55.44", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "29.38", "28.59",
"28.09", "28.18", "29.63", "29.01", "29.33", "29.69", "32.29",
"31.83", "32.67", "32.29", "33.54", "32.96", "33.37", "36.64",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "46.98", "46.58", "47.59", "47.14", "47.95", "47.12",
"47.46", "46.56", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "30.22", "30.68", "30.62", "30.74",
"30.98", "30.99", "31.09", "30.70", "27.46", "27.56", "28.37",
"27.80", "28.06", "27.67", "27.77", "28.08", "56.24", "57.07",
"57.76", "57.47", "58.20", "57.96", "59.09", "59.76", "49.80",
"51.39", "50.77", "50.85", "50.99", "51.38", "50.67", "51.55",
"26.39", "26.83", "25.98", "27.10", "27.80", "27.91", "28.12",
"28.29", "23.42", "23.97", "24.08", "24.65", "24.41", "24.72",
"24.23", "24.47", "31.42", "32.50", "32.33", "33.10", "33.13",
"32.70", "32.85", "33.93", "28.20", "28.19", "28.81", "28.99",
"29.04", "29.33", "28.54", "29.54", "28.71", "29.27", "29.73",
"29.98", "30.10", "30.17", "30.33", "30.33", "25.90", "26.30",
"25.75", "26.00", "25.94", "25.91", "26.04", "27.67", "31.10",
"31.63", "31.83", "31.95", "32.21", "33.26", "35.13", "38.36",
"27.52", "27.86", "28.58", "28.63", "28.87", "29.02", "28.75",
"30.93", "28.98", "28.98", "28.90", "29.34", "28.98", "29.81",
"29.48", "29.91", "25.83", "25.91", "26.14", "26.49", "26.21",
"26.59", "26.63", "25.90", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "33.56", "34.25", "33.54",
"33.82", "34.04", "34.20", "34.42", "34.90", "30.04", "30.65",
"30.39", "30.47", "30.72", "31.01", "30.96", "31.61", "46.22",
"46.87", "47.53", "47.27", "47.43", "46.74", "47.76", "47.21",
"33.02", "32.67", "33.32", "33.19", "34.37", "34.06", "33.73",
"34.30", "29.18", "30.02", "30.55", "30.35", "30.08", "30.14",
"30.78", "30.47", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), Split_150 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "31.30", "31.40", "31.78",
"32.30", "32.07", "32.48", "32.06", "33.00", "27.99", "27.10",
"28.32", "28.57", "28.96", "29.34", "30.47", "31.00", "35.18",
"36.44", "36.06", "36.59", "36.43", "36.50", "36.69", "37.43",
"32.00", "32.25", "32.48", "33.09", "32.94", "32.80", "32.99",
"33.68", "24.89", "24.74", "24.75", "25.79", "25.98", "25.53",
"25.57", "26.13", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "32.81", "32.81", "32.70", "33.21",
"32.34", "34.48", "33.90", "36.91", "36.63", "35.77", "35.96",
"37.56", "36.62", "39.56", "38.72", "44.16", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "22.28",
"21.81", "21.84", "22.11", "22.51", "22.92", "22.69", "22.00",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "30.46", "30.81", "30.55", "31.04", "31.22", "31.32",
"31.40", "31.04", "27.69", "27.78", "28.49", "28.26", "28.24",
"28.13", "28.40", "28.50", "29.49", "29.65", "30.42", "29.94",
"30.54", "31.15", "30.69", "30.00", "26.43", "26.09", "26.16",
"27.10", "27.11", "27.24", "27.31", "27.23", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "32.14",
"32.59", "32.76", "33.38", "33.55", "33.77", "33.49", "34.57",
"28.16", "28.42", "28.88", "28.75", "29.38", "29.73", "29.87",
"30.88", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "28.92", "29.20", "29.21", "29.35", "29.62",
"29.73", "30.51", "30.18", "25.97", "26.08", "26.18", "26.26",
"26.31", "26.60", "26.92", "27.09", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "21.96", "22.17",
"22.17", "22.09", "22.56", "21.76", "22.24", "21.94", "34.30",
"34.58", "34.60", "34.77", "36.97", "36.18", "35.56", "38.57",
"31.45", "33.20", "32.54", "33.26", "32.26", "32.14", "32.16",
"32.58", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA), Split_200 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "31.67", "31.11", "31.75", "32.38",
"32.38", "32.45", "32.49", "33.28", "27.23", "27.04", "27.80",
"28.31", "29.92", "29.58", "30.79", "30.84", "34.85", "34.40",
"36.01", "36.43", "35.83", "35.95", "37.40", "36.45", "32.15",
"32.29", "32.79", "33.15", "32.90", "33.83", "33.52", "32.74",
"51.76", "52.00", "51.69", "53.82", "54.39", "54.49", "53.85",
"54.74", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "26.97", "28.04", "27.61", "28.27", "27.98",
"27.97", "28.43", "28.92", "29.79", "30.28", "29.31", "30.64",
"31.35", "30.21", "31.85", "35.26", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "47.04", "46.25",
"46.23", "47.23", "47.35", "47.85", "47.37", "47.13", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"30.60", "30.60", "30.79", "31.21", "31.39", "31.97", "31.40",
"31.35", "27.81", "28.23", "28.50", "28.29", "28.53", "28.70",
"28.86", "29.23", "1:03.03", "1:03.75", "1:04.62", "1:04.15",
"1:04.66", "1:05.95", "1:05.28", "1:03.48", "56.54", "56.13",
"56.77", "58.18", "57.88", "58.26", "58.49", "58.32", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"32.28", "33.34", "33.48", "32.92", "34.09", "34.59", "35.12",
"35.72", "28.85", "28.51", "29.56", "29.38", "29.60", "30.24",
"31.57", "32.30", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "28.12", "28.96", "28.82", "28.99",
"29.44", "29.71", "30.46", "29.84", "26.21", "26.23", "25.81",
"26.42", "26.56", "26.01", "27.48", "29.46", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "45.72",
"46.53", "46.71", "46.77", "46.88", "45.95", "47.58", "46.57",
"33.35", "33.26", "34.37", "34.37", "36.00", "35.35", "34.32",
"36.85", "31.67", "32.21", "32.09", "32.26", "32.44", "31.30",
"32.17", "31.70", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), Split_250 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "25.32", "25.08",
"24.90", "25.48", "26.05", "25.58", "26.02", "26.33", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "21.80", "22.03", "22.14", "22.63", "22.67", "22.18",
"23.02", "23.14", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "30.59", "30.55", "30.83", "30.94",
"31.20", "31.56", "31.28", "31.25", "27.69", "28.00", "28.19",
"27.94", "28.47", "28.25", "28.95", "29.94", "26.02", "25.77",
"25.71", "26.62", "26.47", "25.60", "27.13", "27.58", "22.22",
"22.57", "23.27", "23.13", "22.74", "23.81", "24.27", "23.39",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "24.72", "25.05", "24.98", "24.80",
"25.92", "25.38", "25.41", "25.65", "36.60", "39.84", "37.42",
"38.47", "38.50", "39.37", "41.40", "45.07", "35.05", "35.21",
"34.21", "33.82", "34.79", "35.94", "33.99", "36.43", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Split_300 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "52.52", "52.49", "53.07", "53.09", "53.71", "53.09",
"54.54", "54.94", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "46.22", "46.87", "46.71",
"46.85", "47.85", "47.59", "48.09", "49.53", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "30.48",
"30.31", "30.93", "30.89", "31.27", "31.44", "31.81", "32.19",
"27.78", "28.40", "27.83", "28.06", "28.43", "28.26", "29.83",
"29.79", "56.37", "56.59", "56.20", "57.92", "57.36", "56.93",
"58.53", "59.87", "48.92", "49.32", "50.30", "49.55", "49.30",
"51.24", "52.88", "51.25", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "52.09",
"52.63", "52.64", "53.01", "53.61", "53.46", "53.58", "53.37",
"37.27", "39.41", "39.15", "39.20", "38.52", "40.15", "41.97",
"44.14", "36.22", "35.11", "35.18", "34.67", "35.89", "36.40",
"35.55", "36.74", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), Split_350 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "24.75", "25.11",
"24.81", "25.63", "25.06", "25.21", "25.74", "26.70", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "21.79", "21.52", "21.90", "21.72", "23.19", "23.31",
"23.42", "23.51", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "30.30", "29.59", "30.89", "30.81",
"31.03", "31.80", "32.10", "32.89", "27.80", "28.34", "27.81",
"28.26", "28.00", "28.46", "30.77", "30.28", "24.25", "24.51",
"24.00", "25.17", "25.14", "25.16", "25.47", "25.75", "21.50",
"21.94", "22.29", "22.21", "22.90", "22.07", "21.92", "22.56",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "24.63", "24.01", "24.93", "24.69",
"24.93", "25.54", "24.72", "26.60", "31.68", "30.97", "32.89",
"32.37", "32.75", "32.50", "32.16", "34.08", "29.67", "29.34",
"29.33", "30.76", "29.43", "29.19", "29.98", "28.83", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Split_400 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "52.08", "52.25", "52.77", "53.25", "52.85", "53.37",
"55.11", "56.07", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "45.28", "46.07", "46.46",
"46.09", "48.04", "49.09", "49.21", "49.30", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "28.88",
"28.83", "30.64", "30.37", "31.06", "31.39", "31.62", "32.83",
"26.77", "27.68", "27.07", "27.59", "26.92", "28.78", "30.65",
"30.02", "51.49", "50.74", "51.29", "52.72", "52.49", "53.20",
"53.57", "55.03", "46.00", "45.94", "46.89", "46.19", "47.51",
"46.82", "46.00", "47.28", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "52.11",
"51.19", "51.30", "51.99", "52.02", "53.90", "51.61", "54.77",
"30.18", "29.74", "31.71", "32.19", "31.42", "31.06", "30.73",
"32.05", "28.98", "26.80", "27.32", "27.15", "28.37", "27.80",
"28.85", "27.08", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA)), row.names = c(NA, -324L), class = c("rowwise_df",
"tbl_df", "tbl", "data.frame"), groups = structure(list(.rows = structure(list(
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L,
27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L,
39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L,
51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L,
63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L,
75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L,
87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L,
99L, 100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L,
109L, 110L, 111L, 112L, 113L, 114L, 115L, 116L, 117L, 118L,
119L, 120L, 121L, 122L, 123L, 124L, 125L, 126L, 127L, 128L,
129L, 130L, 131L, 132L, 133L, 134L, 135L, 136L, 137L, 138L,
139L, 140L, 141L, 142L, 143L, 144L, 145L, 146L, 147L, 148L,
149L, 150L, 151L, 152L, 153L, 154L, 155L, 156L, 157L, 158L,
159L, 160L, 161L, 162L, 163L, 164L, 165L, 166L, 167L, 168L,
169L, 170L, 171L, 172L, 173L, 174L, 175L, 176L, 177L, 178L,
179L, 180L, 181L, 182L, 183L, 184L, 185L, 186L, 187L, 188L,
189L, 190L, 191L, 192L, 193L, 194L, 195L, 196L, 197L, 198L,
199L, 200L, 201L, 202L, 203L, 204L, 205L, 206L, 207L, 208L,
209L, 210L, 211L, 212L, 213L, 214L, 215L, 216L, 217L, 218L,
219L, 220L, 221L, 222L, 223L, 224L, 225L, 226L, 227L, 228L,
229L, 230L, 231L, 232L, 233L, 234L, 235L, 236L, 237L, 238L,
