readme.md
In nickpaul7/npmlb:
npmlb: Collecting Baseball Data
Introduction
This package is designed to collect baseball data from the web. Currently the package supports pulling data from the following sites:
https://www.baseball-reference.com/
- Player Game Logs
- HOF Players
- Career Statistics
Install
To install the latest version use the following code:
devtools::install_github("nickpaul7/npmlb")
Required Packages
library(tidyverse)
Player Game Logs
To get all player game logs for entire season, use the code below.
path <- "/data/"
npmlb::save_mlb_year(2019, save_path = path)
Get Team Roster
The scrape_team_full_roster() function will collect the pitching and batting roster for a given team.
team <- "NYY"
year <- "2019"
df_roster <- npmlb::scrape_team_full_roster(team, year)
To extract the rosters, you can use the following code.
df_roster %>%
filter(data_type == "pitching") %>%
unnest()
## # A tibble: 32 x 42
## team year data_type Rk Pos Name Age W L `W-L%` ERA
## <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 NYY 2019 pitching 1 SP Masah… 30 11 9 .550 4.45
## 2 NYY 2019 pitching 2 SP J.A. … 36 12 8 .600 4.91
## 3 NYY 2019 pitching 3 SP James… 30 15 6 .714 3.82
## 4 NYY 2019 pitching 4 SP Domin… 26 18 4 .818 4.03
## 5 NYY 2019 pitching 5 SP CC Sa… 38 5 8 .385 4.95
## 6 NYY 2019 pitching 6 CL Arold… 31 3 2 .600 2.21
## 7 NYY 2019 pitching 7 RP Chad … 28 4 4 .500 4.17
## 8 NYY 2019 pitching 8 RP Adam … 33 6 5 .545 1.90
## 9 NYY 2019 pitching 9 RP Zack … 31 3 1 .750 1.91
## 10 NYY 2019 pitching 10 RP Tommy… 29 3 2 .600 3.67
## # ... with 22 more rows, and 31 more variables: G <chr>, GS <chr>,
## # GF <chr>, CG <chr>, SHO <chr>, SV <chr>, IP <chr>, H <chr>, R <chr>,
## # ER <chr>, HR <chr>, BB <chr>, IBB <chr>, SO <chr>, HBP <chr>,
## # BK <chr>, WP <chr>, BF <chr>, `ERA+` <chr>, FIP <chr>, WHIP <chr>,
## # H9 <chr>, HR9 <chr>, BB9 <chr>, SO9 <chr>, `SO/W` <chr>, link <chr>,
## # text <chr>, type <chr>, player_id <chr>, game_log_link <chr>
The team_pages data object contains the abbreviations for each team.
npmlb::team_pages
## # A tibble: 30 x 2
## team_page abbreviation
## <chr> <chr>
## 1 https://www.baseball-reference.com/teams/ANA ANA
## 2 https://www.baseball-reference.com/teams/ARI ARI
## 3 https://www.baseball-reference.com/teams/ATL ATL
## 4 https://www.baseball-reference.com/teams/BAL BAL
## 5 https://www.baseball-reference.com/teams/BOS BOS
## 6 https://www.baseball-reference.com/teams/LAD LAD
## 7 https://www.baseball-reference.com/teams/CHC CHC
## 8 https://www.baseball-reference.com/teams/CHW CHW
## 9 https://www.baseball-reference.com/teams/CIN CIN
## 10 https://www.baseball-reference.com/teams/CLE CLE
## # ... with 20 more rows
Scrape a Player Page
link <- "https://www.baseball-reference.com/players/gl.fcgi?id=lemahdj01&t=b&year=2019"
type = "b"
df_player_log <- npmlb::scrape_player_game_logs(link, type)
dplyr::glimpse(df_player_log)
## Observations: 145
## Variables: 38
## $ Rk <chr> "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "...
## $ Gcar <chr> "956", "957", "958", "959", "960", "961", "962", "96...
## $ Gtm <chr> "2 (1)", "3", "4", "5", "6", "7", "8", "9", "10", "1...
## $ Date <chr> "Mar 30", "Mar 31", "Apr 1", "Apr 2", "Apr 3", "Apr ...
## $ Tm <chr> "NYY", "NYY", "NYY", "NYY", "NYY", "NYY", "NYY", "NY...
## $ at <chr> "", "", "", "", "", "@", "@", "@", "@", "@", "@", ""...
## $ Opp <chr> "BAL", "BAL", "DET", "DET", "DET", "BAL", "BAL", "BA...
## $ Rslt <chr> "L,3-5", "L,5-7", "W,3-1", "L,1-3", "L,1-2", "W,8-4"...
## $ Inngs <chr> "CG", "CG", "CG", "CG", "CG", "CG", "CG", "GS-7", "C...
## $ PA <chr> "4", "5", "3", "4", "4", "4", "4", "4", "4", "4", "4...
## $ AB <chr> "4", "2", "2", "4", "4", "4", "4", "4", "4", "4", "3...
## $ R <chr> "1", "1", "0", "1", "1", "1", "1", "1", "1", "0", "0...
## $ H <chr> "2", "2", "0", "2", "1", "1", "3", "1", "1", "0", "3...
## $ `2B` <chr> "1", "0", "0", "0", "1", "0", "0", "1", "1", "0", "1...
## $ `3B` <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ HR <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ RBI <chr> "1", "1", "0", "0", "0", "0", "0", "1", "0", "0", "2...
