This article was accepted into the corpus but its outbound wikilinks were never NER-processed — typical at the deepest BFS hop or when the run's entity cap was reached. No expansion funnel to show.
| AllSportDB | |
|---|---|
| Name | AllSportDB |
| Developer | Community contributors |
| Released | 2013 |
| Programming language | Python, JavaScript, SQL |
| Operating system | Cross-platform |
| Genre | Sports database |
| License | Open data / varied |
AllSportDB
AllSportDB is an open, community-driven database project cataloguing sports competitions, teams, players, venues, seasons, and events across association football, cricket, rugby, baseball, basketball, ice hockey, tennis, athletics, motorsport, and other sports. It aggregates structured records used by developers, broadcasters, researchers, statisticians, and fan projects, linking fixtures, results, squads, and competition metadata for use in applications and analytics.
AllSportDB provides a centralized schema and dataset for sports metadata integrating competitions such as the FIFA World Cup, UEFA Champions League, ICC Cricket World Cup, Rugby World Cup, Major League Baseball, NBA Finals, Stanley Cup, Wimbledon Championships, Roland Garros, Australian Open, Indian Premier League, and Formula One World Championship. It includes entities for clubs like Manchester United F.C., Real Madrid CF, Mumbai Indians, New York Yankees, Los Angeles Lakers, Toronto Maple Leafs; national teams like Brazil national football team, England national cricket team, New Zealand national rugby union team; and venues such as Wembley Stadium, Old Trafford, Eden Gardens, Melbourne Cricket Ground, Madison Square Garden, Camp Nou, Maracanã Stadium, Suzuka Circuit, Silverstone Circuit. The project interoperates with datafeeds and software used by organizations including ESPN, Opta Sports, Stats Perform, BBC Sport, Sky Sports, The Guardian, Reuters, and Associated Press.
The initiative originated in the early 2010s as an effort to standardize fixtures and team metadata inspired by projects like DBpedia, Wikidata, OpenStreetMap and sports-specific repositories such as Football-Data.co.uk and CricketArchive. Early contributions referenced competitions including UEFA Europa League, Copa América, CONCACAF Gold Cup, AFC Asian Cup, Copa Libertadores, CONMEBOL Copa Libertadores, and domestic leagues such as English Football League, La Liga, Bundesliga, Serie A, Ligue 1, Primeira Liga, MLS Cup, A-League Men, J1 League. Over time, contributors added historic seasons like the 1930 FIFA World Cup, 1966 FIFA World Cup, 1999 UEFA Champions League Final, 2005 UEFA Champions League Final, and tournament records for ICC T20 World Cup, FIBA Basketball World Cup, and IHF World Men's Handball Championship.
AllSportDB stores structured data objects for competitions, seasons, fixtures, results, teams, players, managers, referees, clubs, federations, confederations, venues, attendance, and match events. It covers tournaments such as the FA Cup, Coppa Italia, DFB-Pokal, Copa del Rey, Super Bowl, NFL Playoffs, NCAA Basketball Tournament, UEFA European Championship, Olympic Games, and multi-sport events like the Commonwealth Games. Player records include entries for athletes associated with clubs and national teams, including icons like Lionel Messi, Cristiano Ronaldo, Sachin Tendulkar, Virat Kohli, Michael Jordan, LeBron James, Wayne Gretzky, Novak Djokovic, Roger Federer, Lewis Hamilton, Michael Schumacher. Metadata also links governing bodies such as FIFA, UEFA, CONMEBOL, CAF, AFC, CONCACAF, ICC, World Rugby, FIBA, IIHF, IOC.
The schema aligns with common identifiers and standards used by organizations and databases including International Olympic Committee, ISO 3166, IANA time zone database, and modelling approaches seen in Wikidata and DBpedia. Entities are cross-referenced to league systems like English Football League Championship, Scottish Premiership, Bundesliga 2, and cup competitions such as the League Cup (England). Match event vocabularies map to notable fixtures like the El Clásico, Derby della Madonnina, Old Firm derby, North West Derby, and finals such as the Champions League Final. The dataset supports interoperability with APIs from platforms like GitHub, GitLab, Bitbucket, and continuous integration tools like Travis CI, CircleCI, Jenkins for automated updates.
Developers integrate AllSportDB for mobile apps, websites, broadcast graphics, data journalism, predictive models, fantasy sports platforms, and academic research. Use cases include scoreboard overlays for broadcasters such as NBC Sports, Fox Sports, CBS Sports, Eurosport; statistical dashboards used by outlets like FiveThirtyEight and The Athletic; fantasy game backends inspired by Fantasy Premier League and DraftKings. Researchers and institutions including MIT, Stanford University, University of Oxford, University of Cambridge, Harvard University have used sports datasets for studies in analytics, economics, and social science.
The project is maintained by volunteers, contributors, and mirror projects hosted on platforms like GitHub and GitLab, with discussion in forums and communities such as Stack Overflow, Reddit, Discord, and Stack Exchange. Contributors include statisticians, developers, sports historians, and organizations that maintain archives like RSSSF, Soccerbase, Transfermarkt, Baseball-Reference, Basketball-Reference, Hockey-Reference. Integration and tooling draw from libraries and frameworks such as Django, Flask, Node.js, React, Angular, Vue.js, Ruby on Rails, Laravel, Spring Framework.
Data licensing varies by dataset and contributor; portions mirror open licenses similar to Creative Commons and public domain datasets, while other segments require attribution aligned with data suppliers like Opta Sports or proprietary services such as Stats Perform. Access methods include downloadable dumps, RESTful APIs, and SQL exports compatible with systems including PostgreSQL, MySQL, SQLite, and analytics platforms such as Tableau, Power BI, Jupyter Notebook.
AllSportDB has been cited by hobbyist projects, media outlets, and academic papers focused on sports analytics, influence mapping, and historic records. It complements commercial datasets used by UEFA, FIFA, ICC, and clubs such as FC Barcelona, Bayern Munich, Juventus F.C. for non-exclusive purposes, and supports preservation efforts alongside archives like British Library sports collections, National Football Museum, and university special collections. Its community model echoes collaborative projects like Wikipedia and Wikidata in promoting accessible sports metadata.
Category:Sports databases Category:Open data projects Category:Sports statistics