239L, 240L, 241L, 242L, 243L, 244L, 245L, 246L, 247L, 248L,
249L, 250L, 251L, 252L, 253L, 254L, 255L, 256L, 257L, 258L,
259L, 260L, 261L, 262L, 263L, 264L, 265L, 266L, 267L, 268L,
269L, 270L, 271L, 272L, 273L, 274L, 275L, 276L, 277L, 278L,
279L, 280L, 281L, 282L, 283L, 284L, 285L, 286L, 287L, 288L,
289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L, 297L, 298L,
299L, 300L, 301L, 302L, 303L, 304L, 305L, 306L, 307L, 308L,
309L, 310L, 311L, 312L, 313L, 314L, 315L, 316L, 317L, 318L,
319L, 320L, 321L, 322L, 323L, 324L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -324L), class = c("tbl_df",
"tbl", "data.frame")))
expect_equivalent(df_test, df_standard)
}
})
test_that("CAC Score ISL", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_16102020_Budapest_Match_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df <- file %>%
read_results() %>%
swim_parse_ISL()
expect_equal(sum(unique(df[df$Team == "CAC",])$Points, na.rm = TRUE),
567)
}
})
test_that("Lilly King Times with score - season 2", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_16102020_Budapest_Match_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df <- file %>%
read_results() %>%
swim_parse_ISL()
expect_equivalent(df[which(df$Name == "KING Lilly"),]$Finals,
c("2:17.11", "28.86", "1:03.16", "29.16", "29.25", "28.90"))
}
})
test_that("Lilly King Times without score - season 1", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_1_2019/ISL_16112019_CollegePark_Day_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df <- file %>%
read_results() %>%
swim_parse_ISL()
expect_equivalent(df[which(df$Name == "KING Lilly"),]$Finals,
c("29.00", "2:17.78"))
}
})
test_that("without score - season 1", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_1_2019/ISL_16112019_CollegePark_Day_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df_test <- file %>%
read_results() %>%
swim_parse_ISL(splits = TRUE, relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c(
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
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6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
3,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
NA,
1,
2,
2,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
1,
3,
4,
5,
6,
7,
NA,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8
),
Lane = c(
7,
1,
4,
2,
3,
8,
5,
6,
7,
1,
4,
5,
6,
2,
8,
3,
8,
7,
6,
2,
4,
1,
3,
5,
1,
5,
4,
6,
8,
2,
7,
3,
8,
1,
7,
5,
2,
6,
4,
3,
1,
2,
5,
3,
7,
8,
4,
6,
7,
4,
1,
5,
8,
2,
6,
3,
7,
8,
4,
3,
1,
5,
6,
2,
1,
2,
7,
5,
4,
3,
8,
6,
8,
4,
1,
2,
6,
3,
7,
5,
1,
4,
7,
8,
2,
3,
6,
5,
1,
5,
7,
4,
6,
8,
3,
2,
5,
4,
8,
7,
6,
3,
2,
1,
1,
2,
3,
4,
6,
7,
8,
5,
2,
1,
7,
4,
8,
5,
6,
3,
2,
4,
5,
6,
8,
3,
7,
1,
7,
8,
3,
1,
4,
5,
2,
6,
6,
4,
1,
2,
7,
5,
8,
3,
7,
2,
1,
5,
4,
8,
6,
3
),
Name = c(
"DAHLIA Kelsi",
"STEWART Kendyl",
"LOVEMORE Tayla",
"OSMAN Farida",
"BLACK Haley",
"HINDS Natalie",
"RULE Remedy",
"QUAH Ting Wen",
"DRESSEL Caeleb",
"SHIELDS Tom",
"LEWIS Clyde",
"STRAVIUS Jeremy",
"SMITH Giles",
"CONGER Jack",
"SWITKOWSKI Jan",
"COETZEE Ryan",
"KING Lilly",
"HANNIS Molly",
"HAUGHEY Siobhan",
"BAKER Kathleen",
"LARSON Breeja",
"LAZOR Anne",
"ESCOBEDO Emily",
"PICKETT Leiston",
"LIMA Felipe",
"FINNERTY Ian",
"ANDREW Michael",
"CORDES Kevin",
"FINK Nic",
"LICON Will",
"WILSON Andrew",
"KOCH Marco",
"MARGALIS Melanie",
"EASTIN Ella",
"FLICKINGER Hali",
"GALAT Bethany",
"ANDISON Bailey",
"BARKSDALE Emma",
"OVERHOLT Emily",
"WOOD Abbie",
"SELISKAR Andrew",
"KALISZ Chase",
"LITHERLAND Jay",
"SMITH Brendon",
"SZARANEK Mark",
"IPSON Anton",
"PERIBONIO Tomas",
"GROTHE Zane",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"KAWECKI Radoslaw",
"SHEBAT John",
"THORMEYER Markus",
"REID Christopher",
"SHIELDS Tom",
"HOLLARD Tristan",
"LITHERLAND Jay",
"CONGER Jack",
"BAKER Kathleen",
"BILQUIST Amy",
"MASSE Kylie",
"BRATTON Lisa",
"SHERIDAN Mikkayla",
"DELOOF Alexandra",
"FLICKINGER Hali",
"KUBOVA Simona",
"DRESSEL Caeleb",
"ANDREW Michael",
"HELD Ryan",
"CHADWICK Michael",
"APPLE Zach",
"CHIERIGHINI Marcelo",
"BECKER Bowe",
"HOWARD Robert",
"GASTALDELLO Beryl",
"BLUME Pernille",
"WASICK Kasia",
"SMOLIGA Olivia",
"GEER Margo",
"DELOOF Catherine",
"KENNEDY Madison",
"APOSTALON Anika",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"HAUGHEY Siobhan",
"WILSON Madison",
"COMERFORD Mallory",
"MARGALIS Melanie",
"NEALE Leah",
"DELOOF Catherine",
"SMITH Leah",
"GORBENKO Anastasia",
"PIERONI Blake",
"SELISKAR Andrew",
"de LUCCA Joao",
"LEWIS Clyde",
"STJEPANOVIC Velimir",
"MAJCHRZAK Kacper",
"HAAS Townley",
"GROTHE Zane",
"GASTALDELLO Beryl",
"BAKER Kathleen",
"SMOLIGA Olivia",
"DELOOF Alexandra",
"MASSE Kylie",
"KUBOVA Simona",
"COUGHLIN Natalie",
"BLACK Haley",
"GREVERS Matthew",
"ANDREW Michael",
"STRAVIUS Jeremy",
"VAZAIOS Andreas",
"SHEBAT John",
"TARASEVICH Grigory",
"KAWECKI Radoslaw",
"RYAN Shane",
"KING Lilly",
"WOG Kelsey",
"ESCOBEDO Emily",
"LAZOR Anne",
"LARSON Breeja",
"GALAT Bethany",
"ANDISON Bailey",
"BARKSDALE Emma",
"FINNERTY Ian",
"KOCH Marco",
"LICON Will",
"PRENOT Josh",
"FINK Nic",
"MILLER Cody",
"WILSON Andrew",
"PERIBONIO Tomas",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA
),
Team = c(
"CAC",
"LAC",
"NYB",
"LAC",
"NYB",
"CAC",
"DCT",
"DCT",
"CAC",
"LAC",
"NYB",
"DCT",
"DCT",
"LAC",
"CAC",
"NYB",
"CAC",
"CAC",
"DCT",
"LAC",
"NYB",
"LAC",
"NYB",
"DCT",
"LAC",
"DCT",
"NYB",
"DCT",
"CAC",
"LAC",
"CAC",
"NYB",
"CAC",
"LAC",
"CAC",
"DCT",
"LAC",
"DCT",
"NYB",
"NYB",
"LAC",
"LAC",
"DCT",
"NYB",
"CAC",
"CAC",
"NYB",
"DCT",
"CAC",
"NYB",
"LAC",
"DCT",
"CAC",
"LAC",
"DCT",
"NYB",
"CAC",
"CAC",
"NYB",
"NYB",
"LAC",
"DCT",
"DCT",
"LAC",
"LAC",
"LAC",
"CAC",
"DCT",
"NYB",
"NYB",
"CAC",
"DCT",
"CAC",
"NYB",
"LAC",
"LAC",
"DCT",
"NYB",
"CAC",
"DCT",
"LAC",
"NYB",
"CAC",
"CAC",
"LAC",
"NYB",
"DCT",
"DCT",
"LAC",
"DCT",
"CAC",
"NYB",
"DCT",
"CAC",
"NYB",
"LAC",
"DCT",
"NYB",
"CAC",
"CAC",
"DCT",
"NYB",
"LAC",
"LAC",
"LAC",
"LAC",
"NYB",
"NYB",
"DCT",
"CAC",
"CAC",
"DCT",
"LAC",
"LAC",
"CAC",
"NYB",
"CAC",
"DCT",
"DCT",
"NYB",
"LAC",
"NYB",
"DCT",
"DCT",
"CAC",
"NYB",
"CAC",
"LAC",
"CAC",
"CAC",
"NYB",
"LAC",
"NYB",
"DCT",
"LAC",
"DCT",
"DCT",
"NYB",
"LAC",
"LAC",
"CAC",
"DCT",
"CAC",
"NYB",
"CAC",
"LAC",
"LAC",
"DCT",
"NYB",
"CAC",
"DCT",
"NYB"
),
Finals = c(
"55.78",
"56.41",
"56.93",
"57.18",
"57.42",
"57.68",
"57.95",
"58.01",
"49.16",
"49.70",
"51.13",
"51.32",
"51.41",
"51.64",
"52.12",
"52.33",
"29.00",
"29.18",
"29.88",
"30.13",
"30.15",
"30.19",
"30.40",
"30.41",
"25.92",
"25.99",
"26.09",
"26.41",
"26.50",
"26.58",
"26.84",
"27.05",
"4:24.46",
"4:27.53",
"4:29.64",
"4:31.49",
"4:32.01",
"4:32.03",
"4:32.09",
"4:32.16",
"4:02.88",
"4:03.49",
"4:04.17",
"4:07.09",
"4:07.81",
"4:08.46",
"4:11.09",
"4:11.92",
"3:29.38",
"3:30.01",
"3:30.12",
"3:31.87",
"3:33.23",
"3:34.75",
"3:37.16",
"3:38.36",
"1:51.68",
"1:52.15",
"1:52.38",
"1:54.29",
"1:54.50",
"1:54.67",
"1:55.95",
"1:56.72",
"2:01.57",
"2:01.61",
"2:01.93",
"2:02.33",
"2:04.59",
"2:04.74",
"2:05.19",
"2:05.35",
"20.81",
"21.05",
"21.39",
"21.39",
"21.68",
"21.73",
"21.86",
"21.89",
"23.81",
"24.19",
"24.23",
"24.29",
"24.30",
"24.42",
"24.54",
"24.65",
"3:23.63",
"3:25.22",
"3:26.61",
"3:30.70",
"3:30.74",
"3:31.25",
"3:37.09",
NA,
"1:51.99",
"1:54.34",
"1:54.34",
"1:54.40",
"1:55.75",
"1:55.85",
"1:56.08",
"1:57.78",
"1:43.48",
"1:43.66",
"1:43.76",
"1:43.92",
"1:44.12",
"1:44.20",
"1:45.87",
"1:46.87",
"26.18",
"26.21",
"26.32",
"26.52",
"26.78",
"26.85",
"28.29",
"28.63",
"23.38",
"23.38",
"23.49",
"23.51",
"23.77",
"24.58",
"25.04",
NA,
"2:17.78",
"2:18.26",
"2:19.26",
"2:19.30",
"2:22.05",
"2:24.24",
"2:25.55",
"2:26.88",
"2:02.76",
"2:03.79",
"2:04.09",
"2:05.40",
"2:06.69",
"2:07.06",
"2:11.09",
"2:12.49",
"3:08.52",
"3:09.65",
"3:09.81",
"3:10.27",
"3:10.34",
"3:12.49",
"3:14.69",
"3:17.81"
),
Event = c(
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final"
),
DQ = c(
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Relay_Swimmer_1 = c(
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"SMOLIGA Olivia",
"NEAL Lia",
"TETZLOFF Alyssa",
"APOSTALON Anika",
"WASICK Kasia",
"GORBENKO Anastasia",
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"TARASEVICH Grigory",
"HOLLARD Tristan",
"KAWECKI Radoslaw",
"REID Christopher",
"RYAN Shane",
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"DRESSEL Caeleb",
"CARTER Dylan",
"CHADWICK Michael",
"HOWARD Robert",
"THORMEYER Markus",
"SHEBAT John",
"STJEPANOVIC Velimir",
"TANDY Bradley"
),
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"DAHLIA Kelsi",
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"GEER Margo",
"HAUGHEY Siobhan",
"MARGALIS Melanie",
"OSMAN Farida",
"NEALE Leah",
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"LIMA Felipe",
"FINNERTY Ian",
"FINK Nic",
"KOCH Marco",
"CORDES Kevin",
"WILSON Andrew",
"ANDREW Michael",
"LICON Will",
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"MAJCHRZAK Kacper",
"RYAN Shane",
"HELD Ryan",
"APPLE Zach",
"CHIERIGHINI Marcelo",
"JACKSON Tate",
"SMITH Giles",
"REID Christopher"
),
Relay_Swimmer_3 = c(
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NA,
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"HINDS Natalie",
"BLUME Pernille",
"MACK Linnea",
"RASMUS Claire",
"WEIR Amanda",
"BANIC Maddie",
"COUGHLIN Natalie",
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"DRESSEL Caeleb",
"COETZEE Ryan",
"SMITH Giles",
"SWITKOWSKI Jan",
"DARRAGH Mackenzie",
"PRENOT Josh",
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"BECKER Bowe",
"GREVERS Matthew",
"PIERONI Blake",
"VAZAIOS Andreas",
"SPAJARI Pedro",
"HAAS Townley",
"GROTHE Zane",
"COETZEE Ryan"
),
Relay_Swimmer_4 = c(
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"COMERFORD Mallory",
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"GASTALDELLO Beryl",
"QUAH Ting Wen",
"WOG Kelsey",
"STEWART Kendyl",
"GIBSON Sarah",
"LOVEMORE Tayla",
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"CHIERIGHINI Marcelo",
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"RESS Justin",
"SELISKAR Andrew",
"SHIELDS Tom",
"STRAVIUS Jeremy",
"LEWIS Clyde",
"SWITKOWSKI Jan",
"HOLLARD Tristan",
"de LUCCA Joao"
),
Split_50 = c(
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Split_100 = c(
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"36.02",
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"48.37",
"47.40",
"48.47",
"49.29",
"48.68"
),
Split_150 = c(
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NA,
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NA,
