Sports data is your playbook: choose right, win fast. This multi-sport, ML-ready shortlist includes free + paid options, a quick comparison matrix, and clear notes on how to plug each dataset into live pipelines (prediction, CV, tracking).
Open Football APIs for Real-Time Modeling
1. StatsBomb Open Data
Volume: 30+ competitions, thousands of matches since 2018
Access: Free with attribution
Format: JSON event files + CSV match data
Task Fit: Event classification, player analysis, match prediction
If “context is king,” this is royalty—pressures, pass heights, shot freeze-frames, the lot. It punishes lazy features and rewards smart ones (xG, buildup chains, pitch zones). If your model reads the game instead of raw rows, it’ll shine here.
2. Open Football Data API
Volume: Live & historical match results, fixtures, odds
Access: Free API (registration required)
Format: REST API with JSON responses
Task Fit: Predictive modeling, betting analytics, match classification
Plug-and-play football feeds without the plumbing drama. Great for spinning up live win-probability, odds-driven features, and alerting dashboards. Mind the rate limits, cache smartly, and your models stay real-time sharp.
3. College Football Data API
Volume: 1,000+ games per season
Access: Free API
Format: REST API with JSON (games, drives, plays, rosters)
Task Fit: Win prediction, recruitment analysis, player performance
Saturday chaos, structured. Play-by-play, rosters, and drive data let you model tempo, field position, and coaching tendencies. If your features capture scheme and pace, expect serious lift on win-probability curves.
Player Tracking Datasets (Basketball & Football)
4. Kaggle: NBA Shot Logs (2014–15)
Volume: 128,000+ shots from 2014–15 NBA season
Access: Free (Kaggle account required)
Format: CSV (shot location, outcome, context)
Task Fit: Shot prediction, spatial analysis, player efficiency
A slam-dunk playground for spatial models: shot location, outcome, defender context. Perfect for heatmaps, shot quality, and player profiles without chasing proprietary feeds. If distance and angle make it into your features, buckets follow.
5. SoccerNet
Volume: 500+ full broadcast matches with event labels
Access: Free (research registration required)
Format: Video frames, bounding boxes, JSON event annotations
Task Fit: Player tracking, action recognition, event detection
The gold standard for football video ML. Synchronized multi-camera footage, broadcast commentary, and precise event tags make it ideal for benchmarking. If your detector can survive motion blur and crowd noise here, it’s ready for prime time.
6. Metrica Sports Sample Data
Volume: Full-match tracking + event logs
Access: Free (GitHub)
Format: CSV/JSON tracking coordinates + synchronized event data
Task Fit: Player tracking, tactical analysis, computer vision
Think of it as GPS for 22 dots sprinting, passing, and colliding. You get both event logs and full-match positional streams, perfectly synced. A sandbox for anyone testing CV models or tactical visualizations beyond static stats.
Historical Box Scores for Outcome Prediction
7. Sports Reference
Volume: Decades of MLB, NBA, NFL, NHL data
Access: Free
Format: Web tables + downloadable CSVs
Task Fit: Trend analysis, win prediction, player projections
The encyclopedia every U.S. sports analyst secretly bookmarks. Box scores, advanced stats, and historical leaders make it prime territory for long-range forecasting. If your model can’t find signal here, it probably won’t find it anywhere.
8. Lahman Baseball Database
Volume: Over 150 years of MLB stats
Access: Free download
Format: CSV/SQL database files
Task Fit: Historical trend analysis, performance prediction
Baseball’s memory palace, digitized. From dead-ball era oddities to modern OPS+, it’s all in structured tables. A dream dataset for time-series experiments that span generations of players and shifting styles of play.
9. Division III Basketball Play-by-Play
Volume: 300,000+ plays from multiple Division III games
Access: Free (Kaggle)
Format: CSV logs with timestamps, players, and events
Task Fit: Sequence modeling, outcome prediction, time-series
A raw look into small-college basketball where structure meets chaos. Every pass, foul, and run of play is timestamped—perfect for training models that understand momentum and clutch shifts. Ideal for testing RNNs, LSTMs, or transformers built for sports flow.
