Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/matiasmascioto/awesome-soccer-analytics
:soccer::chart_with_upwards_trend: A curated list of awesome resources related to Soccer Analytics.
https://github.com/matiasmascioto/awesome-soccer-analytics
List: awesome-soccer-analytics
analytics awesome football soccer sports sports-analytics
Last synced: 16 days ago
JSON representation
:soccer::chart_with_upwards_trend: A curated list of awesome resources related to Soccer Analytics.
- Host: GitHub
- URL: https://github.com/matiasmascioto/awesome-soccer-analytics
- Owner: matiasmascioto
- License: cc0-1.0
- Created: 2019-02-14T23:10:45.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2020-11-17T15:36:48.000Z (about 4 years ago)
- Last Synced: 2024-04-10T10:17:18.882Z (9 months ago)
- Topics: analytics, awesome, football, soccer, sports, sports-analytics
- Homepage:
- Size: 31.3 KB
- Stars: 476
- Watchers: 32
- Forks: 65
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
Awesome Lists containing this project
- ultimate-awesome - awesome-soccer-analytics - :soccer::chart_with_upwards_trend: A curated list of awesome resources related to Soccer Analytics. (Other Lists / Monkey C Lists)
README
# Awesome Soccer Analytics [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)
A curated list of awesome resources related to *Soccer Analytics* in *english* and *spanish*.
- References:
- *S+: Soccer and other sports. The resource is not just about soccer.*### Contents
* [Blogs & Websites](#blogs--websites)
* [Books](#books)
* [Companies](#companies)
* [Data](#data)
* [Education](#education)
* [Events & Conferences](#events--conferences)
* [Open Source Libraries](#open-source-libraries)
* [Podcasts](#podcasts)
* [Tools & Projects](#tools--projects)
* [Twitter Accounts](#twitter-accounts)
* [Videos](#videos)
* [Miscellaneous](#miscellaneous)## Blogs & Websites
* [2+2=11](https://2plus2equals11.com/)
* [All Things Football](https://allthingsfootballonline.blogspot.com/)
* [American Soccer Analysis](https://www.americansocceranalysis.com/)
* [Analítica Sports](http://www.analiticasports.com) (S+)
* [differentgame](https://differentgame.wordpress.com/)
* [EightyFivePoints](http://eightyfivepoints.blogspot.com/)
* [Football Crunching](https://medium.com/football-crunching)
* [Football Science](https://www.footballscience.net/)
* [Football Data Science](http://business-analytic.co.uk/blog/home-page/)
* [Football Whispers](https://www.footballwhispers.com/)
* [G.C. Analytics](https://www.gcanalytics.net/)
* [Karun Singh](https://karun.in/blog/)
* [North Yard Analytics](https://www.northyardanalytics.com/blog/)
* [OptaPro](https://www.optasportspro.com/news-and-analysis/?_news_category=football)
* [Proform AFC](https://proformanalytics.wordpress.com/)
* [Soccermetrics](http://www.soccermetrics.net/blog)
* [Stats and snakeoil](http://www.statsandsnakeoil.com/)
* [StatsBomb](https://statsbomb.com/)
* [The Harvard Sports Analysis Collective](http://harvardsportsanalysis.org/topics/soccer/)
* [The Last Man Analytics](https://thelastmananalytics.home.blog/) (S+)
* [The Power of Goals](https://thepowerofgoals.blogspot.com/)
* [Total Football Analysis](https://totalfootballanalysis.com/)
* [Wyscout](https://blog.wyscout.com/)## Books
* [Football Hackers: The Science and Art of a Data Revolution](https://www.amazon.com/Football-Hackers-Science-Data-Revolution-ebook/dp/B07NQM3YGK)
* [Soccernomics](https://www.amazon.com/Soccernomics-England-Germany-Australia-Destined/dp/1568584814)
* [Soccermatics: Mathematical Adventures in the Beautiful Game](https://www.amazon.com/Soccermatics-Mathematical-Adventures-Pro-Bloomsbury/dp/1472924142)
* [The Numbers Game: Why Everything You Know about Soccer Is Wrong](https://www.amazon.es/Numbers-Game-Everything-about-Soccer/dp/0143124560)## Companies
### Data Providers
* [DataFactory](http://www.datafactory.la/) (S+)