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NA,
NA,
NA,
NA,
NA,
NA,
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NA,
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NA,
"36.42",
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"23.29"
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Split_200 = c(
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NA,
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NA,
NA,
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NA,
NA,
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NA,
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NA,
NA,
NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"56.54",
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NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"34.54",
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"47.04",
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"48.09",
"49.18"
),
Split_250 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"35.76",
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"16.03",
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"22.35",
"22.26",
"22.49",
"22.57",
"22.61",
"22.69",
"23.14",
"23.82"
),
Split_300 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"36.77",
"38.41",
"39.59",
"38.92",
"38.70",
"39.39",
"40.26",
"38.76",
"34.14",
"34.62",
"35.43",
"36.45",
"35.61",
"36.04",
"35.54",
"38.03",
"52.40",
"52.22",
"52.81",
"53.99",
"54.02",
"54.44",
"55.23",
"55.86",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"49.73",
"51.07",
"49.54",
"53.08",
"51.23",
"52.53",
"53.42",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"47.45",
"47.31",
"47.92",
"46.92",
"47.73",
"47.47",
"48.14",
"50.42"
),
Split_350 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"30.64",
"32.13",
"30.69",
"32.61",
"31.77",
"31.95",
"32.07",
"32.62",
"28.41",
"29.89",
"29.26",
"28.54",
"29.79",
"29.08",
"29.89",
"28.29",
"24.71",
"25.05",
"24.64",
"24.73",
"25.50",
"25.05",
"25.68",
"26.01",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"22.44",
"22.10",
"21.99",
"22.24",
"22.72",
"22.16",
"23.12",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"22.82",
"22.68",
"22.56",
"22.77",
"22.45",
"23.21",
"23.56",
"23.73"
),
Split_400 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"30.03",
"31.72",
"29.59",
"30.89",
"30.11",
"30.65",
"30.69",
"31.40",
"27.14",
"28.45",
"27.20",
"27.05",
"28.96",
"27.97",
"29.31",
"27.05",
"51.68",
"51.92",
"51.87",
"52.65",
"53.22",
"53.06",
"54.69",
"54.93",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"47.20",
"46.63",
"47.81",
"47.47",
"47.93",
"47.11",
"49.62",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"47.31",
"47.36",
"46.97",
"47.94",
"47.04",
"48.32",
"49.17",
"49.53"
)
),
row.names = c(NA,-152L),
class = c("rowwise_df", "tbl_df",
"tbl", "data.frame"),
groups = structure(
list(.rows = structure(
list(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L,
16L,
17L,
18L,
19L,
20L,
21L,
22L,
23L,
24L,
25L,
26L,
27L,
28L,
29L,
30L,
31L,
32L,
33L,
34L,
35L,
36L,
37L,
38L,
39L,
40L,
41L,
42L,
43L,
44L,
45L,
46L,
47L,
48L,
49L,
50L,
51L,
52L,
53L,
54L,
55L,
56L,
57L,
58L,
59L,
60L,
61L,
62L,
63L,
64L,
65L,
66L,
67L,
68L,
69L,
70L,
71L,
72L,
73L,
74L,
75L,
76L,
77L,
78L,
79L,
80L,
81L,
82L,
83L,
84L,
85L,
86L,
87L,
88L,
89L,
90L,
91L,
92L,
93L,
94L,
95L,
96L,
97L,
98L,
99L,
100L,
101L,
102L,
103L,
104L,
105L,
106L,
107L,
108L,
109L,
110L,
111L,
112L,
113L,
114L,
115L,
116L,
117L,
118L,
119L,
120L,
121L,
122L,
123L,
124L,
125L,
126L,
127L,
128L,
129L,
130L,
131L,
132L,
133L,
134L,
135L,
136L,
137L,
138L,
139L,
140L,
141L,
142L,
143L,
144L,
145L,
146L,
147L,
148L,
149L,
150L,
151L,
152L
),
ptype = integer(0),
class = c("vctrs_list_of",
"vctrs_vctr", "list")
)),
row.names = c(NA,-152L),
class = c("tbl_df",
"tbl", "data.frame")
)
)
expect_equivalent(df_test, df_standard)
}
})
test_that("ISL inside swim_parse, ID by teams", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_16102020_Budapest_Match_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df_test <- file %>%
read_results() %>%
swim_parse() %>%
head(3)
df_standard <-
structure(list(Place = c(1, 2, 3), Lane = c(4, 3, 5), Name = c("SJOSTROM Sarah",
"SHKURDAI Anastasiya", "DAHLIA Kelsi"), Team = c("ENS", "ENS",
"CAC"), Finals = c("56.00", "56.07", "56.70"), Event = c("Women's 100m Butterfly",
"Women's 100m Butterfly", "Women's 100m Butterfly"), Points = c(9,
7, 6), DQ = c(0, 0, 0)), class = c("rowwise_df", "tbl_df", "tbl",
"data.frame"), row.names = c(NA, -3L), groups = structure(list(
.rows = structure(list(1L, 2L, 3L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -3L), class = c("tbl_df",
"tbl", "data.frame")))
expect_equivalent(df_test, df_standard)
}
})
# testthat::test_file("tests/testthat/test-ISL.R")
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test_that("ISL season 2 dataframe dims", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_01112020_Budapest_Match_6.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df <- swim_parse_ISL(
read_results(file),
splits = TRUE,
relay_swimmers = TRUE)
expect_equivalent(dim(df), c(324, 20)) # 324 is the normal number of rows, although there can be more depending on ties in the skins races
} # 20 is the normal number of columns
})
test_that("ISL season 2 whole dataframe", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_09112020_Budapest_Match_10.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df_test <- file %>%
read_results() %>%
swim_parse_ISL(splits = TRUE, relay_swimmers = TRUE)
df_standard <- structure(list(Place = c(1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4,
5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1,
2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6,
7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3,
4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8,
1, 2, 3, 4, 5, 6, 7, NA, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4,
5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1,
2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6,
7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3,
4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8,
1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5,
6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2,
3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7,
8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4,
5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 1,
2, 3, 4, 1, 2, 1, 2, 3, 4, 5, 6, 7, 8, 1, 2, 3, 4, 1, 2), Lane = c(1,
6, 2, 4, 5, 3, 7, 8, 5, 1, 6, 4, 7, 8, 2, 3, 5, 6, 2, 1, 7, 4,
8, 3, 1, 5, 3, 4, 2, 7, 8, 6, 4, 5, 3, 1, 7, 6, 2, 8, 2, 4, 1,
8, 6, 5, 3, 7, 4, 5, 1, 7, 2, 6, 8, 3, 5, 1, 8, 6, 2, 7, 3, 4,
2, 1, 5, 3, 6, 4, 7, 8, 3, 7, 4, 1, 2, 6, 5, 8, 6, 4, 2, 1, 3,
7, 5, 8, 7, 2, 8, 4, 6, 3, 1, 5, 6, 5, 4, 7, 8, 3, 2, 1, 5, 7,
1, 4, 3, 6, 8, 2, 5, 4, 7, 2, 6, 1, 3, 8, 1, 4, 3, 5, 6, 7, 2,
8, 5, 7, 6, 4, 3, 2, 1, 8, 7, 1, 4, 5, 3, 2, 8, 6, 5, 4, 1, 6,
3, 2, 7, 8, 1, 7, 4, 5, 3, 8, 6, 2, 5, 6, 2, 1, 4, 8, 3, 7, 3,
7, 4, 8, 6, 5, 2, 1, 3, 5, 1, 2, 8, 7, 6, 4, 5, 4, 2, 1, 8, 6,
7, 3, 3, 2, 4, 5, 1, 6, 8, 7, 6, 5, 4, 2, 3, 1, 7, 8, 6, 5, 4,
2, 3, 1, 8, 7, 3, 4, 6, 2, 7, 5, 1, 8, 2, 5, 3, 7, 8, 6, 4, 1,
3, 2, 5, 1, 4, 7, 6, 8, 5, 6, 3, 2, 4, 1, 7, 8, 8, 3, 4, 6, 7,
5, 2, 1, 3, 2, 7, 1, 8, 4, 6, 5, 7, 8, 5, 6, 2, 3, 4, 1, 3, 5,
2, 6, 4, 7, 1, 8, 2, 3, 1, 5, 6, 4, 7, 8, 2, 7, 5, 6, 3, 8, 4,
1, 4, 3, 7, 8, 2, 1, 5, 6, 4, 3, 5, 6, 5, 4, 6, 2, 5, 1, 4, 7,
3, 8, 6, 5, 3, 4, 5, 4), Name = c("GASTALDELLO Beryl", "DAHLIA Kelsi",
"TETZLOFF Aly", "WATTEL Marie", "HINDS Natalie", "ATKINSON Alia",
"BRUCE Tain", "BLACK Haley", "DRESSEL Caeleb", "SHIELDS Tom",
"CIESLAK Marcin", "VEKOVISHCHEV Mikhail", "SZABO Szebasztian",
"RIVOLTA Matteo", "CARTER Dylan", "GUY James", "NELSON Beata",
"FLICKINGER Hali", "GASSON Helena", "DELOOF Ali", "PELLEGRINI Federica",
"DAWSON Kathleen", "BURIAN Katalin", "WILLMOTT Aimee", "MURPHY Ryan",
"KAWECKI Radoslaw", "GREENBANK Luke", "DIENER Christian", "HVAS Tomoe",
"de DEUS Leonardo", "SANTI Fabio", "SZARANEK Mark", "LAZOR Annie",
"KING Lilly", "PICKREM Sydney", "SEBASTIAN Julia", "CARRARO Martina",
"HANNIS Molly", "SMITH Kierra", "CASTIGLIONI Arianna", "LICON Will",
"PRIGODA Kirill", "PRENOT Josh", "MARTINENGHI Nicolo", "FINK Nic",
"CORDES Kevin", "GREENE Darragh", "SCOZZOLI Fabio", NA, NA, NA,
NA, NA, NA, NA, NA, "DRESSEL Caeleb", "GKOLOMEEV Kristian", "SZABO Szebasztian",
"RESS Justin", "ROONEY Maxime", "MIRESSI Alessandro", "LEVEAUX Amaury",
"VEKOVISHCHEV Mikhail", "WEITZEIL Abbey", "GASTALDELLO Beryl",
"SMOLIGA Olivia", "ANDERSON Freya", "BROWN Erika", "HOPKIN Anna",
"MUNOZ del CAMPO Lidon", "MEDEIROS Etiene", "LANZA Vini", "HEINTZ Philip",
"VAZAIOS Andreas", "SELISKAR Andrew", "PRENOT Josh", "SZARANEK Mark",
"PERIBONIO Tomas", "SANTI Fabio", "NELSON Beata", "PICKREM Sydney",
"GORBENKO Anastasia", "GASSON Helena", "WILLMOTT Aimee", "VERRASZTO Evelyn",
"FERTEL Kelly", "BLACK Haley", "MARTINENGHI Nicolo", "SILVA FRANCA Felipe",
"SCOZZOLI Fabio", "PRIGODA Kirill", "FINK Nic", "GREENE Darragh",
"LICON Will", "CORDES Kevin", "HANNIS Molly", "KING Lilly", "ATKINSON Alia",
"CARRARO Martina", "CASTIGLIONI Arianna", "LAZOR Annie", "SEBASTIAN Julia",
"GORBENKO Anastasia", NA, NA, NA, NA, NA, NA, NA, NA, "SMOLIGA Olivia",
"TOUSSAINT Kira", "MEDEIROS Etiene", "TETZLOFF Aly", "BROWN Erika",
"MARSH Alyssa", "DAWSON Kathleen", "KONOPKA REID Katrina", "MURPHY Ryan",
"GUIDO Guilherme", "DIENER Christian", "RESS Justin", "STEWART Coleman",
"de DEUS Leonardo", "HVAS Tomoe", "SANTI Fabio", "FLICKINGER Hali",
"DUMONT Valentine", "ANDERSON Haley", "HIBBOTT Holly", "WILLMOTT Aimee",
"MUREZ Andi", "SARGENT Makayla", "OLIVEIRA Larissa", "ROMANCHUK Mykhaylo",
"SCHEFFER Fernando", "DEAN Tom", "BAQLAH Khader", "GUY James",
"HEIDTMANN Jacob", "MELO Luiz Altamir", "PERIBONIO Tomas", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "GASTALDELLO Beryl",
"WEITZEIL Abbey", "ANDERSON Freya", "HOPKIN Anna", "SCHMITT Allison",
"MUNOZ del CAMPO Lidon", "NEAL Lia", "OLIVEIRA Larissa", "DRESSEL Caeleb",
"MIRESSI Alessandro", "RESS Justin", "CHIERIGHINI Marcelo", "GKOLOMEEV Kristian",
"ROONEY Maxime", "SCOTT Duncan", "VEKOVISHCHEV Mikhail", "FLICKINGER Hali",
"GASSON Helena", "LARGE Emily", "HIBBOTT Holly", "VERRASZTO Evelyn",
"BRUCE Tain", "SARGENT Makayla", "FERTEL Kelly", "SHIELDS Tom",
"WANG Eddie", "LANZA Vini", "VAZAIOS Andreas", "de DEUS Leonardo",
"PRENOT Josh", "MELO Luiz Altamir", "SZARANEK Mark", "SMOLIGA Olivia",
"TOUSSAINT Kira", "BROWN Erika", "DELOOF Ali", "DAWSON Kathleen",
