dunkapi-skills

Plugin dunkapi-skills from marketplace dunkapi in noahowsh/dunkapi-mcp. Commands read from the repo's manifest — today.

Skills (16)

• backtesting

  Replays a basketball betting rule against historical closing lines from DunkAPI: collects per-book moneylines, spreads and totals by date, settles bets from final scores, computes ROI, units, closing-line value and confidence intervals, and applies realistic constraints (price availability, pushes,

• 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

• 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 use

• edge-detection

  Compares a calibrated basketball model probability with the market to estimate expected value, applies a minimum-edge threshold, sizes stakes with fractional Kelly, and tracks closing line value as the early test of whether an edge is real. Use when the user asks whether a bet has value, where their

• 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,

• 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

• 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 ne

• 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

• 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 hom

• 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 minute

• 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

• 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

• 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 a

• 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, clut

• 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 mis

• 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 e

MCP servers (1)

• dunkapi

  connects to: https://mcp.dunkapi.com/mcp

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