README.md
In epijim/FootballData: Easy access to Football API data and quick toy summaries
FootballData
To rebuild run make build.
library(glue)
library(kableExtra)
library(tidyverse)
library(FootballData)
select_country <- "England"
select_league <- "Championship"
select_team_interest <- "Nottingham Forest FC"
Competitions
Get all competitions.
competitions <- football_get_competition()
glimpse(competitions)
## Rows: 152
## Columns: 6
## $ league <chr> "WC Qualification", "Primera B Nacional", "Superliga A…
## $ competition_id <int> 2006, 2023, 2024, 2149, 2025, 2147, 2008, 2026, 2020, …
## $ plan <chr> "TIER_FOUR", "TIER_FOUR", "TIER_TWO", "TIER_FOUR", "TI…
## $ country <chr> "Africa", "Argentina", "Argentina", "Argentina", "Arge…
## $ url_flag <chr> NA, NA, NA, NA, NA, NA, NA, NA, "https://upload.wikime…
## $ flag <glue> NA, NA, NA, NA, NA, NA, NA, NA, "<img src='https://up…
Filter to the ones on the free plan.
competitions_curated <- competitions %>%
filter(
plan == "TIER_ONE"
)
Show them.
competitions_curated %>%
select(country,league,flag) %>%
knitr::kable(escape = F)
country
league
flag
Brazil
Série A
NA
England
Championship
England
Premier League
Europe
UEFA Champions League
NA
Europe
European Championship
NA
France
Ligue 1
Germany
Bundesliga
Italy
Serie A
Netherlands
Eredivisie
Portugal
Primeira Liga
Spain
Primera Division
World
FIFA World Cup
NA
League info
Look at England - Championship.
league <- competitions_curated %>%
filter(country == select_country & league == select_league) %>%
pull(competition_id) %>%
as.character() %>%
football_get_teams()
league %>%
select(team,crest) %>%
knitr::kable(escape = F)
team
crest
Blackburn Rovers FC
Norwich City FC
Queens Park Rangers FC
Stoke City FC
Swansea City AFC
Birmingham City FC
Derby County FC
Middlesbrough FC
Sheffield Wednesday FC
Watford FC
Nottingham Forest FC
Reading FC
Barnsley FC
Millwall FC
Rotherham United FC
Bristol City FC
Luton Town FC
Huddersfield Town AFC
Brentford FC
Cardiff City FC
AFC Bournemouth
Coventry City FC
Preston North End FC
Wycombe Wanderers FC
Standings
What’s the current league standings.
standings <- competitions_curated %>%
filter(country == select_country & league == select_league) %>%
pull(competition_id) %>%
as.character() %>%
football_get_standing()
glimpse(standings)
## Rows: 24
## Columns: 14
## $ position <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,…
## $ playedGames <int> 28, 27, 27, 27, 28, 28, 28, 27, 28, 28, 28, 27, 28, 27…
## $ form <chr> "L,D,D,W,W", "W,W,W,D,W", "W,W,D,W,W", "D,W,D,W,W", "D…
## $ won <int> 16, 15, 15, 14, 13, 12, 11, 11, 9, 12, 11, 10, 7, 9, 9…
## $ draw <int> 7, 9, 8, 6, 9, 9, 7, 6, 12, 3, 3, 6, 14, 7, 7, 9, 6, 8…
## $ lost <int> 5, 3, 4, 7, 6, 7, 10, 10, 7, 13, 14, 11, 7, 11, 11, 10…
## $ points <int> 55, 54, 53, 48, 48, 45, 40, 39, 39, 39, 36, 36, 35, 34…
## $ goalsFor <int> 35, 52, 35, 40, 31, 43, 31, 41, 32, 29, 32, 29, 26, 35…
## $ goalsAgainst <int> 23, 27, 15, 29, 20, 28, 28, 29, 29, 33, 36, 34, 26, 31…
## $ goalDifference <int> 12, 25, 20, 11, 11, 15, 3, 12, 3, -4, -4, -5, 0, 4, -7…
## $ team_id <int> 68, 402, 72, 355, 346, 1044, 343, 59, 70, 387, 1081, 3…
## $ team <chr> "Norwich City FC", "Brentford FC", "Swansea City AFC",…
## $ url_team <chr> "https://upload.wikimedia.org/wikipedia/en/8/8c/Norwic…
## $ crest <glue> "<img src='https://upload.wikimedia.org/wikipedia/en/…
standings %>%
select(position,points,team,form,crest) %>%
knitr::kable(escape = F)
position
points
team
form
crest
1
55
Norwich City FC
L,D,D,W,W
2
54
Brentford FC
W,W,W,D,W
3
53
Swansea City AFC
W,W,D,W,W
4
48
Reading FC
D,W,D,W,W
5
48
Watford FC
D,L,D,W,W
6
45
AFC Bournemouth
W,L,L,L,L
7
40
Middlesbrough FC
L,D,L,L,W
8
39
Blackburn Rovers FC
L,W,W,D,W
9
39
Stoke City FC
D,D,L,D,D
10
39
Bristol City FC
L,L,L,W,L
11
36
Preston North End FC
L,L,D,W,L
12
36
Barnsley FC
D,D,L,L,L
13
35
Millwall FC
W,D,D,D,W
14
34
Cardiff City FC
W,D,D,L,L
15
34
Luton Town FC
D,L,L,W,L
16
33
Queens Park Rangers FC
W,W,L,W,W
17
33
Huddersfield Town AFC
D,D,L,L,L
18
32
Nottingham Forest FC
W,W,D,L,W
19
31
Coventry City FC