"TETZLOFF Aly", "MEDEIROS Etiene", "BURIAN Katalin", "MURPHY Ryan",
"CARTER Dylan", "KAWECKI Radoslaw", "GUIDO Guilherme", "STEWART Coleman",
"GREENBANK Luke", "RIVOLTA Matteo", "SANTI Fabio", "GASTALDELLO Beryl",
"GORBENKO Anastasia", "NELSON Beata", "KAMENEVA Maria", "FLICKINGER Hali",
"WILLMOTT Aimee", "KONOPKA REID Katrina", "BLACK Haley", "DRESSEL Caeleb",
"CIESLAK Marcin", "HVAS Tomoe", "VAZAIOS Andreas", "HEINTZ Philip",
"SELISKAR Andrew", "SCOTT Duncan", "de DEUS Leonardo", "ANDERSON Freya",
"MUREZ Andi", "SCHMITT Allison", "PELLEGRINI Federica", "DUMONT Valentine",
"RASMUS Claire", "BROWN Erika", "HIBBOTT Holly", "HAAS Townley",
"VEKOVISHCHEV Mikhail", "SCHEFFER Fernando", "DEAN Tom", "BAQLAH Khader",
"CORREIA Breno", "HEIDTMANN Jacob", "MELO Luiz Altamir", "GASTALDELLO Beryl",
"MARSH Alyssa", "DAHLIA Kelsi", "WATTEL Marie", "NELSON Beata",
"HOPKIN Anna", "BRUCE Tain", "BLACK Haley", "SZABO Szebasztian",
"DRESSEL Caeleb", "CIESLAK Marcin", "SHIELDS Tom", "RIVOLTA Matteo",
"ROONEY Maxime", "LANZA Vini", "GUY James", "KING Lilly", "ATKINSON Alia",
"CARRARO Martina", "LAZOR Annie", "CASTIGLIONI Arianna", "HANNIS Molly",
"SEBASTIAN Julia", "SMITH Kierra", "MARTINENGHI Nicolo", "SCOZZOLI Fabio",
"SILVA FRANCA Felipe", "LICON Will", "PRIGODA Kirill", "CORDES Kevin",
"FINK Nic", "GREENE Darragh", NA, NA, NA, NA, NA, NA, NA, NA,
"PICKREM Sydney", "FLICKINGER Hali", "WILLMOTT Aimee", "SARGENT Makayla",
"GORBENKO Anastasia", "FERTEL Kelly", "VERRASZTO Evelyn", "DUMONT Valentine",
"SCOTT Duncan", "HEINTZ Philip", "HEIDTMANN Jacob", "PRENOT Josh",
"PERIBONIO Tomas", "ROMANCHUK Mykhaylo", "SZARANEK Mark", "DEAN Tom",
"KING Lilly", "HANNIS Molly", "CARRARO Martina", "CASTIGLIONI Arianna",
"ANDERSON Freya", "LAZOR Annie", "SEBASTIAN Julia", "GASSON Helena",
"KING Lilly", "HANNIS Molly", "CARRARO Martina", "CASTIGLIONI Arianna",
"KING Lilly", "HANNIS Molly", "MURPHY Ryan", "GUIDO Guilherme",
"CARTER Dylan", "DIENER Christian", "STEWART Coleman", "RIVOLTA Matteo",
"RESS Justin", "de DEUS Leonardo", "MURPHY Ryan", "CARTER Dylan",
"DIENER Christian", "GUIDO Guilherme", "MURPHY Ryan", "CARTER Dylan"
), Team = c("LAC", "CAC", "LAC", "LON", "CAC", "LON", "AQC",
"AQC", "CAC", "LAC", "CAC", "LON", "AQC", "AQC", "LAC", "LON",
"CAC", "CAC", "LAC", "LAC", "AQC", "LON", "AQC", "LON", "LAC",
"CAC", "LON", "LON", "LAC", "AQC", "AQC", "CAC", "LON", "CAC",
"LON", "LAC", "AQC", "CAC", "LAC", "AQC", "LAC", "LON", "LAC",
"AQC", "CAC", "CAC", "LON", "AQC", "LON", "CAC", "LAC", "AQC",
"LAC", "CAC", "AQC", "LON", "CAC", "LAC", "AQC", "CAC", "LAC",
"AQC", "LON", "LON", "LAC", "LAC", "CAC", "LON", "CAC", "LON",
"AQC", "AQC", "LON", "AQC", "LON", "LAC", "LAC", "CAC", "CAC",
"AQC", "CAC", "LON", "LAC", "LAC", "LON", "AQC", "CAC", "AQC",
"AQC", "LAC", "AQC", "LON", "CAC", "LON", "LAC", "CAC", "CAC",
"CAC", "LON", "AQC", "AQC", "LON", "LAC", "LAC", "CAC", "AQC",
"LAC", "LON", "LON", "CAC", "AQC", "LAC", "CAC", "LON", "AQC",
"LAC", "CAC", "LAC", "LON", "AQC", "LAC", "LON", "LON", "CAC",
"CAC", "AQC", "LAC", "AQC", "CAC", "AQC", "CAC", "LON", "LON",
"LAC", "LAC", "AQC", "AQC", "LAC", "LON", "CAC", "LON", "LAC",
"AQC", "CAC", "CAC", "LON", "LAC", "CAC", "LON", "LAC", "AQC",
"AQC", "LAC", "AQC", "LON", "CAC", "LON", "AQC", "CAC", "LAC",
"LAC", "LAC", "LON", "LON", "CAC", "AQC", "CAC", "AQC", "CAC",
"AQC", "CAC", "AQC", "LAC", "LAC", "LON", "LON", "CAC", "LAC",
"LON", "LON", "AQC", "AQC", "LAC", "CAC", "LAC", "CAC", "LON",
"LON", "AQC", "LAC", "AQC", "CAC", "CAC", "LON", "CAC", "LAC",
"LON", "LAC", "AQC", "AQC", "LAC", "LAC", "CAC", "LON", "CAC",
"LON", "AQC", "AQC", "LAC", "LAC", "CAC", "LON", "CAC", "LON",
"AQC", "AQC", "CAC", "CAC", "LAC", "LON", "AQC", "LAC", "LON",
"AQC", "LON", "LAC", "CAC", "AQC", "AQC", "LAC", "CAC", "LON",
"CAC", "LON", "LAC", "LON", "CAC", "AQC", "LAC", "AQC", "LAC",
"LAC", "CAC", "LON", "CAC", "LON", "AQC", "AQC", "AQC", "CAC",
"CAC", "LAC", "AQC", "LAC", "LON", "LON", "CAC", "LON", "AQC",
"LON", "AQC", "CAC", "LAC", "LAC", "AQC", "AQC", "LAC", "LAC",
"LON", "CAC", "CAC", "LON", "CAC", "LAC", "LON", "LAC", "CAC",
"AQC", "LON", "AQC", "LON", "CAC", "LON", "LAC", "LAC", "CAC",
"AQC", "AQC", "LON", "AQC", "LAC", "LAC", "CAC", "AQC", "CAC",
"LON", "CAC", "CAC", "AQC", "AQC", "LON", "LON", "LAC", "LAC",
"CAC", "CAC", "AQC", "AQC", "CAC", "CAC", "LAC", "LON", "LAC",
"LON", "CAC", "AQC", "CAC", "AQC", "LAC", "LAC", "LON", "LON",
"LAC", "LAC"), Finals = c("55.71", "55.72", "56.46", "56.50", "57.10",
"57.21", "58.17", "1:00.14", "49.02", "49.17", "49.67", "49.88",
"49.89", "49.93", "50.70", "51.64", "2:02.51", "2:03.02", "2:05.29",
"2:05.62", "2:05.64", "2:05.92", "2:06.12", "2:08.34", "1:48.60",
"1:48.79", "1:50.50", "1:50.80", "1:53.54", "1:54.07", "1:57.73",
"1:58.84", "2:17.04", "2:17.18", "2:20.22", "2:20.89", "2:21.41",
"2:21.48", "2:22.20", "2:23.95", "2:04.12", "2:04.21", "2:06.60",
"2:07.04", "2:07.18", "2:07.22", "2:07.73", "2:07.81", "3:28.65",
"3:28.69", "3:29.69", "3:33.80", "3:34.26", "3:35.41", "3:38.42",
"3:41.19", "20.52", "20.89", "21.09", "21.17", "21.45", "21.48",
"21.80", "21.82", "23.45", "23.78", "24.05", "24.28", "24.34",
"24.41", "24.55", "24.59", "1:53.70", "1:53.73", "1:53.79", "1:54.17",
"1:54.97", "1:57.04", "1:57.05", "2:01.74", "2:05.95", "2:05.97",
"2:05.98", "2:08.02", "2:10.17", "2:11.31", "2:12.33", "2:23.47",
"25.89", "26.08", "26.39", "26.45", "26.88", "26.96", "27.11",
"27.12", "29.17", "29.18", "29.44", "29.60", "29.94", "30.42",
"30.73", NA, "3:05.52", "3:05.77", "3:06.99", "3:07.31", "3:11.19",
"3:11.65", "3:12.13", "3:12.52", "25.85", "26.32", "26.71", "26.75",
"26.81", "27.29", "27.48", "27.89", "22.75", "22.89", "23.24",
"23.27", "23.29", "23.76", "24.63", "24.81", "3:59.78", "4:00.05",
"4:03.74", "4:04.58", "4:07.16", "4:09.16", "4:09.45", "4:11.10",
"3:38.93", "3:41.07", "3:41.91", "3:42.09", "3:42.30", "3:43.96",
"3:50.60", "3:52.11", "3:47.13", "3:48.15", "3:49.87", "3:52.26",
"3:52.71", "3:54.04", "3:56.47", "3:58.14", "3:21.26", "3:22.78",
"3:24.73", "3:24.77", "3:25.68", "3:27.70", "3:28.04", "3:28.40",
"51.16", "51.26", "51.52", "51.97", "53.37", "53.42", "54.09",
"54.16", "45.56", "46.23", "46.25", "46.53", "46.73", "46.85",
"46.89", "46.99", "2:04.36", "2:07.27", "2:07.45", "2:08.60",
"2:09.75", "2:10.09", "2:10.80", "2:13.57", "1:49.78", "1:50.14",
"1:52.32", "1:52.92", "1:53.15", "1:54.93", "1:55.09", "1:58.74",
"55.92", "56.30", "57.24", "57.75", "58.02", "58.21", "58.44",
"59.23", "49.93", "50.11", "50.17", "50.19", "50.23", "50.54",
"50.78", "53.11", "57.43", "57.90", "58.60", "58.64", "1:00.22",
"1:01.63", "1:03.02", "1:07.23", "50.48", "51.36", "52.11", "52.73",
"52.91", "53.18", "53.19", "55.78", "1:52.82", "1:53.98", "1:54.45",
"1:55.10", "1:55.39", "1:57.17", "1:57.82", "1:57.88", "1:41.84",
"1:42.34", "1:42.71", "1:43.31", "1:43.40", "1:43.69", "1:45.58",
"1:46.47", "25.30", "25.31", "25.35", "25.60", "25.68", "25.95",
"27.09", "27.25", "21.86", "22.06", "22.55", "22.68", "22.77",
"22.87", "22.96", "23.55", "1:03.15", "1:04.43", "1:04.54", "1:04.55",
"1:04.61", "1:04.76", "1:05.51", "1:06.61", "56.46", "57.23",
"57.47", "57.88", "57.95", "58.29", "58.35", "59.10", "3:16.14",
"3:17.22", "3:18.18", "3:19.04", "3:19.94", "3:20.05", "3:20.53",
"3:21.92", "4:25.90", "4:29.52", "4:32.93", "4:34.03", "4:37.37",
"4:38.09", "4:39.30", "4:55.35", "4:07.88", "4:07.99", "4:08.03",
"4:08.60", "4:09.71", "4:10.00", "4:10.09", "4:10.35", "29.16",
"29.77", "29.81", "29.95", "30.13", "30.34", "30.60", "30.71",
"29.63", "29.99", "30.21", "30.33", "29.24", "29.85", "22.85",
"23.12", "23.28", "23.30", "23.37", "23.50", "23.51", "23.82",
"23.54", "23.93", "24.31", "24.40", "24.18", "24.99"), Event = c("Women's 100m Butterfly",
"Women's 100m Butterfly", "Women's 100m Butterfly", "Women's 100m Butterfly",
"Women's 100m Butterfly", "Women's 100m Butterfly", "Women's 100m Butterfly",
"Women's 100m Butterfly", "Men's 100m Butterfly", "Men's 100m Butterfly",
"Men's 100m Butterfly", "Men's 100m Butterfly", "Men's 100m Butterfly",
"Men's 100m Butterfly", "Men's 100m Butterfly", "Men's 100m Butterfly",
"Women's 200m Backstroke", "Women's 200m Backstroke", "Women's 200m Backstroke",
"Women's 200m Backstroke", "Women's 200m Backstroke", "Women's 200m Backstroke",
"Women's 200m Backstroke", "Women's 200m Backstroke", "Men's 200m Backstroke",
"Men's 200m Backstroke", "Men's 200m Backstroke", "Men's 200m Backstroke",
"Men's 200m Backstroke", "Men's 200m Backstroke", "Men's 200m Backstroke",
"Men's 200m Backstroke", "Women's 200m Breaststroke", "Women's 200m Breaststroke",
"Women's 200m Breaststroke", "Women's 200m Breaststroke", "Women's 200m Breaststroke",
"Women's 200m Breaststroke", "Women's 200m Breaststroke", "Women's 200m Breaststroke",
"Men's 200m Breaststroke", "Men's 200m Breaststroke", "Men's 200m Breaststroke",
"Men's 200m Breaststroke", "Men's 200m Breaststroke", "Men's 200m Breaststroke",
"Men's 200m Breaststroke", "Men's 200m Breaststroke", "Women's 4x100m Freestyle",
"Women's 4x100m Freestyle", "Women's 4x100m Freestyle", "Women's 4x100m Freestyle",
"Women's 4x100m Freestyle", "Women's 4x100m Freestyle", "Women's 4x100m Freestyle",
"Women's 4x100m Freestyle", "Men's 50m Freestyle", "Men's 50m Freestyle",
"Men's 50m Freestyle", "Men's 50m Freestyle", "Men's 50m Freestyle",
"Men's 50m Freestyle", "Men's 50m Freestyle", "Men's 50m Freestyle",
"Women's 50m Freestyle", "Women's 50m Freestyle", "Women's 50m Freestyle",
"Women's 50m Freestyle", "Women's 50m Freestyle", "Women's 50m Freestyle",
"Women's 50m Freestyle", "Women's 50m Freestyle", "Men's 200m Individual Medley",
"Men's 200m Individual Medley", "Men's 200m Individual Medley",
"Men's 200m Individual Medley", "Men's 200m Individual Medley",
"Men's 200m Individual Medley", "Men's 200m Individual Medley",
"Men's 200m Individual Medley", "Women's 200m Individual Medley",
"Women's 200m Individual Medley", "Women's 200m Individual Medley",
"Women's 200m Individual Medley", "Women's 200m Individual Medley",
"Women's 200m Individual Medley", "Women's 200m Individual Medley",
"Women's 200m Individual Medley", "Men's 50m Breaststroke", "Men's 50m Breaststroke",
"Men's 50m Breaststroke", "Men's 50m Breaststroke", "Men's 50m Breaststroke",
"Men's 50m Breaststroke", "Men's 50m Breaststroke", "Men's 50m Breaststroke",
"Women's 50m Breaststroke", "Women's 50m Breaststroke", "Women's 50m Breaststroke",
"Women's 50m Breaststroke", "Women's 50m Breaststroke", "Women's 50m Breaststroke",
"Women's 50m Breaststroke", "Women's 50m Breaststroke", "Men's 4x100m Freestyle",