10. NHL Play-by-Play Data
Volume: 10+ years of NHL logs
Access: Free (Kaggle)
Format: CSV event logs with shots, penalties, goals
Task Fit: Shot analysis, win prediction, efficiency metrics
Hockey isn’t chaos—it’s structured chaos, and this dataset proves it. Play-by-play sequences let you analyze shot quality, penalty impact, and even goalie hot streaks. A sturdy launchpad for predictive hockey analytics.
Event-Level Sports Data for xG & Tactics
11. FIFA 23 Player Dataset
Volume: 19,000+ players, 100+ attributes
Access: Free (Kaggle)
Format: CSV (player attributes, positions, clubs, nations)
Task Fit: Classification, clustering, scouting
Ratings, traits, and roles—enough signal to build a scouting engine that actually feels smart. Slice by league, position group, or age curve and surface “hidden gems” your rivals overlook. Great playground for similarity search, role archetyping, and squad planning.
12. Football Manager Complete Dataset
Volume: 150,000+ players
Access: Free (Kaggle)
Format: CSV (player stats, attributes, positions, nations)
Task Fit: Recommendation, scouting analysis
A cult dataset reborn — clean, deep, and refreshingly current. Attribute-rich player profiles make it perfect for training recommender systems or similarity searches. Whether you’re matching midfield archetypes or ranking potential signings, this one’s pure transfer gold.
13. WTA & ATP Tennis Stats and Results
Volume: WTA and ATP matches from 1949–2021
Access: Free (Kaggle)
Format: CSV (match results, player stats, tournament metadata)
Task Fit: Outcome prediction, ranking models
Seven decades of tennis history — Grand Slams, upsets, and dominance cycles captured in one dataset. Ideal for modeling Elo-style ratings, predicting match outcomes, or studying era-based performance trends. If your model respects surface and fatigue, this set rewards nuance.
Multi-Sport APIs and Data Sources
14. balldontlie NBA API
Volume: Historical & current NBA games, players, and stats
Access: Free (no key required; sensible rate limits)
Format: REST API with JSON responses
Task Fit: Real-time dashboards, trend analysis, prediction features
Clean, consistent NBA endpoints without scraping drama. Pull games, box scores, players, and season splits straight into notebooks or BI tools. Great for building live tiles, baseline models, and stat pipelines in a single afternoon.
15. Sports Stats API
Volume: Covers football, basketball, hockey, tennis
Access: Free tier + paid plans
Format: REST API with JSON (multi-sport endpoints)
Task Fit: Multi-sport modeling, visualization, predictions
One doorway, many sports. Pull consistent JSON across leagues, wire it into your ETL, and ship a unified analytics layer fast. Ideal for teams that need breadth without juggling five different vendor schemas.
16. ESPN Sports Data via Flipside LiveQuery
Volume: Scores, schedules, and player stats across major U.S. sports
Access: Free (requires Flipside account)
Format: SQL-based API queries returning JSON/CSV
Task Fit: Trend analysis, visualization, performance tracking
Finally—ESPN data without the scraping pain. Query real game stats, schedules, and leaderboards directly through SQL endpoints. Ideal for analysts who want clean pipelines from ESPN’s ecosystem into BI dashboards or ML notebooks in minutes.
17. FiveThirtyEight Sports Data
Volume: Multiple datasets (NBA, NFL, MLB, more)
Access: Free (GitHub)
Format: CSV with documentation/READMEs
Task Fit: Prediction, sports betting, storytelling
The datasets behind headline-grabbing forecasts, packaged for immediate use. Clean columns, sensible dictionaries, and repeatable structures make baselines quick to build. Great for demos, benchmarks, and explainable models your PM can love.
18. DataHub Football Data Collection
Volume: 60K+ match results from global leagues and tournaments
Access: Free (open source, downloadable CSV/JSON)
Format: CSV/JSON (team stats, results, goals, standings)
Task Fit: Experimental modeling, benchmarking, reproducibility
A clean, structured, and open dataset that brings worldwide football stats to your fingertips. No scraping, no rate limits—just tidy data ready for ML models, dashboards, or quick EDA. Ideal for testing match outcome prediction or transfer learning across leagues.