## $ BB <chr> "0", "2", "1", "0", "0", "0", "0", "0", "0", "0", "0...
## $ IBB <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ SO <chr> "0", "0", "2", "0", "2", "1", "0", "0", "0", "1", "0...
## $ HBP <chr> "0", "1", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ SH <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ SF <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "1...
## $ ROE <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ GDP <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ SB <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ CS <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ BA <chr> ".500", ".667", ".500", ".500", ".438", ".400", ".45...
## $ OBP <chr> ".500", ".778", ".667", ".625", ".550", ".500", ".53...
## $ SLG <chr> ".750", ".833", ".625", ".583", ".563", ".500", ".54...
## $ OPS <chr> "1.250", "1.611", "1.292", "1.208", "1.113", "1.000"...
## $ BOP <chr> "9", "9", "7", "5", "1", "6", "7", "6", "7", "6", "6...
## $ aLI <chr> "1.68", "1.47", ".61", "1.06", ".91", ".90", "1.36",...
## $ WPA <chr> "0.078", "0.213", "-0.011", "-0.027", "-0.030", "-0....
## $ RE24 <chr> "0.93", "2.44", "-0.16", "0.11", "-0.18", "-0.40", "...
## $ `DFS(DK)` <chr> "12.00", "16.00", "2.00", "8.00", "7.00", "5.00", "1...
## $ `DFS(FD)` <chr> "15.70", "21.70", "3.00", "9.20", "9.20", "6.20", "1...
## $ Pos <chr> "3B", "2B", "3B", "3B", "3B", "3B", "3B 2B", "2B", "...
nickpaul7/npmlb documentation built on Nov. 4, 2019, 10:04 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.
npmlb: Collecting Baseball Data
Introduction
This package is designed to collect baseball data from the web. Currently the package supports pulling data from the following sites:
https://www.baseball-reference.com/
- Player Game Logs
- HOF Players
- Career Statistics
Install
To install the latest version use the following code:
devtools::install_github("nickpaul7/npmlb")
Required Packages
library(tidyverse)
Player Game Logs
To get all player game logs for entire season, use the code below.
path <- "/data/"
npmlb::save_mlb_year(2019, save_path = path)
Get Team Roster
The scrape_team_full_roster() function will collect the pitching and batting roster for a given team.
team <- "NYY"
year <- "2019"
df_roster <- npmlb::scrape_team_full_roster(team, year)
To extract the rosters, you can use the following code.
df_roster %>%
filter(data_type == "pitching") %>%
unnest()
## # A tibble: 32 x 42
## team year data_type Rk Pos Name Age W L `W-L%` ERA
## <chr> <chr> <chr> <dbl> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
## 1 NYY 2019 pitching 1 SP Masah… 30 11 9 .550 4.45
## 2 NYY 2019 pitching 2 SP J.A. … 36 12 8 .600 4.91
## 3 NYY 2019 pitching 3 SP James… 30 15 6 .714 3.82
## 4 NYY 2019 pitching 4 SP Domin… 26 18 4 .818 4.03
## 5 NYY 2019 pitching 5 SP CC Sa… 38 5 8 .385 4.95
## 6 NYY 2019 pitching 6 CL Arold… 31 3 2 .600 2.21
## 7 NYY 2019 pitching 7 RP Chad … 28 4 4 .500 4.17
## 8 NYY 2019 pitching 8 RP Adam … 33 6 5 .545 1.90
## 9 NYY 2019 pitching 9 RP Zack … 31 3 1 .750 1.91
## 10 NYY 2019 pitching 10 RP Tommy… 29 3 2 .600 3.67
## # ... with 22 more rows, and 31 more variables: G <chr>, GS <chr>,
## # GF <chr>, CG <chr>, SHO <chr>, SV <chr>, IP <chr>, H <chr>, R <chr>,
## # ER <chr>, HR <chr>, BB <chr>, IBB <chr>, SO <chr>, HBP <chr>,
## # BK <chr>, WP <chr>, BF <chr>, `ERA+` <chr>, FIP <chr>, WHIP <chr>,
## # H9 <chr>, HR9 <chr>, BB9 <chr>, SO9 <chr>, `SO/W` <chr>, link <chr>,
## # text <chr>, type <chr>, player_id <chr>, game_log_link <chr>
The team_pages data object contains the abbreviations for each team.