"Men's 4x100m Freestyle", "Men's 4x100m Freestyle", "Men's 4x100m Freestyle",
"Men's 4x100m Freestyle", "Men's 4x100m Freestyle", "Men's 4x100m Freestyle",
"Men's 4x100m Freestyle", "Women's 50m Backstroke", "Women's 50m Backstroke",
"Women's 50m Backstroke", "Women's 50m Backstroke", "Women's 50m Backstroke",
"Women's 50m Backstroke", "Women's 50m Backstroke", "Women's 50m Backstroke",
"Men's 50m Backstroke", "Men's 50m Backstroke", "Men's 50m Backstroke",
"Men's 50m Backstroke", "Men's 50m Backstroke", "Men's 50m Backstroke",
"Men's 50m Backstroke", "Men's 50m Backstroke", "Women's 400m Freestyle",
"Women's 400m Freestyle", "Women's 400m Freestyle", "Women's 400m Freestyle",
"Women's 400m Freestyle", "Women's 400m Freestyle", "Women's 400m Freestyle",
"Women's 400m Freestyle", "Men's 400m Freestyle", "Men's 400m Freestyle",
"Men's 400m Freestyle", "Men's 400m Freestyle", "Men's 400m Freestyle",
"Men's 400m Freestyle", "Men's 400m Freestyle", "Men's 400m Freestyle",
"Women's 4x100m Medley Relay", "Women's 4x100m Medley Relay",
"Women's 4x100m Medley Relay", "Women's 4x100m Medley Relay",
"Women's 4x100m Medley Relay", "Women's 4x100m Medley Relay",
"Women's 4x100m Medley Relay", "Women's 4x100m Medley Relay",
"Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay",
"Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay",
"Men's 4x100m Medley Relay", "Men's 4x100m Medley Relay", "Women's 100m Freestyle",
"Women's 100m Freestyle", "Women's 100m Freestyle", "Women's 100m Freestyle",
"Women's 100m Freestyle", "Women's 100m Freestyle", "Women's 100m Freestyle",
"Women's 100m Freestyle", "Men's 100m Freestyle", "Men's 100m Freestyle",
"Men's 100m Freestyle", "Men's 100m Freestyle", "Men's 100m Freestyle",
"Men's 100m Freestyle", "Men's 100m Freestyle", "Men's 100m Freestyle",
"Women's 200m Butterfly", "Women's 200m Butterfly", "Women's 200m Butterfly",
"Women's 200m Butterfly", "Women's 200m Butterfly", "Women's 200m Butterfly",
"Women's 200m Butterfly", "Women's 200m Butterfly", "Men's 200m Butterfly",
"Men's 200m Butterfly", "Men's 200m Butterfly", "Men's 200m Butterfly",
"Men's 200m Butterfly", "Men's 200m Butterfly", "Men's 200m Butterfly",
"Men's 200m Butterfly", "Women's 100m Backstroke", "Women's 100m Backstroke",
"Women's 100m Backstroke", "Women's 100m Backstroke", "Women's 100m Backstroke",
"Women's 100m Backstroke", "Women's 100m Backstroke", "Women's 100m Backstroke",
"Men's 100m Backstroke", "Men's 100m Backstroke", "Men's 100m Backstroke",
"Men's 100m Backstroke", "Men's 100m Backstroke", "Men's 100m Backstroke",
"Men's 100m Backstroke", "Men's 100m Backstroke", "Women's 100m Individual Medley",
"Women's 100m Individual Medley", "Women's 100m Individual Medley",
"Women's 100m Individual Medley", "Women's 100m Individual Medley",
"Women's 100m Individual Medley", "Women's 100m Individual Medley",
"Women's 100m Individual Medley", "Men's 100m Individual Medley",
"Men's 100m Individual Medley", "Men's 100m Individual Medley",
"Men's 100m Individual Medley", "Men's 100m Individual Medley",
"Men's 100m Individual Medley", "Men's 100m Individual Medley",
"Men's 100m Individual Medley", "Women's 200m Freestyle", "Women's 200m Freestyle",
"Women's 200m Freestyle", "Women's 200m Freestyle", "Women's 200m Freestyle",
"Women's 200m Freestyle", "Women's 200m Freestyle", "Women's 200m Freestyle",
"Men's 200m Freestyle", "Men's 200m Freestyle", "Men's 200m Freestyle",
"Men's 200m Freestyle", "Men's 200m Freestyle", "Men's 200m Freestyle",
"Men's 200m Freestyle", "Men's 200m Freestyle", "Women's 50m Butterfly",
"Women's 50m Butterfly", "Women's 50m Butterfly", "Women's 50m Butterfly",
"Women's 50m Butterfly", "Women's 50m Butterfly", "Women's 50m Butterfly",
"Women's 50m Butterfly", "Men's 50m Butterfly", "Men's 50m Butterfly",
"Men's 50m Butterfly", "Men's 50m Butterfly", "Men's 50m Butterfly",
"Men's 50m Butterfly", "Men's 50m Butterfly", "Men's 50m Butterfly",
"Women's 100m Breaststroke", "Women's 100m Breaststroke", "Women's 100m Breaststroke",
"Women's 100m Breaststroke", "Women's 100m Breaststroke", "Women's 100m Breaststroke",
"Women's 100m Breaststroke", "Women's 100m Breaststroke", "Men's 100m Breaststroke",
"Men's 100m Breaststroke", "Men's 100m Breaststroke", "Men's 100m Breaststroke",
"Men's 100m Breaststroke", "Men's 100m Breaststroke", "Men's 100m Breaststroke",
"Men's 100m Breaststroke", "Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle",
"Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle",
"Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle", "Mixed 4x100m Freestyle",
"Women's 400m Individual Medley", "Women's 400m Individual Medley",
"Women's 400m Individual Medley", "Women's 400m Individual Medley",
"Women's 400m Individual Medley", "Women's 400m Individual Medley",
"Women's 400m Individual Medley", "Women's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Men's 400m Individual Medley", "Men's 400m Individual Medley",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Women's 50m Breaststroke Skins", "Women's 50m Breaststroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins",
"Men's 50m Backstroke Skins", "Men's 50m Backstroke Skins"),
Points = c(12, 7, 6, 5, 4, 3, 0, -1, 10, 7, 6, 5, 4, 3, 2,
0, 10, 7, 6, 5, 4, 3, 2, 0, 19, 7, 6, 5, 0, 0, 0, -1, 10,
7, 6, 5, 4, 3, 2, 0, 9, 7, 6, 5, 4, 3, 2, 1, 20, 14, 12,
10, 8, 6, 4, -2, 19, 7, 6, 5, 0, 0, 0, 0, 15, 7, 6, 5, 4,
0, 0, 0, 10, 7, 6, 5, 4, 3, 2, -1, 15, 7, 6, 5, 4, 0, 0,
-1, 15, 7, 6, 5, 4, 0, 0, 0, 15, 7, 6, 5, 4, 0, 0, -2, 18,
14, 12, 10, 8, 6, 4, 2, 15, 7, 6, 5, 4, 0, 0, 0, 15, 7, 6,
5, 4, 0, 0, 0, 12, 7, 6, 5, 4, 3, 0, -1, 12, 7, 6, 5, 4,
3, -1, -1, 20, 14, 12, 10, 8, 6, 4, 0, 18, 14, 12, 10, 8,
6, 4, 2, 19, 7, 6, 5, 0, 0, 0, 0, 9, 7, 6, 5, 4, 3, 2, 1,
19, 7, 6, 5, 0, 0, 0, -1, 15, 7, 6, 5, 4, 0, 0, 0, 15, 7,
6, 5, 4, 0, 0, 0, 10, 7, 6, 5, 4, 3, 2, 0, 19, 7, 6, 5, 0,
0, -1, -1, 24, 7, 6, 0, 0, 0, 0, -1, 12, 7, 6, 5, 4, 3, 0,
0, 10, 7, 6, 5, 4, 3, 2, 0, 12, 7, 6, 5, 4, 3, -1, -1, 19,
7, 6, 5, 0, 0, 0, 0, 10, 7, 6, 5, 4, 3, 2, 0, 10, 7, 6, 5,
4, 3, 2, 0, 18, 14, 12, 10, 8, 6, 4, 2, 19, 7, 6, 5, 0, 0,
0, -1, 9, 7, 6, 5, 4, 3, 2, 1, 15, 7, 6, 5, 4, 0, 0, 0, 9,
7, 6, 5, 14, 7, 10, 7, 6, 5, 4, 3, 2, 0, 9, 7, 6, 5, 14,
7), DQ = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0), Relay_Swimmer_1 = c(NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "HOPKIN Anna",
"SMOLIGA Olivia", "MUREZ Andi", "MUNOZ del CAMPO Lidon",
"STEWART Kendyl", "NEAL Lia", "KONOPKA REID Katrina", "HIBBOTT Holly",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, "MAJCHRZAK Kacper", "MIRESSI Alessandro", "FERREIRA Marco",
"SCOTT Duncan", "CLOGG Elliot", "CIESLAK Marcin", "CORREIA Breno",
"CARTER Dylan", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "SMOLIGA Olivia", "TOUSSAINT Kira",
"DELOOF Ali", "NELSON Beata", "KAMENEVA Maria", "GASSON Helena",
"PELLEGRINI Federica", "BURIAN Katalin", "MURPHY Ryan", "RIVOLTA Matteo",
"DIENER Christian", "STEWART Coleman", "GREENBANK Luke",
"de DEUS Leonardo", "KAWECKI Radoslaw", "CHRISTOU Apostolos",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "RESS Justin", "GKOLOMEEV Kristian",
"VEKOVISHCHEV Mikhail", "CHRISTOU Apostolos", "JACKSON Tate",
"MIRESSI Alessandro", "VAZAIOS Andreas", "SZABO Szebasztian",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA),
Relay_Swimmer_2 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "ANDERSON Freya", "BROWN Erika",
"GORBENKO Anastasia", "PELLEGRINI Federica", "RASMUS Claire",
"BURCHILL Veronica", "MEDEIROS Etiene", "WEST Harriet", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "JACKSON Tate", "SPAJARI Pedro", "SHIELDS Tom", "KUSCH Marius",
"DEAN Tom", "WANG Eddie", "SANTOS Gabriel", "CHRISTOU Apostolos",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "KING Lilly", "ATKINSON Alia", "GORBENKO Anastasia",
"HANNIS Molly", "LAZOR Annie", "SEBASTIAN Julia", "CARRARO Martina",
"CASTIGLIONI Arianna", "SILVA FRANCA Felipe", "MARTINENGHI Nicolo",
"PRIGODA Kirill", "FINK Nic", "GREENE Darragh", "SCOZZOLI Fabio",
"CORDES Kevin", "LICON Will", NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"DRESSEL Caeleb", "SHIELDS Tom", "KUSCH Marius", "FERREIRA Marco",
"MAJCHRZAK Kacper", "CHIERIGHINI Marcelo", "CLOGG Elliot",
"SPAJARI Pedro", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA), Relay_Swimmer_3 = c(NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "WATTEL Marie",
"SCHMITT Allison", "MARSH Alyssa", "OLIVEIRA Larissa", "McLAUGHLIN Katie",
"FLICKINGER Hali", "BRUCE Tain", "LARGE Emily", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"HAAS Townley", "SZABO Szebasztian", "GKOLOMEEV Kristian",
"LANZA Vini", "LEVEAUX Amaury", "KAWECKI Radoslaw", "MELO Luiz Altamir",
"HVAS Tomoe", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "DAHLIA Kelsi", "WATTEL Marie", "GASTALDELLO Beryl",
"HINDS Natalie", "WEST Harriet", "STEWART Kendyl", "BRUCE Tain",
"TOURETSKI Sasha Alexandra", "SHIELDS Tom", "SZABO Szebasztian",
"KUSCH Marius", "DRESSEL Caeleb", "VEKOVISHCHEV Mikhail",
"HEINTZ Philip", "JACKSON Tate", "CARTER Dylan", NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "SMOLIGA Olivia", "GASTALDELLO Beryl",
"KAMENEVA Maria", "TETZLOFF Aly", "SCHMITT Allison", "MUNOZ del CAMPO Lidon",
"WATTEL Marie", "PELLEGRINI Federica", NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA), Relay_Swimmer_4 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "KAMENEVA Maria", "HINDS Natalie", "TETZLOFF Aly",
"DUMONT Valentine", "WEITZEIL Abbey", "DAHLIA Kelsi", "TOURETSKI Sasha Alexandra",
"DAWSON Kathleen", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "DRESSEL Caeleb", "CHIERIGHINI Marcelo",
"ROONEY Maxime", "VEKOVISHCHEV Mikhail", "VAZAIOS Andreas",
"SZARANEK Mark", "HEINTZ Philip", "SELISKAR Andrew", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "BROWN Erika", "ANDERSON Freya", "WEITZEIL Abbey", "SCHMITT Allison",
"HOPKIN Anna", "TETZLOFF Aly", "MUNOZ del CAMPO Lidon", "KONOPKA REID Katrina",
"ROONEY Maxime", "MIRESSI Alessandro", "SCOTT Duncan", "MAJCHRZAK Kacper",
"LANZA Vini", "CHIERIGHINI Marcelo", "RESS Justin", "FERREIRA Marco",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "BROWN Erika", "WEITZEIL Abbey",
"ANDERSON Freya", "MUREZ Andi", "HINDS Natalie", "OLIVEIRA Larissa",
"HOPKIN Anna", "DUMONT Valentine", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA), Split_50 = c("25.85", "26.04",
"26.07", "26.09", "26.70", "26.88", "27.23", "27.46", "23.32",
"22.85", "23.39", "23.19", "23.09", "23.23", "23.30", "23.83",
