Sports Data and R – Scope for a Thematic (Rather than Task) View? (Living Post)

Via my feeds, I noticed a package announcement today for cricketR!, a new package for analysing cricket performance data.

This got me wondering (again!) about what other sports related packages there might be out there, either in terms of functional thematic packages (to do with sport in general, or one sport in particular), or particular data packages, that either bundle up sports related data sets, or provide and API (that is, a wrapper for an official API, or a wrapper for a scraper that extracts data from one or more websites in a slightly scruffier way!)

This is just a first quick attempt, an unstructured listing that may also include data sets that are more generic than R-specific (eg CSV datafiles, or SQL database exports). I’ll try to keep this post updated as I find/hear about more packages, and also work a bit more on structuring it a little better. I really should pist this as a wiki somewhere – or perhaps curate something on Github?

  • generic:
    • SportsAnalytics [CRAN]: “infrastructure for sports analysis. Anyway, currently it is a selection of data sets, functions to fetch sports data, examples, and demos”.
    • PlayerRatings [CRAN]: “schemes for estimating player or team skill based on dynamic updating. Implemented methods include Elo, Glicko and Stephenson” (via Twitter: @UTVilla)
  • athletics:
    • olympic {ade4} [Inside-R packages]: “performances of 33 men’s decathlon at the Olympic Games (1988)”.
    • decathlon {GDAdata} [CRAN]: “Top performances in the Decathlon from 1985 to 2006.” (via comments: Antony Unwin)
    • MexLJ {GDAdata} [CRAN]: “Data from the longjump final in the 1968 Mexico Olympics.” (via comments: Antony Unwin)
  • baseball:
  • basketball:
  • biathlon:
  • chess:
  •  cricket:
  • darts:
    • darts [CRAN]: “Statistical Tools to Analyze Your Darts Game” (via comments: @MarchiMax)
  • football (American football):
  • football (soccer):
    • engsoccerdata [Github]: “a repository for complete soccer datasets, along with some built-in functions for analyzing parts of the data. Currently includes English League data, FA Cup data, Playoff data, some European leagues (Spain, Germany, Italy, Holland).”. Citation: James P. Curley (2015). engsoccerdata: English Soccer Data 1871-2015. R package version 0.1.4
    • UKSoccer {vcd} [Inside-R packages]: data “on the goals scored by Home and Away teams in the Premier Football League, 1995/6 season.”.
    • Soccer {PASWR} [Inside-R packages]: “how many goals were scored in the regulation 90 minute periods of World Cup soccer matches from 1990 to 2002”.
  • fbRanks [CRAN]: “Association Football (Soccer) Ranking via Poisson Regression: time dependent Poisson regression and a record of goals scored in matches to rank teams via estimated attack and defense strengths” (via comments: @MarchiMax)
  • golf:
  • gymnastics:
  • horse racing:
    • RcappeR [Github]: “tools to aid the analysis and handicapping of Thoroughbred Horse Racing” (via Twitter: @UTVilla)
    • rBloodstock [Github]: “datasets from Thoroughbred Bloodstock Sales, Tattersalls sales from 2010 to 2015 (incomplete)” (via Twitter: @UTVilla)
  • ice hockey:
    • nhlscrapr [CRAN]: “routines for extracting play-by-play game data for regular-season and playoff
      NHL games, particularly for analyses that depend on which players are on the ice”      . [via comments – Triplethink]
    • hockey {gamlr} [Inside-R packages]: “information about play configuration and the players on ice (including goalies) for every goal from 2002-03 to 2012-13 NHL seasons” [via comments – Triplethink]
    • nhl-pbp [Github]: “code to parse and analyze NHL PBP data using R”.
    • ( liigadata (python) – utility for parsing Finnish ice hockey league game data from liiga.fi website)
  • motor sport:
  • skiing:
    • SpeedSki {GDAdata} [CRAN]: “World Speed Skiing Competition, Verbier 21st April, 2011.” (via comments: Antony Unwin)
  • sailing: I didn’t find any R packages, but I did find a sailing regatta results data interchange format: ISAF XML Regatta Reporting (XRR) Data Format
  • snooker:
  • swimming: I didn’t find any R packages, but I did find a swimming results data interchange format: Lenex; and a site that publishes data in that format: Omega Timing.
  • tennis:

It would perhaps make more sense to try to collect rather more structured (meta)data for each package. For example: homepage, sport/discipline; analysis, data (package or API), or analysis and data; if data: year-range, source, data coverage (e.g. table column headings); if analysis, brief synopsis of tools available (e.g. chart generators).

If you know of any others, please let me know via the comments and I’ll try to keep this page updated with a reasonably current list.

As well as packages, here are some links to blog posts that look at sports data analysis using R:

Again, if you can recommend further posts, please let me know via the comments.

PS other sports data interchange formats: SportsML-G2

Author: Tony Hirst

I'm a Senior Lecturer at The Open University, with an interest in #opendata policy and practice, as well as general web tinkering...

16 thoughts on “Sports Data and R – Scope for a Thematic (Rather than Task) View? (Living Post)”

    1. @znmeb_rfs Ooh – that looks interesting. There’s great scope, I think, for putting together distributions that make it easier for journalists to get started using this tools by removing the setup hassle, and effectively turning them in to run anywhere apps, eg launched by something like Kitematic?

      I sketched one approach out around the ergast motor racing data that linked in MySQL database: https://blog.ouseful.info/2015/01/17/connecting-rstudio-and-mysql-docker-containers-the-ergastdb/

      FWIW, I started trying to pull together list of various packages that support authoring Rmd/python across RStudio, IPython Notebooks, etc.: https://blog.ouseful.info/2015/06/06/ipython-markdown-opportunities/

  6. Thank for getting this thread started!
    There is a larger decathlon dataset (almost 8000 results) in the package GDAdata. The package also includes two smaller sports datasets, one for the World Speed Skiing Competition in 2011 and one for the longjump final in the 1968 Mexico Olympics—for those of us who remember the shock of Bob Beamon’s performance.

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