npmlb::team_pages
## # A tibble: 30 x 2
## team_page abbreviation
## <chr> <chr>
## 1 https://www.baseball-reference.com/teams/ANA ANA
## 2 https://www.baseball-reference.com/teams/ARI ARI
## 3 https://www.baseball-reference.com/teams/ATL ATL
## 4 https://www.baseball-reference.com/teams/BAL BAL
## 5 https://www.baseball-reference.com/teams/BOS BOS
## 6 https://www.baseball-reference.com/teams/LAD LAD
## 7 https://www.baseball-reference.com/teams/CHC CHC
## 8 https://www.baseball-reference.com/teams/CHW CHW
## 9 https://www.baseball-reference.com/teams/CIN CIN
## 10 https://www.baseball-reference.com/teams/CLE CLE
## # ... with 20 more rows
Scrape a Player Page
link <- "https://www.baseball-reference.com/players/gl.fcgi?id=lemahdj01&t=b&year=2019"
type = "b"
df_player_log <- npmlb::scrape_player_game_logs(link, type)
dplyr::glimpse(df_player_log)
## Observations: 145
## Variables: 38
## $ Rk <chr> "1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "...
## $ Gcar <chr> "956", "957", "958", "959", "960", "961", "962", "96...
## $ Gtm <chr> "2 (1)", "3", "4", "5", "6", "7", "8", "9", "10", "1...
## $ Date <chr> "Mar 30", "Mar 31", "Apr 1", "Apr 2", "Apr 3", "Apr ...
## $ Tm <chr> "NYY", "NYY", "NYY", "NYY", "NYY", "NYY", "NYY", "NY...
## $ at <chr> "", "", "", "", "", "@", "@", "@", "@", "@", "@", ""...
## $ Opp <chr> "BAL", "BAL", "DET", "DET", "DET", "BAL", "BAL", "BA...
## $ Rslt <chr> "L,3-5", "L,5-7", "W,3-1", "L,1-3", "L,1-2", "W,8-4"...
## $ Inngs <chr> "CG", "CG", "CG", "CG", "CG", "CG", "CG", "GS-7", "C...
## $ PA <chr> "4", "5", "3", "4", "4", "4", "4", "4", "4", "4", "4...
## $ AB <chr> "4", "2", "2", "4", "4", "4", "4", "4", "4", "4", "3...
## $ R <chr> "1", "1", "0", "1", "1", "1", "1", "1", "1", "0", "0...
## $ H <chr> "2", "2", "0", "2", "1", "1", "3", "1", "1", "0", "3...
## $ `2B` <chr> "1", "0", "0", "0", "1", "0", "0", "1", "1", "0", "1...
## $ `3B` <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ HR <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ RBI <chr> "1", "1", "0", "0", "0", "0", "0", "1", "0", "0", "2...
## $ BB <chr> "0", "2", "1", "0", "0", "0", "0", "0", "0", "0", "0...
## $ IBB <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ SO <chr> "0", "0", "2", "0", "2", "1", "0", "0", "0", "1", "0...
## $ HBP <chr> "0", "1", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ SH <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ SF <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "1...
## $ ROE <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ GDP <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ SB <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ CS <chr> "0", "0", "0", "0", "0", "0", "0", "0", "0", "0", "0...
## $ BA <chr> ".500", ".667", ".500", ".500", ".438", ".400", ".45...
## $ OBP <chr> ".500", ".778", ".667", ".625", ".550", ".500", ".53...
## $ SLG <chr> ".750", ".833", ".625", ".583", ".563", ".500", ".54...
## $ OPS <chr> "1.250", "1.611", "1.292", "1.208", "1.113", "1.000"...
## $ BOP <chr> "9", "9", "7", "5", "1", "6", "7", "6", "7", "6", "6...
## $ aLI <chr> "1.68", "1.47", ".61", "1.06", ".91", ".90", "1.36",...
## $ WPA <chr> "0.078", "0.213", "-0.011", "-0.027", "-0.030", "-0....
## $ RE24 <chr> "0.93", "2.44", "-0.16", "0.11", "-0.18", "-0.40", "...
## $ `DFS(DK)` <chr> "12.00", "16.00", "2.00", "8.00", "7.00", "5.00", "1...
## $ `DFS(FD)` <chr> "15.70", "21.70", "3.00", "9.20", "9.20", "6.20", "1...
## $ Pos <chr> "3B", "2B", "3B", "3B", "3B", "3B", "3B 2B", "2B", "...
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