"28.70", "29.45", "29.65", "29.20", "29.55", "29.08", "29.60",
"30.07", "25.50", "26.36", "26.04", "25.72", "26.72", "26.40",
"26.81", "27.38", "31.76", "30.61", "32.37", "32.09", "32.51",
"32.06", "32.35", "33.06", "28.65", "28.08", "29.21", "28.32",
"28.90", "28.62", "28.93", "28.41", "25.12", "24.98", "24.87",
"25.71", "25.48", "26.02", "26.13", "26.69", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "24.54",
"24.29", "25.39", "24.51", "25.02", "25.58", "25.39", "26.22",
"27.24", "28.09", "28.04", "27.53", "28.66", "28.58", "28.39",
"27.41", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "22.59", "22.33", "22.65", "22.68", "22.90",
"22.81", "22.95", "22.24", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "28.25", "28.68", "28.49",
"28.58", "29.01", "28.69", "28.75", "28.85", "25.93", "25.08",
"25.65", "25.89", "25.65", "25.71", "25.37", "26.27", "27.31",
"27.57", "27.29", "27.88", "28.06", "27.85", "28.78", "29.09",
"23.96", "24.95", "24.61", "24.46", "24.65", "24.92", "24.93",
"24.67", "24.77", "24.43", "25.54", "24.87", "25.57", "25.51",
"25.97", "25.87", "22.14", "22.26", "22.17", "21.88", "22.32",
"22.13", "22.66", "22.52", "28.52", "28.84", "28.88", "29.20",
"28.98", "29.03", "29.34", "29.35", "24.57", "25.02", "25.07",
"25.80", "25.13", "25.63", "25.11", "26.02", "27.21", "27.03",
"27.51", "27.77", "27.92", "28.04", "28.11", "28.90", "24.03",
"23.81", "24.42", "24.19", "24.29", "24.63", "24.74", "25.44",
"26.33", "26.27", "26.77", "26.69", "28.01", "28.37", "27.89",
"28.87", "22.96", "23.50", "23.53", "24.10", "24.04", "24.16",
"24.44", "24.85", "26.80", "26.84", "27.52", "27.42", "27.35",
"27.92", "27.37", "27.95", "23.83", "24.12", "24.58", "24.14",
"24.32", "24.49", "24.55", "24.02", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "29.59", "30.18",
"31.00", "30.73", "30.57", "30.56", "31.09", "31.71", "26.42",
"26.58", "27.08", "27.41", "27.23", "27.28", "27.39", "27.49",
"22.18", "22.31", "22.80", "22.78", "22.59", "22.15", "22.96",
"22.61", "29.50", "29.05", "29.47", "29.47", "28.84", "29.42",
"29.43", "30.29", "25.66", "26.10", "26.81", "26.33", "26.45",
"27.09", "26.61", "26.52", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA), Split_100 = c("29.86", "29.68", "30.39",
"30.41", "30.40", "30.33", "30.94", "32.68", "25.70", "26.32",
"26.28", "26.69", "26.80", "26.70", "27.40", "27.81", "30.84",
"31.06", "32.11", "31.74", "31.64", "31.91", "31.97", "31.99",
"27.88", "28.29", "28.34", "28.20", "27.94", "28.75", "29.66",
"29.62", "35.25", "35.73", "35.78", "35.78", "36.64", "36.97",
"35.76", "37.01", "31.32", "31.59", "32.12", "32.48", "32.44",
"31.97", "32.29", "32.98", "52.29", "51.95", "52.16", "53.64",
"53.31", "54.46", "54.92", "55.44", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "29.38", "28.59",
"28.09", "28.18", "29.63", "29.01", "29.33", "29.69", "32.29",
"31.83", "32.67", "32.29", "33.54", "32.96", "33.37", "36.64",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "46.98", "46.58", "47.59", "47.14", "47.95", "47.12",
"47.46", "46.56", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "30.22", "30.68", "30.62", "30.74",
"30.98", "30.99", "31.09", "30.70", "27.46", "27.56", "28.37",
"27.80", "28.06", "27.67", "27.77", "28.08", "56.24", "57.07",
"57.76", "57.47", "58.20", "57.96", "59.09", "59.76", "49.80",
"51.39", "50.77", "50.85", "50.99", "51.38", "50.67", "51.55",
"26.39", "26.83", "25.98", "27.10", "27.80", "27.91", "28.12",
"28.29", "23.42", "23.97", "24.08", "24.65", "24.41", "24.72",
"24.23", "24.47", "31.42", "32.50", "32.33", "33.10", "33.13",
"32.70", "32.85", "33.93", "28.20", "28.19", "28.81", "28.99",
"29.04", "29.33", "28.54", "29.54", "28.71", "29.27", "29.73",
"29.98", "30.10", "30.17", "30.33", "30.33", "25.90", "26.30",
"25.75", "26.00", "25.94", "25.91", "26.04", "27.67", "31.10",
"31.63", "31.83", "31.95", "32.21", "33.26", "35.13", "38.36",
"27.52", "27.86", "28.58", "28.63", "28.87", "29.02", "28.75",
"30.93", "28.98", "28.98", "28.90", "29.34", "28.98", "29.81",
"29.48", "29.91", "25.83", "25.91", "26.14", "26.49", "26.21",
"26.59", "26.63", "25.90", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "33.56", "34.25", "33.54",
"33.82", "34.04", "34.20", "34.42", "34.90", "30.04", "30.65",
"30.39", "30.47", "30.72", "31.01", "30.96", "31.61", "46.22",
"46.87", "47.53", "47.27", "47.43", "46.74", "47.76", "47.21",
"33.02", "32.67", "33.32", "33.19", "34.37", "34.06", "33.73",
"34.30", "29.18", "30.02", "30.55", "30.35", "30.08", "30.14",
"30.78", "30.47", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), Split_150 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "31.30", "31.40", "31.78",
"32.30", "32.07", "32.48", "32.06", "33.00", "27.99", "27.10",
"28.32", "28.57", "28.96", "29.34", "30.47", "31.00", "35.18",
"36.44", "36.06", "36.59", "36.43", "36.50", "36.69", "37.43",
"32.00", "32.25", "32.48", "33.09", "32.94", "32.80", "32.99",
"33.68", "24.89", "24.74", "24.75", "25.79", "25.98", "25.53",
"25.57", "26.13", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "32.81", "32.81", "32.70", "33.21",
"32.34", "34.48", "33.90", "36.91", "36.63", "35.77", "35.96",
"37.56", "36.62", "39.56", "38.72", "44.16", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "22.28",
"21.81", "21.84", "22.11", "22.51", "22.92", "22.69", "22.00",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, "30.46", "30.81", "30.55", "31.04", "31.22", "31.32",
"31.40", "31.04", "27.69", "27.78", "28.49", "28.26", "28.24",
"28.13", "28.40", "28.50", "29.49", "29.65", "30.42", "29.94",
"30.54", "31.15", "30.69", "30.00", "26.43", "26.09", "26.16",
"27.10", "27.11", "27.24", "27.31", "27.23", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "32.14",
"32.59", "32.76", "33.38", "33.55", "33.77", "33.49", "34.57",
"28.16", "28.42", "28.88", "28.75", "29.38", "29.73", "29.87",
"30.88", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, "28.92", "29.20", "29.21", "29.35", "29.62",
"29.73", "30.51", "30.18", "25.97", "26.08", "26.18", "26.26",
"26.31", "26.60", "26.92", "27.09", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "21.96", "22.17",
"22.17", "22.09", "22.56", "21.76", "22.24", "21.94", "34.30",
"34.58", "34.60", "34.77", "36.97", "36.18", "35.56", "38.57",
"31.45", "33.20", "32.54", "33.26", "32.26", "32.14", "32.16",
"32.58", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA), Split_200 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "31.67", "31.11", "31.75", "32.38",
"32.38", "32.45", "32.49", "33.28", "27.23", "27.04", "27.80",
"28.31", "29.92", "29.58", "30.79", "30.84", "34.85", "34.40",
"36.01", "36.43", "35.83", "35.95", "37.40", "36.45", "32.15",
"32.29", "32.79", "33.15", "32.90", "33.83", "33.52", "32.74",
"51.76", "52.00", "51.69", "53.82", "54.39", "54.49", "53.85",
"54.74", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, "26.97", "28.04", "27.61", "28.27", "27.98",
"27.97", "28.43", "28.92", "29.79", "30.28", "29.31", "30.64",
"31.35", "30.21", "31.85", "35.26", NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "47.04", "46.25",
"46.23", "47.23", "47.35", "47.85", "47.37", "47.13", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"30.60", "30.60", "30.79", "31.21", "31.39", "31.97", "31.40",
"31.35", "27.81", "28.23", "28.50", "28.29", "28.53", "28.70",
"28.86", "29.23", "1:03.03", "1:03.75", "1:04.62", "1:04.15",
"1:04.66", "1:05.95", "1:05.28", "1:03.48", "56.54", "56.13",
"56.77", "58.18", "57.88", "58.26", "58.49", "58.32", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
"32.28", "33.34", "33.48", "32.92", "34.09", "34.59", "35.12",
"35.72", "28.85", "28.51", "29.56", "29.38", "29.60", "30.24",
"31.57", "32.30", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "28.12", "28.96", "28.82", "28.99",
"29.44", "29.71", "30.46", "29.84", "26.21", "26.23", "25.81",
"26.42", "26.56", "26.01", "27.48", "29.46", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "45.72",
"46.53", "46.71", "46.77", "46.88", "45.95", "47.58", "46.57",
"33.35", "33.26", "34.37", "34.37", "36.00", "35.35", "34.32",
"36.85", "31.67", "32.21", "32.09", "32.26", "32.44", "31.30",
"32.17", "31.70", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), Split_250 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "25.32", "25.08",
"24.90", "25.48", "26.05", "25.58", "26.02", "26.33", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "21.80", "22.03", "22.14", "22.63", "22.67", "22.18",
"23.02", "23.14", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "30.59", "30.55", "30.83", "30.94",
"31.20", "31.56", "31.28", "31.25", "27.69", "28.00", "28.19",
"27.94", "28.47", "28.25", "28.95", "29.94", "26.02", "25.77",
"25.71", "26.62", "26.47", "25.60", "27.13", "27.58", "22.22",
"22.57", "23.27", "23.13", "22.74", "23.81", "24.27", "23.39",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "24.72", "25.05", "24.98", "24.80",
"25.92", "25.38", "25.41", "25.65", "36.60", "39.84", "37.42",
"38.47", "38.50", "39.37", "41.40", "45.07", "35.05", "35.21",
"34.21", "33.82", "34.79", "35.94", "33.99", "36.43", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Split_300 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "52.52", "52.49", "53.07", "53.09", "53.71", "53.09",
"54.54", "54.94", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "46.22", "46.87", "46.71",
"46.85", "47.85", "47.59", "48.09", "49.53", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "30.48",
"30.31", "30.93", "30.89", "31.27", "31.44", "31.81", "32.19",
"27.78", "28.40", "27.83", "28.06", "28.43", "28.26", "29.83",
"29.79", "56.37", "56.59", "56.20", "57.92", "57.36", "56.93",
"58.53", "59.87", "48.92", "49.32", "50.30", "49.55", "49.30",
"51.24", "52.88", "51.25", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "52.09",
"52.63", "52.64", "53.01", "53.61", "53.46", "53.58", "53.37",
"37.27", "39.41", "39.15", "39.20", "38.52", "40.15", "41.97",
"44.14", "36.22", "35.11", "35.18", "34.67", "35.89", "36.40",
"35.55", "36.74", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA), Split_350 = c(NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "24.75", "25.11",
"24.81", "25.63", "25.06", "25.21", "25.74", "26.70", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "21.79", "21.52", "21.90", "21.72", "23.19", "23.31",
"23.42", "23.51", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, "30.30", "29.59", "30.89", "30.81",
"31.03", "31.80", "32.10", "32.89", "27.80", "28.34", "27.81",
"28.26", "28.00", "28.46", "30.77", "30.28", "24.25", "24.51",
"24.00", "25.17", "25.14", "25.16", "25.47", "25.75", "21.50",