D,L,D,W,L
20
29
Rotherham United FC
W,W,L,W,D
21
28
Derby County FC
L,W,W,W,L
22
28
Birmingham City FC
L,D,D,L,W
23
19
Sheffield Wednesday FC
L,W,W,L,W
24
16
Wycombe Wanderers FC
L,D,L,L,W
Scheduled games
upcoming_foe_data <- standings %>%
filter(
team == select_team_interest
) %>%
pull(team_id) %>%
as.character() %>%
football_get_upcoming() %>%
arrange(utcDate)
glimpse(upcoming_foe_data)
## Rows: 18
## Columns: 14
## $ id <int> 306708, 306723, 306732, 306745, 306756, 306765, 306785, 3…
## $ competition <df[,3]> <data.frame[18 x 3]>
## $ season <df[,5]> <data.frame[18 x 5]>
## $ utcDate <chr> "2021-02-13T12:30:00Z", "2021-02-17T19:00:00Z", "2021-02-…
## $ status <chr> "SCHEDULED", "SCHEDULED", "SCHEDULED", "SCHEDULED", "SCHE…
## $ matchday <int> 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 4…
## $ stage <chr> "REGULAR_SEASON", "REGULAR_SEASON", "REGULAR_SEASON", "RE…
## $ group <chr> "Regular Season", "Regular Season", "Regular Season", "Re…
## $ lastUpdated <chr> "2021-01-22T19:33:55Z", "2021-01-26T23:33:52Z", "2020-08-…
## $ odds <df[,1]> <data.frame[18 x 1]>
## $ score <df[,6]> <data.frame[18 x 6]>
## $ homeTeam <df[,2]> <data.frame[18 x 2]>
## $ awayTeam <df[,2]> <data.frame[18 x 2]>
## $ referees <list> [[], [], [], [], [], [], [], [], [], [], [], [], [], [],…
Metrics - League
metrics <- football_calculate_competition_metrics(standings)
# table
metrics %>%
mutate(Team = paste(crest,team)) %>%
select(Team, Mood = metric_mood) %>%
mutate(
Mood = as.character(Mood),
Mood = case_when(
str_detect(Mood,"Jubilant") ~ cell_spec(
Mood, color = "black", background = "#98FB98"
),
str_detect(Mood,"Optimistic") ~ cell_spec(
Mood, color = "black", background = "#e5f5f9"
),
str_detect(Mood,"Ambivalent") ~ cell_spec(
Mood, color = "black", background = "#f7fcb9"
),
str_detect(Mood,"Doldrums") ~ cell_spec(
Mood, color = "black", background = "#ffc4c4"
),
TRUE ~ Mood
)
) %>%
knitr::kable(escape = F)
Team
Mood
Norwich City FC
Jubilant:
Norwich City FC are on a roll
Brentford FC
Jubilant:
Brentford FC are on a roll
Swansea City AFC
Jubilant:
Swansea City AFC are on a roll
Reading FC
Optimistic:
Reading FC are doing well
Watford FC
Optimistic:
Watford FC are doing well
AFC Bournemouth
Optimistic:
AFC Bournemouth are doing well
Middlesbrough FC
Optimistic:
Middlesbrough FC are doing well
Blackburn Rovers FC
Optimistic:
Blackburn Rovers FC are doing well
Stoke City FC
Ambivalent:
Stoke City FC aren’t doing well, but hey - at least they aren’t Wycombe
Wanderers FC
Bristol City FC
Ambivalent:
Bristol City FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Preston North End FC
Ambivalent:
Preston North End FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Barnsley FC
Ambivalent:
Barnsley FC aren’t doing well, but hey - at least they aren’t Wycombe
Wanderers FC
Millwall FC
Ambivalent:
Millwall FC aren’t doing well, but hey - at least they aren’t Wycombe
Wanderers FC
Cardiff City FC
Ambivalent:
Cardiff City FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Luton Town FC
Ambivalent:
Luton Town FC aren’t doing well, but hey - at least they aren’t Wycombe
Wanderers FC
Queens Park Rangers FC
Ambivalent:
Queens Park Rangers FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Huddersfield Town AFC
Ambivalent:
Huddersfield Town AFC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Nottingham Forest FC
Ambivalent:
Nottingham Forest FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Coventry City FC
Ambivalent:
Coventry City FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Rotherham United FC
Ambivalent:
Rotherham United FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Derby County FC
Ambivalent:
Derby County FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Birmingham City FC
Ambivalent:
Birmingham City FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Sheffield Wednesday FC
Ambivalent:
Sheffield Wednesday FC aren’t doing well, but hey - at least they aren’t
Wycombe Wanderers FC
Wycombe Wanderers FC
Doldrums:
Wycombe Wanderers FC are doing poorly. Avoid supporters at all
costs.
