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DunkAPI

ChatGPT plugin

NBA basketball data and stats

View in ChatGPT directory

DunkAPI connects ChatGPT and Codex to NBA basketball data from DunkAPI. It covers the NBA since 2004 with every shot located, the WNBA since 2006, and Division I men's and women's college basketball.

Ask for standings, schedules and scores, box scores, player averages and game logs, leaders, team ratings, play-by-play, shot charts, sportsbook odds, line movement and player prop lines. The plugin looks the answer up with read-only tools and reports what the data says, including the season, date and source of each number.

The first time you use it, you sign in with your DunkAPI account.

Limits: DunkAPI is read-only. It cannot place wagers, accept or track bets, or edit your account. Odds and prop lines are shown as information about the market, not as advice. Data comes from public sources and the DunkAPI pipeline and is not guaranteed to be error-free or current to the minute, so do not rely on it as the sole basis for financial decisions. Ratings shown are DunkAPI's own Elo-style ratings, not official rankings. Not affiliated with the NBA or any team.

Bundled skills teach the model how to choose the right tool for a question and how to explain results.

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Rank by placement

#9951of 10,70422places down24h—7d
#9,862#9,887#9,912#9,937Oct 4Oct 10Oct 16Oct 22Oct 28Nov 2

Rank in Data & analytics

#576of 6231places down24h—7d
#571#573#575Oct 4Oct 10Oct 16Oct 22Oct 28Nov 2

In its category

How this plugin compares with others in the same category. Positions are counted within the category, not across the whole directory.

Data & analytics576th of 623 by placement
#PluginPosition7d
574Panther#9917—
575EndzoneAPI#9941—
576DunkAPIThis page#9951—
577FastballAPI#9952—
578StrikerAPI#9953—

All 623 Data & analytics plugins

Example prompts

  • “Show the 2024-25 NBA standings.”
  • “Find Jalen Brunson and show his 2025-26 season averages.”
  • “Who were the top three NBA scorers per game in 2024-25?”

Skills

  • dispatch

    Routes a basketball analytics request to the right 2-3 skills. Load this FIRST when an NBA, WNBA or college basketball request comes in and you are unsure which skills to activate. Prevents loading all 16 skills when only 2-3 are needed. Do not use for a single obvious request such as devigging two prices, see odds-analysis directly.

  • dunkapi-tool

    Default data source for the DunkAPI skills. Routes every call to the 18 DunkAPI tools for NBA, WNBA, men's and women's college basketball: games, box scores, play-by-play, shot charts, team ratings, odds, line movement and player props. Use when any other skill needs basketball data, or when the user asks which tool answers a question or what a call costs.

  • feature-engineering

    Builds leak-free features for basketball prediction models from DunkAPI data: rolling team margin and efficiency, Elo rebuilt game by game, rest days and back-to-backs, home court, opponent-adjusted form, market features and player minutes. Use when the user wants to build a model of game outcomes, margins, totals or player stats, or asks what features to use or whether a feature leaks. Do not use for choosing a validation scheme, see walk-forward-validation. Do not use for calibrating output probabilities, see probability-calibration. Do not use for descriptive team or player summaries, see team-analysis or player-form.

  • game-lookup

    Finds basketball games and reads results: scores by date, team, range or season, upcoming schedule, and a single game's full box score. Use when the user asks who played, what the score was, who plays tonight, a team's recent results, or wants a game id for another call. Covers NBA, WNBA, men's and women's college. Do not use for odds comparison, see odds-explorer. Do not use for team strength, see team-analysis. Do not use for a pre-game breakdown, see game-preview.

  • game-preview

    Builds a full pre-game basketball preview: teams' Elo and efficiency, recent form, rest and back-to-backs, injuries, the market line across books, and a simple projection with its uncertainty. Use when the user asks to preview or break down tonight's game or the season opener, or wants everything needed before tip in one place. Works for the new season before it has games (falls back to last season's numbers and says so). Covers NBA, WNBA, men's and women's college. Do not use for results after the fact, see game-lookup. Do not use for devigging, see odds-analysis.

  • odds-analysis

    Odds math for basketball betting markets: American, decimal and implied probability conversion, vig, and four devigging methods (multiplicative, additive/Shin, power) applied to moneylines, spreads, totals and player props, plus building a consensus no-vig line across sportsbooks. Use when the user asks what a price implies, how to remove the vig, what the true probability is, or what a fair line is. Do not use for finding the best price or line movement, see odds-explorer.

