Pricing

from $2.50 / 1,000 game extracteds

Basketball API Scraper — Box Scores, Stats & Standings

Basketball data API: per-player box scores with points, rebounds, assists, steals, blocks, plus-minus and field goal percentage; league standings with win percentage and games behind; season schedules, quarter-by-quarter scores, play-by-play, rosters with salaries, live games and point spreads.

Pricing

from $2.50 / 1,000 game extracteds

Rating

0.0

(0)

Developer

SIÁN OÜ

Actor stats

Bookmarked

Total users

Monthly active users

4 days ago

Last modified

[2026-07-31]

🎉 Basketball API Scraper - Launch!

Per-Player Box Scores - Pull 22 statistical columns for every player in every game: points, rebounds, assists, steals, blocks, turnovers, personal fouls, plus-minus, minutes played, field goal percentage and full shooting splits
League Standings in One Call - Wins, losses, win percentage, games behind, streak and point differential, with every conference, division and league-wide table returned together
Quarter-by-Quarter Scoring - Every game row carries points per quarter, overtime and the playoff series score, not just a final result
Shot-Classified Play-by-Play - Every basket labelled as a one, two or three-pointer with the running score and the player who scored it
Roster & Player Salary Data - Jersey numbers, positions, heights, weights, nationalities, salary amounts and contract expiry dates
Point Spread & Game Total Odds - Basketball markets with opening and current prices plus price movement
Live Basketball Scores - Every game in progress worldwide with current quarter and running score
Pay Per Operation - 14 discrete charge events, so a league standings pull never costs the same as a 109-row play-by-play pull

💎 User Benefits

Fantasy basketball developers get production-grade per-player data without maintaining a scraper
Analytics teams get whole-league tables and full season histories from a single operation
Betting modellers get odds, quarter-level team stats and scoring sequences for the same game
Error rows are written to the dataset for transparency and are never charged
Export straight to JSON, CSV, Excel or XML from the Apify dataset

🎯 Use Cases

Fantasy platform developers building draft boards and weekly projections from per-player box scores
Front-end teams shipping live score widgets that refresh in-play basketball games
Analytics teams tracking record, streak, roster turnover and payroll on one season dashboard
Quantitative modellers backtesting closing-line value against quarter-scoring distributions
Journalists and academics assembling reproducible historical basketball datasets
Scouts building cross-league player databases with contract expiry tracking

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