Metrics - Team
metrics_team <- metrics %>%
filter(team == select_team_interest)
metrics_team_summary <- metrics_team %>% select(team,crest,metric_mood)
metrics_team %>%
select(-c(metric_mood_numeric,metric_mood)) %>%
pivot_longer(starts_with("metric"),
names_to = "Variable",
values_to = "Modifier"
) %>%
mutate(
Effect = case_when(
str_detect(Modifier, "\\+") ~ "Positive",
str_detect(Modifier, "\\-") ~ "Negative",
TRUE ~ "Neutral"
)
) %>%
select(
Effect,Modifier
) %>% arrange(Effect) %>%
mutate(
Effect = case_when(
Effect == "Negative" ~ cell_spec(
Effect, color = "white", bold = TRUE, background = "#F66E5CFF"
),
Effect == "Positive" ~ cell_spec(
Effect, color = "white", bold = TRUE, background = "#228B22"
),
TRUE ~ Effect
)
) %>%
knitr::kable(escape = F)
Effect
Modifier
Negative
- so so season
Negative
- conceded more than scored
Positive
\++ recent wins
epijim/FootballData documentation built on March 3, 2021, 11:52 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
FootballData
To rebuild run make build.
library(glue)
library(kableExtra)
library(tidyverse)
library(FootballData)
select_country <- "England"
select_league <- "Championship"
select_team_interest <- "Nottingham Forest FC"
Competitions
Get all competitions.
competitions <- football_get_competition()
glimpse(competitions)
## Rows: 152
## Columns: 6
## $ league <chr> "WC Qualification", "Primera B Nacional", "Superliga A…
## $ competition_id <int> 2006, 2023, 2024, 2149, 2025, 2147, 2008, 2026, 2020, …
## $ plan <chr> "TIER_FOUR", "TIER_FOUR", "TIER_TWO", "TIER_FOUR", "TI…
## $ country <chr> "Africa", "Argentina", "Argentina", "Argentina", "Arge…
## $ url_flag <chr> NA, NA, NA, NA, NA, NA, NA, NA, "https://upload.wikime…
## $ flag <glue> NA, NA, NA, NA, NA, NA, NA, NA, "<img src='https://up…
Filter to the ones on the free plan.
competitions_curated <- competitions %>%
filter(
plan == "TIER_ONE"
)
Show them.
competitions_curated %>%
select(country,league,flag) %>%
knitr::kable(escape = F)
League info
Look at England - Championship.
league <- competitions_curated %>%
filter(country == select_country & league == select_league) %>%
pull(competition_id) %>%
as.character() %>%
football_get_teams()
league %>%
select(team,crest) %>%
knitr::kable(escape = F)
Standings
What’s the current league standings.