  • odds-explorer

    Multi-book basketball odds comparison: best moneyline, spread and total across sportsbooks, vig per book, opening versus closing lines, and pre-tip line movement. Use when the user asks for current or historical odds, the best price, which book is off the market, how a line moved, or whether the home side covered. Covers NBA, WNBA, men's and women's college. Do not use for devigging or probability math, see odds-analysis. Do not use for player props, see prop-modeling.

  • player-form

    Reads a basketball player's recent form from his game log: rolling averages, minutes trend, per-minute rates, rest effects, home and road splits and opponent context, with proper shrinkage so a hot week is not mistaken for a new talent level. Use when the user asks if a player is hot, how his minutes have changed, what his last 10 games say, or needs rolling inputs for a projection. Covers NBA, WNBA, men's and women's college. Do not use for season profile and comparisons, see player-scouting. Do not use for shot location, see shot-zone-analysis. Do not use for prop lines, see prop-modeling.

  • player-scouting

    Looks up and profiles basketball players: finds the player id, reads per-season averages and shooting splits, compares two or more players on a per-minute basis, and pulls season leaderboards. Use when the user asks about a player, who leads a stat, how two players compare, or whether a scoring line is efficient or lucky. Covers NBA, WNBA, men's and women's college. Do not use for rolling or recent form across a season, see player-form. Do not use for shot location, see shot-zone-analysis. Do not use for prop lines, see prop-modeling.

  • probability-calibration

    Checks and fixes whether basketball model probabilities mean what they say: reliability tables, Brier score and log loss, Platt scaling and isotonic regression fitted out of sample, converting predicted margins to win and cover probabilities, and shrinking toward the market. Use when a model outputs win, cover or over probabilities, asks if 65% really wins 65% of the time, or needs probabilities from a margin model. Do not use for building the model, see feature-engineering. Do not use for choosing splits, see walk-forward-validation.

  • prop-modeling

    Builds basketball player prop models for points, rebounds, assists, threes, points + rebounds + assists, blocks and steals: projects minutes and per-minute rates from the game log, turns a projection into an over/under probability with a suitable distribution, compares it with devigged prop prices across books, and checks a player's history against his lines. Use when the user asks if a player will go over a number, how often he has hit his line, what a fair prop price is, or how to project a stat line. Props exist for NBA, WNBA and men's college only. Do not use for team-side or total models, see feature-engineering. Do not use for recent-form description alone, see player-form.

  • shot-zone-analysis

    Analyzes basketball shot profiles by zone using DunkAPI shot data: attempts, makes and points per shot in restricted area, paint, midrange, corner three and above-the-break three, compared with expected points per shot to separate shot quality from shot making. Also covers team defence by zone, clutch shots and drawing a shot chart from x/y. Use when the user asks where a player or team shoots, whether a hot shooter is lucky, which defence gives up the worst shots, or wants expected points. Do not use for season box-score averages, see player-scouting. Do not use for team pace and ratings, see team-analysis.

Show all 14
  • team-analysis

    Evaluates basketball teams: standings, DunkAPI Elo power ratings, pace, offensive and defensive rating, net rating and the four factors (eFG%, turnover rate, offensive rebound rate, free throw rate). Use when the user asks how a team is doing, who the best or fastest team is, why a team's record misleads, or wants two teams compared. Covers NBA, WNBA, men's and women's college. Do not use for a single game, see game-lookup or game-preview. Do not use for a player, see player-scouting. Do not use for where a team shoots from, see shot-zone-analysis.

  • walk-forward-validation

    Validates basketball prediction models with chronological walk-forward splits instead of random k-fold: expanding or rolling windows, season-block folds, purge gaps, proper benchmarks (home-team baseline and the closing line), paired significance tests and the sample sizes needed to detect a small edge. Use when the user has a model and asks if it is any good, asks whether k-fold or a random split is okay (it is not), or wants to tune hyperparameters on time-ordered game data. Do not use for building the features, see feature-engineering. Do not use for probability reliability, see probability-calibration.

Categories
Made by
DunkAPI · Website
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On Install
Capabilities
Look up NBA, WNBA and college teams and players, Read standings, schedules and scores, Read box scores, leaders and team stats, Read play-by-play and shot charts, Read sportsbook odds and prop lines (information only)
Availability
Available
Version
1.0.0
Keywords
nba, sports-data, sports-analytics, stats, dunkapi
Created
October 16, 2026
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