19. Match Charting Project – Tennis Data
Volume: 60K+ ATP & WTA matches (1968–2024)
Access: Free (open GitHub repo)
Format: CSV (match results, players, stats)
Task Fit: Outcome prediction, ranking models, time-series
A long-running open tennis dataset curated by Jeff Sackmann. Clean, consistent columns for player, surface, round, and result — perfect for building predictive models or ranking algorithms without any preprocessing.
20. UCI Sports Datasets
Volume: Small-to-mid datasets (athletics, gym, swimming)
Access: Free
Format: CSV/ARFF; some sensor streams
Task Fit: Classification, biomechanics, activity recognition
A classic playground for quick experiments and teaching notebooks. Sensor-rich tasks like activity recognition let you test pipelines without heavy ETL. When you need clean, compact data to prove a point, start here.
🏅 Sports Dataset Cheat-Sheet (2025)
⚽ Football / Soccer Analytics
| Dataset | Volume | Data Type | Special Features | Ideal Use Case | License / Access |
|---|---|---|---|---|---|
| SoccerNet v3 | 500+ full matches | Video + JSON annotations | Multi-camera, event tags, sync audio | Video action detection, temporal localization | Free (research) |
| StatsBomb Open Data | 30+ competitions | JSON events, CSV matches | Detailed events, pressures, xG | Tactical modeling, xG pipelines | Free (attribution) |
| Open Football Data API | Live + historical | REST/JSON API | Results, fixtures, odds | Real-time prediction, betting analytics | Free (registration) |
| Understat xG Data | Top 5 leagues (2014–2024) | JSON (shots, players, teams) | Shot locations + xG values | xG modeling, form tracking | Free (public) |
| DataHub Football Data | 60K+ matches worldwide | CSV/JSON | Clean schema, global coverage | Outcome prediction, cross-league benchmarking | Free (open source) |
🏀 Basketball Analytics
| Dataset | Volume | Data Type | Special Features | Ideal Use Case | License / Access |
|---|---|---|---|---|---|
| NBA Shot Logs (2014–15) | 128K+ shots | CSV | Shot location, defender context | Spatial models, shot prediction | Free (Kaggle) |
| balldontlie NBA API | All seasons since 1979 | REST/JSON API | Games, players, stats | Dashboards, forecasting, live features | Free (public) |
| Division III Basketball Play-by-Play | 300K+ plays | CSV | Timestamps, sequential play data | Sequence modeling, win prediction | Free (Kaggle) |
🎾 Tennis Analytics
| Dataset | Volume | Data Type | Special Features | Ideal Use Case | License / Access |
|---|---|---|---|---|---|
| Jeff Sackmann Tennis Data | 60K+ ATP & WTA matches | CSV | Clean stats, surfaces, tournaments | Ranking, match prediction | Free (GitHub) |
| WTA & ATP Stats (1949–2021) | ~72 years of results | CSV | Players, tournaments, rankings | Outcome prediction, era analysis | Free (Kaggle) |
| Match Charting Project | 10K+ charted matches | CSV | Manual shot sequences | Tactics, sequence modeling | Free (open) |
⚾ Baseball Analytics
| Dataset | Volume | Data Type | Special Features | Ideal Use Case | License / Access |
|---|---|---|---|---|---|
| Lahman Baseball Database | 150+ years of MLB stats | CSV/SQL | Structured tables by season | Performance forecasting, sabermetrics | Free (public) |
| Retrosheet Play-by-Play | 100+ seasons | CSV / event text | Pitch-by-pitch, substitutions | Game simulation, strategy modeling | Free (public) |
🏈 Multisport & General Analytics
| Dataset | Volume | Data Type | Special Features | Ideal Use Case | License / Access |
|---|---|---|---|---|---|
| OpenSports Dataset (DataHub) | 50K+ records | CSV/JSON | Unified schema across sports | Cross-sport analytics, feature engineering | Free (open source) |
| SportsMOT | 240 video sequences | Video + JSON | Multi-object tracking | Object detection, motion tracking | Free (research) |
Conclusion
From detailed football event logs to real-time APIs spanning dozens of sports, these datasets cover the full spectrum of analytics needs. Whether you’re modeling match outcomes, building scouting engines, or training CV models, there’s a dataset here to fuel your project.