"21.94", "22.29", "22.21", "22.90", "22.07", "21.92", "22.56",
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, "24.63", "24.01", "24.93", "24.69",
"24.93", "25.54", "24.72", "26.60", "31.68", "30.97", "32.89",
"32.37", "32.75", "32.50", "32.16", "34.08", "29.67", "29.34",
"29.33", "30.76", "29.43", "29.19", "29.98", "28.83", NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), Split_400 = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, "52.08", "52.25", "52.77", "53.25", "52.85", "53.37",
"55.11", "56.07", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, "45.28", "46.07", "46.46",
"46.09", "48.04", "49.09", "49.21", "49.30", NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "28.88",
"28.83", "30.64", "30.37", "31.06", "31.39", "31.62", "32.83",
"26.77", "27.68", "27.07", "27.59", "26.92", "28.78", "30.65",
"30.02", "51.49", "50.74", "51.29", "52.72", "52.49", "53.20",
"53.57", "55.03", "46.00", "45.94", "46.89", "46.19", "47.51",
"46.82", "46.00", "47.28", NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, "52.11",
"51.19", "51.30", "51.99", "52.02", "53.90", "51.61", "54.77",
"30.18", "29.74", "31.71", "32.19", "31.42", "31.06", "30.73",
"32.05", "28.98", "26.80", "27.32", "27.15", "28.37", "27.80",
"28.85", "27.08", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA)), row.names = c(NA, -324L), class = c("rowwise_df",
"tbl_df", "tbl", "data.frame"), groups = structure(list(.rows = structure(list(
1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L,
27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L,
39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L, 50L,
51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L,
63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L,
75L, 76L, 77L, 78L, 79L, 80L, 81L, 82L, 83L, 84L, 85L, 86L,
87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 97L, 98L,
99L, 100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L,
109L, 110L, 111L, 112L, 113L, 114L, 115L, 116L, 117L, 118L,
119L, 120L, 121L, 122L, 123L, 124L, 125L, 126L, 127L, 128L,
129L, 130L, 131L, 132L, 133L, 134L, 135L, 136L, 137L, 138L,
139L, 140L, 141L, 142L, 143L, 144L, 145L, 146L, 147L, 148L,
149L, 150L, 151L, 152L, 153L, 154L, 155L, 156L, 157L, 158L,
159L, 160L, 161L, 162L, 163L, 164L, 165L, 166L, 167L, 168L,
169L, 170L, 171L, 172L, 173L, 174L, 175L, 176L, 177L, 178L,
179L, 180L, 181L, 182L, 183L, 184L, 185L, 186L, 187L, 188L,
189L, 190L, 191L, 192L, 193L, 194L, 195L, 196L, 197L, 198L,
199L, 200L, 201L, 202L, 203L, 204L, 205L, 206L, 207L, 208L,
209L, 210L, 211L, 212L, 213L, 214L, 215L, 216L, 217L, 218L,
219L, 220L, 221L, 222L, 223L, 224L, 225L, 226L, 227L, 228L,
229L, 230L, 231L, 232L, 233L, 234L, 235L, 236L, 237L, 238L,
239L, 240L, 241L, 242L, 243L, 244L, 245L, 246L, 247L, 248L,
249L, 250L, 251L, 252L, 253L, 254L, 255L, 256L, 257L, 258L,
259L, 260L, 261L, 262L, 263L, 264L, 265L, 266L, 267L, 268L,
269L, 270L, 271L, 272L, 273L, 274L, 275L, 276L, 277L, 278L,
279L, 280L, 281L, 282L, 283L, 284L, 285L, 286L, 287L, 288L,
289L, 290L, 291L, 292L, 293L, 294L, 295L, 296L, 297L, 298L,
299L, 300L, 301L, 302L, 303L, 304L, 305L, 306L, 307L, 308L,
309L, 310L, 311L, 312L, 313L, 314L, 315L, 316L, 317L, 318L,
319L, 320L, 321L, 322L, 323L, 324L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -324L), class = c("tbl_df",
"tbl", "data.frame")))
expect_equivalent(df_test, df_standard)
}
})
test_that("CAC Score ISL", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_16102020_Budapest_Match_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df <- file %>%
read_results() %>%
swim_parse_ISL()
expect_equal(sum(unique(df[df$Team == "CAC",])$Points, na.rm = TRUE),
567)
}
})
test_that("Lilly King Times with score - season 2", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_16102020_Budapest_Match_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df <- file %>%
read_results() %>%
swim_parse_ISL()
expect_equivalent(df[which(df$Name == "KING Lilly"),]$Finals,
c("2:17.11", "28.86", "1:03.16", "29.16", "29.25", "28.90"))
}
})
test_that("Lilly King Times without score - season 1", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_1_2019/ISL_16112019_CollegePark_Day_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df <- file %>%
read_results() %>%
swim_parse_ISL()
expect_equivalent(df[which(df$Name == "KING Lilly"),]$Finals,
c("29.00", "2:17.78"))
}
})
test_that("without score - season 1", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_1_2019/ISL_16112019_CollegePark_Day_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df_test <- file %>%
read_results() %>%
swim_parse_ISL(splits = TRUE, relay_swimmers = TRUE)
df_standard <-
structure(
list(
Place = c(
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
3,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
NA,
1,
2,
2,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
1,
3,
4,
5,
6,
7,
NA,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8,
1,
2,
3,
4,
5,
6,
7,
8
),
Lane = c(
7,
1,
4,
2,
3,
8,
5,
6,
7,
1,
4,
5,
6,
2,
8,
3,
8,
7,
6,
2,
4,
1,
3,
5,
1,
5,
4,
6,
8,
2,
7,
3,
8,
1,
7,
5,
2,
6,
4,
3,
1,
2,
5,
3,
7,
8,
4,
6,
7,
4,
1,
5,
8,
2,
6,
3,
7,
8,
4,
3,
1,
5,
6,
2,
1,
2,
7,
5,
4,
3,
8,
6,
8,
4,
1,
2,
6,
3,
7,
5,
1,
4,
7,
8,
2,
3,
6,
5,
1,
5,
7,
4,
6,
8,
3,
2,
5,
4,
8,
7,
6,
3,
2,
1,
1,
2,
3,
4,
6,
7,
8,
5,
2,
1,
7,
4,
8,
5,
6,
3,
2,
4,
5,
6,
8,
3,
7,
1,
7,
8,
3,
1,
4,
5,
2,
6,
6,
4,
1,
2,
7,
5,
8,
3,
7,
2,
1,
5,
4,
8,
6,
3
),
Name = c(
"DAHLIA Kelsi",
"STEWART Kendyl",
"LOVEMORE Tayla",
"OSMAN Farida",
"BLACK Haley",
"HINDS Natalie",
"RULE Remedy",
"QUAH Ting Wen",
"DRESSEL Caeleb",
"SHIELDS Tom",
"LEWIS Clyde",
"STRAVIUS Jeremy",
"SMITH Giles",
"CONGER Jack",
"SWITKOWSKI Jan",
"COETZEE Ryan",
"KING Lilly",
"HANNIS Molly",
"HAUGHEY Siobhan",
"BAKER Kathleen",
"LARSON Breeja",
"LAZOR Anne",
"ESCOBEDO Emily",
"PICKETT Leiston",
"LIMA Felipe",
"FINNERTY Ian",
"ANDREW Michael",
"CORDES Kevin",
"FINK Nic",
"LICON Will",
"WILSON Andrew",
"KOCH Marco",
"MARGALIS Melanie",
"EASTIN Ella",
"FLICKINGER Hali",
"GALAT Bethany",
"ANDISON Bailey",
"BARKSDALE Emma",
"OVERHOLT Emily",
"WOOD Abbie",
"SELISKAR Andrew",
"KALISZ Chase",
"LITHERLAND Jay",
"SMITH Brendon",
"SZARANEK Mark",
"IPSON Anton",
"PERIBONIO Tomas",
"GROTHE Zane",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"KAWECKI Radoslaw",
"SHEBAT John",
"THORMEYER Markus",
"REID Christopher",
"SHIELDS Tom",
"HOLLARD Tristan",
"LITHERLAND Jay",
"CONGER Jack",
"BAKER Kathleen",
"BILQUIST Amy",
"MASSE Kylie",
"BRATTON Lisa",
"SHERIDAN Mikkayla",
"DELOOF Alexandra",
"FLICKINGER Hali",
"KUBOVA Simona",
"DRESSEL Caeleb",
"ANDREW Michael",
"HELD Ryan",
"CHADWICK Michael",
"APPLE Zach",
"CHIERIGHINI Marcelo",
"BECKER Bowe",
"HOWARD Robert",
"GASTALDELLO Beryl",
"BLUME Pernille",
"WASICK Kasia",
"SMOLIGA Olivia",
"GEER Margo",
"DELOOF Catherine",
"KENNEDY Madison",
"APOSTALON Anika",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"HAUGHEY Siobhan",
"WILSON Madison",
"COMERFORD Mallory",
"MARGALIS Melanie",
"NEALE Leah",
"DELOOF Catherine",
"SMITH Leah",
"GORBENKO Anastasia",
"PIERONI Blake",
"SELISKAR Andrew",
"de LUCCA Joao",
"LEWIS Clyde",
"STJEPANOVIC Velimir",
"MAJCHRZAK Kacper",
"HAAS Townley",
"GROTHE Zane",
"GASTALDELLO Beryl",
"BAKER Kathleen",
"SMOLIGA Olivia",
"DELOOF Alexandra",
"MASSE Kylie",
"KUBOVA Simona",
"COUGHLIN Natalie",
"BLACK Haley",
"GREVERS Matthew",
"ANDREW Michael",
"STRAVIUS Jeremy",
"VAZAIOS Andreas",
"SHEBAT John",
"TARASEVICH Grigory",
"KAWECKI Radoslaw",
"RYAN Shane",
"KING Lilly",
"WOG Kelsey",
"ESCOBEDO Emily",
"LAZOR Anne",
"LARSON Breeja",
"GALAT Bethany",
"ANDISON Bailey",
"BARKSDALE Emma",
"FINNERTY Ian",
"KOCH Marco",
"LICON Will",
"PRENOT Josh",
"FINK Nic",
"MILLER Cody",
"WILSON Andrew",
"PERIBONIO Tomas",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA
),
Team = c(
"CAC",
"LAC",
"NYB",
"LAC",
"NYB",
"CAC",
"DCT",
"DCT",
"CAC",
"LAC",
"NYB",
"DCT",
"DCT",
"LAC",
"CAC",
"NYB",
"CAC",
"CAC",
"DCT",
"LAC",
"NYB",
"LAC",
"NYB",
"DCT",
"LAC",
"DCT",
"NYB",
"DCT",
"CAC",
"LAC",
"CAC",
"NYB",
"CAC",
"LAC",
"CAC",
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"LAC",
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"NYB",
"NYB",
"LAC",
"LAC",
"DCT",
"NYB",
"CAC",
"CAC",
"NYB",
"DCT",
"CAC",
"NYB",
"LAC",
"DCT",
"CAC",
"LAC",
"DCT",
"NYB",
"CAC",
"CAC",
"NYB",
"NYB",
"LAC",
"DCT",
"DCT",
"LAC",
"LAC",
"LAC",
"CAC",
"DCT",
"NYB",
"NYB",
"CAC",
"DCT",
"CAC",
"NYB",
"LAC",
"LAC",
"DCT",
"NYB",
"CAC",
"DCT",
"LAC",
"NYB",
"CAC",
"CAC",
"LAC",
"NYB",
"DCT",
"DCT",
"LAC",
"DCT",
"CAC",
"NYB",
"DCT",
"CAC",
"NYB",
"LAC",
"DCT",
"NYB",
"CAC",
"CAC",
"DCT",
"NYB",
"LAC",
"LAC",
"LAC",
"LAC",
"NYB",
"NYB",
"DCT",
"CAC",
"CAC",
"DCT",
"LAC",
"LAC",
"CAC",
"NYB",
"CAC",
"DCT",
"DCT",
"NYB",
"LAC",
"NYB",
"DCT",
"DCT",
"CAC",
"NYB",
"CAC",
"LAC",
"CAC",
"CAC",
"NYB",
"LAC",
"NYB",
"DCT",
"LAC",
"DCT",
"DCT",
"NYB",
"LAC",
"LAC",
"CAC",
"DCT",
"CAC",
"NYB",
"CAC",
"LAC",
"LAC",
"DCT",
"NYB",
"CAC",
"DCT",
"NYB"
),
Finals = c(
"55.78",
"56.41",
"56.93",
"57.18",
"57.42",
"57.68",
"57.95",
"58.01",
"49.16",
"49.70",
"51.13",
"51.32",
"51.41",
"51.64",
"52.12",
"52.33",
"29.00",
"29.18",
"29.88",
"30.13",
"30.15",
"30.19",
"30.40",
"30.41",
"25.92",
"25.99",
"26.09",
"26.41",
"26.50",
"26.58",
"26.84",
"27.05",
"4:24.46",
"4:27.53",
"4:29.64",
"4:31.49",
"4:32.01",
"4:32.03",
"4:32.09",
"4:32.16",
"4:02.88",
"4:03.49",
"4:04.17",
"4:07.09",
"4:07.81",
"4:08.46",
"4:11.09",
"4:11.92",
"3:29.38",
"3:30.01",
"3:30.12",
"3:31.87",
"3:33.23",
"3:34.75",
"3:37.16",
"3:38.36",
"1:51.68",
"1:52.15",
"1:52.38",
"1:54.29",
"1:54.50",
"1:54.67",
"1:55.95",
"1:56.72",
"2:01.57",
"2:01.61",
"2:01.93",
"2:02.33",
"2:04.59",
"2:04.74",
"2:05.19",
"2:05.35",
"20.81",
"21.05",
"21.39",
"21.39",
"21.68",
"21.73",
"21.86",
"21.89",
"23.81",
"24.19",
"24.23",
"24.29",
"24.30",
"24.42",
"24.54",
"24.65",
"3:23.63",
"3:25.22",
"3:26.61",
"3:30.70",
"3:30.74",
"3:31.25",
"3:37.09",
NA,
"1:51.99",
"1:54.34",
"1:54.34",
"1:54.40",
"1:55.75",
"1:55.85",
"1:56.08",
"1:57.78",
"1:43.48",
"1:43.66",
"1:43.76",
"1:43.92",
"1:44.12",
"1:44.20",
"1:45.87",
"1:46.87",
"26.18",
"26.21",
"26.32",
"26.52",
"26.78",
"26.85",
"28.29",
"28.63",
"23.38",
"23.38",
"23.49",
"23.51",
"23.77",
"24.58",
"25.04",
NA,
"2:17.78",
"2:18.26",
"2:19.26",
"2:19.30",
"2:22.05",
"2:24.24",
"2:25.55",
"2:26.88",
"2:02.76",
"2:03.79",
"2:04.09",
"2:05.40",
"2:06.69",
"2:07.06",
"2:11.09",
"2:12.49",
"3:08.52",
"3:09.65",
"3:09.81",
"3:10.27",
"3:10.34",
"3:12.49",
"3:14.69",
