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understatr <img src="man/figures/logo.png" alt="" width="120" align="right" />
Overview
An R package to help with retrieving tidy understat data.
Install
understatr is not likely to be submitted to CRAN. Get the latest
development version from GitHub:
remotes::install_github('ewenme/understatr')
Use
library(understatr)
Check currently available leagues/seasons:
get_leagues_meta()
#> # A tibble: 48 × 4
#> league_name year season url
#> <chr> <dbl> <chr> <chr>
#> 1 EPL 2021 2021/2022 https://understat.com/league/EPL/2021
#> 2 EPL 2020 2020/2021 https://understat.com/league/EPL/2020
#> 3 EPL 2019 2019/2020 https://understat.com/league/EPL/2019
#> 4 EPL 2018 2018/2019 https://understat.com/league/EPL/2018
#> 5 EPL 2017 2017/2018 https://understat.com/league/EPL/2017
#> 6 EPL 2016 2016/2017 https://understat.com/league/EPL/2016
#> 7 EPL 2015 2015/2016 https://understat.com/league/EPL/2015
#> 8 EPL 2014 2014/2015 https://understat.com/league/EPL/2014
#> 9 La liga 2021 2021/2022 https://understat.com/league/La%20liga/2021
#> 10 La liga 2020 2020/2021 https://understat.com/league/La%20liga/2020
#> # … with 38 more rows
Get stats for a team’s playing squad in a league season:
get_team_players_stats(team_name = "Manchester City", year = 2018)
#>
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#> player_id = col_double(),
#> player_name = col_character(),
#> games = col_double(),
#> time = col_double(),
#> goals = col_double(),
#> xG = col_double(),
#> assists = col_double(),
#> xA = col_double(),
#> shots = col_double(),
#> key_passes = col_double(),
#> yellow_cards = col_double(),
#> red_cards = col_double(),
#> position = col_character(),
#> team_name = col_character(),
#> npg = col_double(),
#> npxG = col_double(),
#> xGChain = col_double(),
#> xGBuildup = col_double()
#> )
#> # A tibble: 21 × 19
#> player_id player_name games time goals xG assists xA shots key_passes
#> <dbl> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 619 Sergio Agüero 33 2515 21 19.9 8 5.23 118 34
#> 2 618 Raheem Sterling 34 2788 17 15.9 10 10.8 77 66
#> 3 337 Leroy Sané 31 1866 10 6.98 10 8.10 56 40
#> 4 750 Riyad Mahrez 27 1333 7 6.62 4 5.01 54 24
#> 5 3635 Bernardo Silva 36 2851 7 8.20 7 8.63 62 71
#> 6 5543 Gabriel Jesus 29 993 7 12.6 3 2.65 43 21
#> 7 314 Ilkay Gündogan 31 2133 6 4.21 3 4.97 43 43
#> 8 617 David Silva 33 2426 6 8.13 8 10.1 51 73
#> 9 2498 Aymeric Laporte 35 3059 3 3.75 3 0.839 26 13
#> 10 447 Kevin De Bruyne 19 965 2 1.47 2 6.65 31 36
#> # … with 11 more rows, and 9 more variables: yellow_cards <dbl>,
#> # red_cards <dbl>, position <chr>, team_name <chr>, npg <dbl>, npxG <dbl>,
#> # xGChain <dbl>, xGBuildup <dbl>, year <dbl>
Get stats for a player across all seasons:
get_player_seasons_stats(player_id = 618)
#>
#> ── Column specification ────────────────────────────────────────────────────────
#> cols(
#> position = col_character(),
#> games = col_double(),
#> goals = col_double(),
#> shots = col_double(),
#> time = col_double(),
#> xG = col_double(),
#> assists = col_double(),
#> xA = col_double(),
#> key_passes = col_double(),
#> year = col_double(),
#> team_name = col_character(),
#> yellow = col_double(),
#> red = col_double(),
#> npg = col_double(),
#> npxG = col_double(),
#> xGChain = col_double(),
#> xGBuildup = col_double(),
#> player_name = col_character()
#> )
#> # A tibble: 8 × 19
#> position games goals shots time xG assists xA key_passes year
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 FWL 3 1 7 128 1.71 0 0.111 1 2021
#> 2 AML 31 10 70 2539 12.1 7 6.63 39 2020
#> 3 FWL 33 20 100 2678 19.8 1 7.21 48 2019
#> 4 AML 34 17 77 2788 15.9 10 10.8 66 2018
#> 5 Sub 33 18 87 2594 18.8 11 8.84 55 2017
#> 6 AMR 33 7 64 2532 8.11 6 5.50 46 2016
#> 7 AML 31 6 52 1943 7.15 2 3.25 35 2015
#> 8 AML 35 7 84 3059 8.79 7 6.04 75 2014
#> # … with 9 more variables: team_name <chr>, yellow <dbl>, red <dbl>, npg <dbl>,
#> # npxG <dbl>, xGChain <dbl>, xGBuildup <dbl>, player_id <dbl>,
#> # player_name <chr>
Issues
If you encounter a clear bug, please file a minimal reproducible example on GitHub. For questions and other discussion, try stackoverflow or e-mail.
Disclaimer
While there is no official notice on the site condoning web scraping activity, Understat’s support have previously confirmed (via e-mail exchange, 8th November 2018) that their data is free to use for non-commercial purposes. This stance is subject to change.
Also, be polite and attribute the source.
Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.