* [Opta Sports](https://www.optasports.com/) (S+)
* [SPORTLOGiQ](https://sportlogiq.com/en/) (S+)
* [Sport radar](https://www.sportradar.com/) (S+)
* [STATS PERFORM](https://www.statsperform.com/) (S+)
* [StatsBomb](https://statsbomb.com/data/)
* [Wyscout](https://wyscout.com/es/)### Tracking
* [ChyronHego](https://chyronhego.com/)
* [STATS SportVU](https://www.stats.com/sportvu-football/)
* [Kinexon](https://kinexon-sports.com/) (S+)
* [Oliver](https://tryoliver.com/)### Video Analysis - Performance Analysis
* [Analytics FC](http://analyticsfc.co.uk/)
* [dataFootball](https://www.bdatafutbol.com/)
* [ERIC Sports](http://www.ericsports.net/) (S+)
* [Futbolytics](https://futbolytics.cl/)
* [hudl](https://www.hudl.com/) (S+)
* [LBi Dynasty](http://www.lbidynasty.com/) (S+)
* [LongoMatch](https://longomatch.com/es/) (S+)
* [MEDIACOACH](https://portal.mediacoach.es/)
* [Metrica Sports](https://metrica-sports.com/)
* [nacsport](https://nacsport.com/) (S+)
* [Olocip](http://www.olocip.com/) (S+)
* [SICO](https://www.sicostats.com/)
* [Wise](http://app.wise4sports.com/home/) (S+)## Data
### Datasets
* [A public data set of spatio-temporal match events in soccer competitions](https://figshare.com/collections/Soccer_match_event_dataset/4415000) : Free - .json - UEFA Euro Cup 2016 - La Liga, Serie A, Bundesliga, Premier League, Ligue 1, FIFA World Cup 2018
* [European Soccer Database](https://www.kaggle.com/hugomathien/soccer/version/10): Free - .sqlite - 25k+ matches, players & teams attributes for European Professional Football
* [engsoccerdata](https://github.com/jalapic/engsoccerdata): Free - .csv - English and European soccer results 1871-2017
* [football.csv](https://footballcsv.github.io/): Free - .csv - Historical soccer results in .csv format
* [football.db](http://openfootball.github.io/): Free - database - A free and open public domain football database & schema for use in any (programming) language (e.g. uses plain datasets).
* [Metrica Sports sample tracking and event data](https://github.com/metrica-sports/sample-data): Free - .csv - Sample tracking and event data.
* [PlusMinusData](https://github.com/fmatano/PlusMinusData): Free - R package - Play by play data from espn.com and sofifa.com
* [Rec.Sport.Soccer Statistics Foundation](http://www.rsssf.com/nersssf.html): Free- database - Historical league tables and football results
* [RoboCup Soccer Simulator](http://oliver.obst.eu/data/RoboCupSimData/overview.html): Free - .csv - RoboCup Soccer Simulator Data
* [Soccer match event dataset](https://figshare.com/collections/Soccer_match_event_dataset/4415000/2): Free - .json - Spatio-temporal events (passes, shots, fouls, etc.) that occur during all matches of an entire season of seven competitions (La Liga, Serie A, Bundesliga, Premier League, Ligue 1, FIFA World Cup 2018, UEFA Euro Cup 2016).
* [Soccer Video and Player Position Dataset](http://home.ifi.uio.no/paalh/dataset/alfheim/): Free - .csv - Dataset of elite soccer player movements and corresponding videos
* [StatsBomb Open Data](https://github.com/statsbomb/open-data): - Free - JSON - Competitions and matches (with events)
* [wosostats](https://github.com/amj2012/wosostats): Free - .csv - Data about women's soccer from around the world.### APIs
* [BDFUTBOL](https://www.bdfutbol.com/es/c/api2.html): Paid - Historical football results, players and teams data
* [ClubElo](http://clubelo.com/API): Free - Historical ELO rankings for european soccer.### Other resources
* [Awesome Footbal](https://github.com/planetopendata/awesome-football): A collection of awesome football (national teams, clubs, match schedules, players, stadiums, etc.) datasets.
* [Guide to Football/Soccer data and APIs](https://www.jokecamp.com/blog/guide-to-football-and-soccer-data-and-apis/)## Education
* [Máster Big Data Deportivo](https://www.campusbigdata.com/master-en-big-data-deportivo): Certified by [UCAM](https://www.ucam.edu/).