"3:17.81"
),
Event = c(
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Women's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Men's 100m Butterfly Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Women's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Men's 50m Breaststroke Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Women's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Men's 400m Individual Medley Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Women's 4 x 100m Freestyle Relay Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Men's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Women's 200m Backstroke Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Men's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Women's 50m Freestyle Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Men's 4 x 100m Medley Relay Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Women's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Men's 200m Freestyle Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Women's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Men's 50m Backstroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Women's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 200m Breaststroke Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final",
"Men's 4 x 100m Freestyle Relay Final"
),
DQ = c(
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
0,
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0,
0,
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0,
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0,
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0,
0
),
Relay_Swimmer_1 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"SMOLIGA Olivia",
"NEAL Lia",
"TETZLOFF Alyssa",
"APOSTALON Anika",
"WASICK Kasia",
"GORBENKO Anastasia",
"KENNEDY Madison",
"DELOOF Gabby",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"GREVERS Matthew",
"VAZAIOS Andreas",
"RESS Justin",
"TARASEVICH Grigory",
"HOLLARD Tristan",
"KAWECKI Radoslaw",
"REID Christopher",
"RYAN Shane",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"DRESSEL Caeleb",
"CARTER Dylan",
"CHADWICK Michael",
"HOWARD Robert",
"THORMEYER Markus",
"SHEBAT John",
"STJEPANOVIC Velimir",
"TANDY Bradley"
),
Relay_Swimmer_2 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"DAHLIA Kelsi",
"DELOOF Catherine",
"GEER Margo",
"HAUGHEY Siobhan",
"MARGALIS Melanie",
"OSMAN Farida",
"NEALE Leah",
"SHERIDAN Mikkayla",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"LIMA Felipe",
"FINNERTY Ian",
"FINK Nic",
"KOCH Marco",
"CORDES Kevin",
"WILSON Andrew",
"ANDREW Michael",
"LICON Will",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"MAJCHRZAK Kacper",
"RYAN Shane",
"HELD Ryan",
"APPLE Zach",
"CHIERIGHINI Marcelo",
"JACKSON Tate",
"SMITH Giles",
"REID Christopher"
),
Relay_Swimmer_3 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"HINDS Natalie",
"BLUME Pernille",
"MACK Linnea",
"RASMUS Claire",
"WEIR Amanda",
"BANIC Maddie",
"COUGHLIN Natalie",
"BLACK Haley",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"SHIELDS Tom",
"STRAVIUS Jeremy",
"DRESSEL Caeleb",
"COETZEE Ryan",
"SMITH Giles",
"SWITKOWSKI Jan",
"DARRAGH Mackenzie",
"PRENOT Josh",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"BECKER Bowe",
"GREVERS Matthew",
"PIERONI Blake",
"VAZAIOS Andreas",
"SPAJARI Pedro",
"HAAS Townley",
"GROTHE Zane",
"COETZEE Ryan"
),
Relay_Swimmer_4 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"COMERFORD Mallory",
"WILSON Madison",
"GASTALDELLO Beryl",
"QUAH Ting Wen",
"WOG Kelsey",
"STEWART Kendyl",
"GIBSON Sarah",
"LOVEMORE Tayla",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"CHADWICK Michael",
"APPLE Zach",
"JACKSON Tate",
"SPAJARI Pedro",
"HOWARD Robert",
"HAAS Townley",
"CHIERIGHINI Marcelo",
"CARTER Dylan",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"RESS Justin",
"SELISKAR Andrew",
"SHIELDS Tom",
"STRAVIUS Jeremy",
"LEWIS Clyde",
"SWITKOWSKI Jan",
"HOLLARD Tristan",
"de LUCCA Joao"
),
Split_50 = c(
"26.36",
"26.03",
"26.27",
"26.58",
"26.82",
"26.72",
"26.90",
"26.90",
"23.41",
"23.13",
"24.52",
"23.44",
"23.69",
"23.98",
"24.29",
"24.44",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"28.78",
"29.00",
"28.74",
"28.59",
"30.23",
"29.31",
"28.50",
"28.25",
"25.78",
"25.80",
"26.35",
"26.54",
"25.92",
"26.96",
"26.69",
"26.71",
"25.36",
"25.65",
"25.55",
"25.88",
"25.70",
"26.04",
"25.56",
"26.17",
"25.86",
"26.02",
"26.53",
"26.57",
"26.65",
"26.13",
"27.46",
"27.42",
"28.59",
"29.27",
"28.76",
"29.47",
"29.25",
"29.29",
"30.13",
"29.54",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
NA,
NA,
NA,
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"24.06",
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"24.45",
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NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
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NA,
"50.16",
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NA,
NA,
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NA,
NA,
NA,
"36.02",
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"48.68"
),
Split_150 = c(
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
NA,
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"22.35",
"22.43",
"22.69",
"22.87",
"22.71",
"23.29"
),
Split_200 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
NA,
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NA,
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NA,
"56.54",
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NA,
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NA,
NA,
NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"34.54",
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"47.29",
"47.67",
"47.04",
"48.17",
"48.23",
"48.09",
"49.18"
),
Split_250 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"35.76",
"37.50",
"39.63",
"38.01",
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"38.21",
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"24.63",
"24.85",
"26.07",
"25.78",
"25.30",
"26.19",
"26.69",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"16.03",
"23.38",
"23.03",
"24.85",
"23.64",
"24.32",
"24.88",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"22.35",
"22.26",
"22.49",
"22.57",
"22.61",
"22.69",
"23.14",
"23.82"
),
Split_300 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"36.77",
"38.41",
"39.59",
"38.92",
"38.70",
"39.39",
"40.26",
"38.76",
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"52.22",
"52.81",
"53.99",
"54.02",
"54.44",
"55.23",
"55.86",
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
NA,
NA,
NA,
NA,
NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
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NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"47.45",
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"47.92",
"46.92",
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"48.14",
"50.42"
),
Split_350 = c(
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
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NA,
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NA,
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NA,
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NA,
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NA,
NA,
NA,
NA,
NA,
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NA,
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"22.82",
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),
Split_400 = c(
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NA,
NA,
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NA,
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NA,
NA,
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NA,
NA,
NA,
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NA,
NA,
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NA,
NA,
"47.20",
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"47.93",
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NA,
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NA,
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NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
NA,
"47.31",
"47.36",
"46.97",
"47.94",
"47.04",
"48.32",
"49.17",
"49.53"
)
),
row.names = c(NA,-152L),
class = c("rowwise_df", "tbl_df",
"tbl", "data.frame"),
groups = structure(
list(.rows = structure(
list(
1L,
2L,
3L,
4L,
5L,
6L,
7L,
8L,
9L,
10L,
11L,
12L,
13L,
14L,
15L,
16L,
17L,
18L,
19L,
20L,
21L,
22L,
23L,
24L,
25L,
26L,
27L,
28L,
29L,
30L,
31L,
32L,
33L,
34L,
35L,
36L,
37L,
38L,
39L,
40L,
41L,
42L,
43L,
44L,
45L,
46L,
47L,
48L,
49L,
50L,
51L,
52L,
53L,
54L,
55L,
56L,
57L,
58L,
59L,
60L,
61L,
62L,
63L,
64L,
65L,
66L,
67L,
68L,
69L,
70L,
71L,
72L,
73L,
74L,
75L,
76L,
77L,
78L,
79L,
80L,
81L,
82L,
83L,
84L,
85L,
86L,
87L,
88L,
89L,
90L,
91L,
92L,
93L,
94L,
95L,
96L,
97L,
98L,
99L,
100L,
101L,
102L,
103L,
104L,
105L,
106L,
107L,
108L,
109L,
110L,
111L,
112L,
113L,
114L,
115L,
116L,
117L,
118L,
119L,
120L,
121L,
122L,
123L,
124L,
125L,
126L,
127L,
128L,
129L,
130L,
131L,
132L,
133L,
134L,
135L,
136L,
137L,
138L,
139L,
140L,
141L,
142L,
143L,
144L,
145L,
146L,
147L,
148L,
149L,
150L,
151L,
152L
),
ptype = integer(0),
class = c("vctrs_list_of",
"vctrs_vctr", "list")
)),
row.names = c(NA,-152L),
class = c("tbl_df",
"tbl", "data.frame")
)
)
expect_equivalent(df_test, df_standard)
}
})
test_that("ISL inside swim_parse, ID by teams", {
skip_on_cran() # due to risk of external resources failing
file <- "https://github.com/gpilgrim2670/Pilgrim_Data/raw/master/ISL/Season_2_2020/ISL_16102020_Budapest_Match_1.pdf"
if(is_link_broken(file) == TRUE){
warning("Link to external data is broken")
} else {
df_test <- file %>%
read_results() %>%
swim_parse() %>%
head(3)
df_standard <-
structure(list(Place = c(1, 2, 3), Lane = c(4, 3, 5), Name = c("SJOSTROM Sarah",
"SHKURDAI Anastasiya", "DAHLIA Kelsi"), Team = c("ENS", "ENS",
"CAC"), Finals = c("56.00", "56.07", "56.70"), Event = c("Women's 100m Butterfly",
"Women's 100m Butterfly", "Women's 100m Butterfly"), Points = c(9,
7, 6), DQ = c(0, 0, 0)), class = c("rowwise_df", "tbl_df", "tbl",
"data.frame"), row.names = c(NA, -3L), groups = structure(list(
.rows = structure(list(1L, 2L, 3L), ptype = integer(0), class = c("vctrs_list_of",
"vctrs_vctr", "list"))), row.names = c(NA, -3L), class = c("tbl_df",
"tbl", "data.frame")))
expect_equivalent(df_test, df_standard)
}
})
# testthat::test_file("tests/testthat/test-ISL.R")
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