standings <- competitions_curated %>%
filter(country == select_country & league == select_league) %>%
pull(competition_id) %>%
as.character() %>%
football_get_standing()
glimpse(standings)
## Rows: 24
## Columns: 14
## $ position <int> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,…
## $ playedGames <int> 28, 27, 27, 27, 28, 28, 28, 27, 28, 28, 28, 27, 28, 27…
## $ form <chr> "L,D,D,W,W", "W,W,W,D,W", "W,W,D,W,W", "D,W,D,W,W", "D…
## $ won <int> 16, 15, 15, 14, 13, 12, 11, 11, 9, 12, 11, 10, 7, 9, 9…
## $ draw <int> 7, 9, 8, 6, 9, 9, 7, 6, 12, 3, 3, 6, 14, 7, 7, 9, 6, 8…
## $ lost <int> 5, 3, 4, 7, 6, 7, 10, 10, 7, 13, 14, 11, 7, 11, 11, 10…
## $ points <int> 55, 54, 53, 48, 48, 45, 40, 39, 39, 39, 36, 36, 35, 34…
## $ goalsFor <int> 35, 52, 35, 40, 31, 43, 31, 41, 32, 29, 32, 29, 26, 35…
## $ goalsAgainst <int> 23, 27, 15, 29, 20, 28, 28, 29, 29, 33, 36, 34, 26, 31…
## $ goalDifference <int> 12, 25, 20, 11, 11, 15, 3, 12, 3, -4, -4, -5, 0, 4, -7…
## $ team_id <int> 68, 402, 72, 355, 346, 1044, 343, 59, 70, 387, 1081, 3…
## $ team <chr> "Norwich City FC", "Brentford FC", "Swansea City AFC",…
## $ url_team <chr> "https://upload.wikimedia.org/wikipedia/en/8/8c/Norwic…
## $ crest <glue> "<img src='https://upload.wikimedia.org/wikipedia/en/…
standings %>%
select(position,points,team,form,crest) %>%
knitr::kable(escape = F)
Scheduled games
upcoming_foe_data <- standings %>%
filter(
team == select_team_interest
) %>%
pull(team_id) %>%
as.character() %>%
football_get_upcoming() %>%
arrange(utcDate)
glimpse(upcoming_foe_data)
## Rows: 18
## Columns: 14
## $ id <int> 306708, 306723, 306732, 306745, 306756, 306765, 306785, 3…
## $ competition <df[,3]> <data.frame[18 x 3]>
## $ season <df[,5]> <data.frame[18 x 5]>
## $ utcDate <chr> "2021-02-13T12:30:00Z", "2021-02-17T19:00:00Z", "2021-02-…
## $ status <chr> "SCHEDULED", "SCHEDULED", "SCHEDULED", "SCHEDULED", "SCHE…
## $ matchday <int> 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 4…
## $ stage <chr> "REGULAR_SEASON", "REGULAR_SEASON", "REGULAR_SEASON", "RE…
## $ group <chr> "Regular Season", "Regular Season", "Regular Season", "Re…
## $ lastUpdated <chr> "2021-01-22T19:33:55Z", "2021-01-26T23:33:52Z", "2020-08-…
## $ odds <df[,1]> <data.frame[18 x 1]>
## $ score <df[,6]> <data.frame[18 x 6]>
## $ homeTeam <df[,2]> <data.frame[18 x 2]>
## $ awayTeam <df[,2]> <data.frame[18 x 2]>
## $ referees <list> [[], [], [], [], [], [], [], [], [], [], [], [], [], [],…
Metrics - League
metrics <- football_calculate_competition_metrics(standings)
# table
metrics %>%
mutate(Team = paste(crest,team)) %>%
select(Team, Mood = metric_mood) %>%
mutate(
Mood = as.character(Mood),
Mood = case_when(
str_detect(Mood,"Jubilant") ~ cell_spec(
Mood, color = "black", background = "#98FB98"
),
str_detect(Mood,"Optimistic") ~ cell_spec(
Mood, color = "black", background = "#e5f5f9"
),
str_detect(Mood,"Ambivalent") ~ cell_spec(
Mood, color = "black", background = "#f7fcb9"
),
str_detect(Mood,"Doldrums") ~ cell_spec(
Mood, color = "black", background = "#ffc4c4"
),
TRUE ~ Mood
)
) %>%
knitr::kable(escape = F)
Metrics - Team
metrics_team <- metrics %>%
filter(team == select_team_interest)
metrics_team_summary <- metrics_team %>% select(team,crest,metric_mood)
metrics_team %>%
select(-c(metric_mood_numeric,metric_mood)) %>%
pivot_longer(starts_with("metric"),
names_to = "Variable",
values_to = "Modifier"
) %>%
mutate(
Effect = case_when(
str_detect(Modifier, "\\+") ~ "Positive",
str_detect(Modifier, "\\-") ~ "Negative",
TRUE ~ "Neutral"
)
) %>%
select(
Effect,Modifier
) %>% arrange(Effect) %>%
mutate(
Effect = case_when(
Effect == "Negative" ~ cell_spec(
Effect, color = "white", bold = TRUE, background = "#F66E5CFF"
),
Effect == "Positive" ~ cell_spec(
Effect, color = "white", bold = TRUE, background = "#228B22"
),
TRUE ~ Effect
)
) %>%
knitr::kable(escape = F)
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