* [Posgrado en Sports Analytics](https://www.talent.upc.edu/esp/estudis/formacio/curs/303600/postgrau-sports-analytics/): Universitat Politècnica de Catalunya
* [Soccer Analytics Handbook](https://github.com/devinpleuler/analytics-handbook): Getting started with soccer analytics
* [StatsBomb Courses](https://courses.statsbomb.com/: StatsBomb courses are delivered by video and webinar## Events & Conferences
* [Carnegie Mellon Sports Analytics Conference](http://www.cmusportsanalytics.com/conference2018.html)
* [CASSIS](http://cascadiasports.com/)
* [Football Data International Forum](https://eniit.es/football-data-international-forum/)
* [Global Training Camp](http://gtc.analyticsinsport.com/)
* [Great Lakes Analytics Conference](https://www.uwsp.edu/cols/Pages/GLAC/analyticsconference.aspx)
* [MathSport International](http://www.mathsportinternational.com/)
* [MIT Sloan Sports Analytics Conference](http://www.sloansportsconference.com/)
* [New England Symposium on Statistics in Sports](http://www.nessis.org/)
* [OptaPro Analytics Forum](https://www.optasportspro.com/events/)
* [Sports Analytics World Series](https://www.analyticsinsport.com/)
* [Sportdata & Performance Forum](https://www.sportdataperformance.com/)
* [Sports Technology Symposium](https://www.fcbarcelona.com/club/sports-technology-symposium)
* [StatsBomb Conference](https://statsbomb.com/conference/)## Open Source Libraries
### Visualisation
* [BirdsPyView](https://github.com/rjtavares/BirdsPyView): (Python) A Streamlit app to transform perspective of an image to a top-down view by identifying a rectangle on the ground
* [ggsoccer](https://github.com/Torvaney/ggsoccer) - (R) Plot Opta-style soccer event data in R/ggplot2.
* [PlusMinusModels](https://github.com/tpospisi/PlusMinusModels) - (R) This package fits plus-minus models for sports data.
* [PyFootballPitch](https://github.com/znstrider/PyFootballPitch) - (Python) Functions to draw a football pitch in various available styles for matplotlib and bokeh.
* [SBpitch](https://github.com/FCrSTATS/SBpitch) - (R) Creates customisable plots of pitches in ggplot2 that allows event data to be plotted on top.
* [socceraction](https://github.com/ML-KULeuven/socceraction): (Python) - Convert existing soccer event stream data to SPADL and value player actions
* [soccerAnimate](https://github.com/Dato-Futbol/soccerAnimate): (R) - An R package to create 2D animations of soccer tracking data
* [soccermatics](https://github.com/JoGall/soccermatics) - (R) Tools for visualisation and analysis of soccer spatiotemporal data.
* [Tracking-Data](https://github.com/KubaMichalczyk/Tracking-Data) - (R) Plots soccer tracking data.### Others
* [Codeball](https://codeball.metrica-sports.com/) - (Python) Data driven tactical and video analysis of soccer games.
* [Expected-Goals-Model](https://github.com/KubaMichalczyk/Expected-Goals-Model) - (R) Expected Goals Model.
* [extending-xG-gain](https://github.com/KubaMichalczyk/extending-xG-gain) - (R) An attempt to extend xG gain.
* [Football-crunching](https://github.com/rjtavares/football-crunching) - (Python) Some soccer analysis.
* [passing-networks](https://github.com/JoGall/passing-networks) - (R) Tools to create team passing networks from soccer passing data.
* [regista](https://github.com/Torvaney/regista) - (R) Package for performing some of the common modelling tasks in soccer analytics.
* [simulated-walks](https://github.com/JoGall/simulated-walks) - (R) Simulate movement of football players using a random walk rule.
* [statsbomb-parser](https://github.com/imrankhan17/statsbomb-parser) - (Python) Convert StatsBomb's JSON data into easy-to-use CSV format.
* [statsbomb\_python](https://github.com/petermckeever/statsbomb_python) - (Python) Python Package for using Statsbomb IQ dataset.
* [StatsBomb\_WomensData](https://github.com/FCrSTATS/StatsBomb_WomensData) - (R) Utilising the free women's football data supplied by Statsbomb to help explore and teach football analytics.
* [xyFootyPy](https://github.com/znstrider/xyFootyPy) - (Python) Introduction to working with Positional Data - Using RoboCup 2D Simulation Data.
