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Datasets and Analytics for the National Women's Soccer League (NWSL)

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nwslR

Lifecycle: experimental CRAN status Travis build status

nwslR

nwslR is an R package that contains datasets and analysis functionality for the National Women’s Soccer League (NWSL). Founded in 2013, the NWSL is the United States’ top professional women’s soccer league, featuring players from all over the world. Previously, data regarding the league has been disparate and often difficult to find. The goal of this package is to make it easier for fans and analysts to access and engage with all these data in one place. We're just getting started here; we still have a few issues open where we could use some help! Additionally, if you see anything you'd like added, changed, or updated, please open up a new issue of your own.

This package is currently in the process of changing and updating significantly, so it is suggested that you frequently update it so that you have access to the most recent version.

Install

You can install the current version of nwslR from GitHub using:

devtools::install_github("adror1/nwslR")

Load

library(nwslR)

Available Tables

  • award: dataset of player awards received each season
  • fieldplayer_overall_season_stats: season-by-season data for each NWSL field player
  • franchise: team names, ids, and locations throughout their history in the league
  • game: dataset of game_ids and game results that each correspond to an individual game
  • goalkeeper_season_stats: season-by-season data for each NWSL goalkeeper
  • stadium: historical and current stadium information and statistics
  • team_stats_season: season level statistics for each team from the league's inception through present-day

Example: Player Statistics

head(nwslR::fieldplayer_overall_season_stats)
#> # A tibble: 6 x 14
#>   person_id season nation pos   team_id    mp starts   min   gls   ast    pk
#>       <int>  <dbl> <chr>  <chr> <chr>   <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1       342   2013 USA    DF    WAS         5      4    NA     0     0     0
#> 2       117   2013 USA    FW,MF NJ         20     20    NA     3     3     1
#> 3         6   2013 ESP    FW    WNY        15     14     3     1    NA     0
#> 4       300   2013 USA    DF,MF KC         22     22  1900     0     5     0
#> 5       202   2013 USA    DF    POR         4      2   212     0     0     0
#> 6       202   2013 USA    DF    BOS        11     11   990     0     1     0
#> # … with 3 more variables: p_katt <dbl>, crd_y <dbl>, crd_r <dbl>

Example: Team IDs

head(nwslR::franchise, 15)
#> # A tibble: 15 x 5
#>    team_id team_name              city        state season
#>    <chr>   <chr>                  <chr>       <chr>  <dbl>
#>  1 BOS     Boston Breakers        Boston      MA      2013
#>  2 BOS     Boston Breakers        Boston      MA      2014
#>  3 BOS     Boston Breakers        Boston      MA      2015
#>  4 BOS     Boston Breakers        Boston      MA      2016
#>  5 BOS     Boston Breakers        Boston      MA      2017
#>  6 KC      FC Kansas City         Kansas City MO      2013
#>  7 KC      FC Kansas City         Kansas City MO      2014
#>  8 KC      FC Kansas City         Kansas City MO      2015
#>  9 KC      FC Kansas City         Kansas City MO      2016
#> 10 KC      FC Kansas City         Kansas City MO      2017
#> 11 WNY     Western New York Flash Buffalo     NY      2013
#> 12 WNY     Western New York Flash Buffalo     NY      2014
#> 13 WNY     Western New York Flash Buffalo     NY      2015
#> 14 WNY     Western New York Flash Buffalo     NY      2016
#> 15 CHI     Chicago Red Stars      Chicago     IL      2013

Functionality

adv_team_stats #scraped and formatted dataset of hundreds of advanced team statistics from the NWSL website
adv_player_stats #scraped and formatted dataset of hundreds of advanced player statistics from the NWSL website

The above data tables will eventually be deprecated. Please use the functions before, instead.

To use this function, you need to find the game_id for a given game.

These are available in the game table (updated periodically throughout the season) or by looking on the NWSL website.

get_adv_team_stats("utah-royals-vs-washington-spirit-2019-04-20")
get_adv_player_stats("utah-royals-vs-washington-spirit-2019-04-20")
get_events("utah-royals-vs-washington-spirit-2019-04-20")
harris <- nwslR::player_search("Harris", goalkeeper = TRUE)
#> Joining, by = c("person_id", "nation", "pos")
head(harris)
#> # A tibble: 6 x 22
#>   person_id season nation pos   team_id    mp starts   min    ga ga_90 so_ta
#>       <dbl> <chr>  <chr>  <chr> <chr>   <dbl>  <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1     10007 2013   USA    GK    WAS        18     18  1620    33 1.83    118
#> 2     10007 2014   USA    GK    WAS        19     19  1710    31 1.63     97
#> 3     10007 2015   USA    GK    WAS         9      9   810    12 1.33     60
#> 4     10007 2016   USA    GK    ORL        15     15  1350    20 1.33     74
#> 5     10007 2017   USA    GK    ORL        13     13  1106     7 0.570    NA
#> 6     10007 2018   USA    GK    ORL        21     21  1890    31 1.48     NA
#> # … with 11 more variables: saves <dbl>, save_pct <dbl>, w <dbl>, d <dbl>,
#> #   l <dbl>, cs <dbl>, cs_pct <dbl>, crd_y <dbl>, crd_r <dbl>, player <chr>,
#> #   name_other <chr>

For further examples and capabilities, please see the vignette

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