* [football-graphs](https://github.com/rodmoioliveira/football-graphs) - (Clojure) Some visualizations on passing networks## Podcasts
* [Analytics FC Podcast](https://podcasts.apple.com/gb/podcast/analytics-fc-podcast/id991610009)
* [Big Data Sports](https://podcasts.apple.com/us/podcast/big-data-sports/id1377252519) (S+)
* [Differentgame - The Football Analytics Podcast](https://podcasts.apple.com/pk/podcast/differentgame-the-football-analytics-podcast/id1226164447?mt=2)
* [Expected Value](https://podcasts.apple.com/us/podcast/expected-value/id1477998252) (S+)
* [Measurables](https://www.measurablespod.com/) (S+)
* [Three At The Back (By OptaPro)](https://itunes.apple.com/sk/podcast/three-at-the-back/id1143073118?mt=2)## Tools & Projects
* [Following Messi](https://becominghuman.ai/following-messi-with-tensorflow-and-object-detection-20ba6d75667) - (Python) Following Messi with TensorFlow and Object Detection.
* [Expected Goals interactive site](https://torvaney.github.io/projects/xG.htm
* [Football + Voronoi](http://durtal.github.io/interactives/Football-Voronoi/)
* [Game event Tracker](https://codepen.io/Mcnultyj/live/gdVbyv)
l)
* [Peter McKeever](http://petermckeever.com/plotting-xy-football-data-in-python/) - (Python) Plotting xy football data in python.
* [PySport](https://pysport.org/)
* [Soccer event logger](https://torvaney.github.io/projects/tracker.html)## Twitter Accounts
### Data Scientists - Data Analysts
* [Andre Brener](https://twitter.com/andre_brener)
* [Dan Altman](https://twitter.com/NYAsports)
* [Eliot McKinley](https://twitter.com/etmckinley)
* [Garry Gelade](https://twitter.com/GarryGelade)
* [Karun Singh](https://twitter.com/karun1710)
* [Luke Bornn](https://twitter.com/LukeBornn)
* [Mark Taylor](https://twitter.com/MarkTaylor0)
* [Mark Thompson](https://twitter.com/EveryTeam_Mark)
* [Mladen Sormaz](https://twitter.com/Mladen_Sormaz)
* [Paul Power](https://twitter.com/counterattack9)
* [Paul Riley](https://twitter.com/footballfactman)
* [Philip Z. Maymin](https://twitter.com/pmaymin)
* [Peter McKeever](https://twitter.com/petermckeever)### Others
* [Big Data Sports](https://twitter.com/bigdatasport)
* [danzn1](https://twitter.com/danzn1)
* [FC Python](https://twitter.com/FC_Python)
* [FC rSTATS](https://twitter.com/FC_rstats)
* [Fútbol Avanzado](https://twitter.com/FutbolAvanzado)
* [Last Row](https://twitter.com/lastrowview)
* [Predictive Analytics](https://twitter.com/moneyballfutbol)
* [The xG Philosophy](https://twitter.com/xGPhilosophy)## Videos
* [Football Player Ratings (YouTube channel)](https://www.youtube.com/channel/UC64jAkIQX-hD3pSnnOmr2MA)
* [Friends of Tracking (YouTube channel)](https://www.youtube.com/channel/UCUBFJYcag8j2rm_9HkrrA7w/featured)## Miscellaneous
* [Association of Sports Analytics Professionals](https://www.sportsanalyticsprofessionals.com/)
* [Expected Goal literature](https://docs.google.com/document/d/1OY0dxqXIBgncj0UDgb97zOtczC-b6JUknPFWgD77ng4/edit)
* [FIFA EPTS (Electronic Performance and Tracking Systems)](https://football-technology.fifa.com/en/media-tiles/epts/)
* [Football Tableau User Group](https://usergroups.tableau.com/footballtableauusergroup)
* [Football/soccer data analysts with publicly available work](https://docs.google.com/spreadsheets/d/1wjMVOpupmcF4hEG7PO4lY6l2mKsldGsnkyAULQwyAp8/edit?usp=sharing)
* [opensport (Google Group)](https://groups.google.com/forum/#!forum/opensport)
* [Technical Report - 2018 FIFA World Cup](https://img.fifa.com/image/upload/evdvpfdkueqrdlbbrrus.pdf)## Contribute
Contributions are always welcome! Send me a pull request.