King of the Court Tracker

A tracker for DraftKings Sportsbook's NBA King of the Court promo. Bettors who used their token on the night's points + rebounds + assists (PRA) leader split the bonus-bet pool. The promo ran on Tuesdays in 2025-26 ($1–3M pools) and on Wednesdays in 2026-27 (usually $2M; $5M on opening night).

Site: https://mattrudy13.github.io/kotc-tracker/

At a glance

• What it does: simulates each NBA night 10,000 times to estimate every player's chance of leading the slate in PRA, estimates how many bettors will pick each player, and ranks players by value: win chance divided by pick share, since a popular winner's prize is split many ways.
• How it was tested: fitted on October–January 2025-26 and tested on February–April (64 nights). On those nights the model's top pick won 18 times, against 16 for the plain "highest PRA average" pick: a real but small edge. A model factor stays only if it improves the holdout score (log loss). The pick-share model is fitted on DraftKings' published payout lists.
• Live record: the first 2026-27 promo night was Oct 21, 2026; graded results build up from there on the Model page. Tonight's three picks are tracked night by night: the #1 pick (Anthony Edwards) won $824 on Oct 21.
• Built with: JavaScript (Node), GitHub Actions on a schedule, GitHub Pages and ESPN's public API.

Pages

• Tonight (index.html): the next promo night, under a fight-poster masthead with the date, prize pool, games and first tip. It leads with the top 3 value picks (chalk left out): #1 as the "main event" with its stats, #2 and #3 below. Then the night's games and the model favorite, the model's win chance and estimated pick share for each player (top 15, "Show all" for the rest, with "+N% teammates out" tags), the players ruled out, a Best value list, a Most picked card, a live PRA leaderboard during games (polled from ESPN in the browser every minute) and this season's Kings. Each section has a one-line summary, with the full explanation under "How this works".
• Season (season.html): the PRA leader for every night, season PRA averages (70% of team games to qualify), and crown counts.
• History (history.html): every 2025-26 promo night: winners, PRA, pool, payout per winning bet, the model's backtest chance, and a link to the source post.
• Model (model.html): this season's locked predictions graded, the 2025-26 backtest against two baselines, what each model factor adds, how Tonight's three picks did (totals by pick and a result card per promo night), the value-pick record by strategy, a calibration chart, and how the model works.
• Night (day.html?d=YYYY-MM-DD): one night's top 10, the suggested picks and the model's list.

Best value

The prize is split among everyone who picked the King, so a popular favorite pays little. The Tonight page estimates each player's share of picks and shows value = win chance ÷ pick share (1.00× = fair), plus a rough dollar value per token. The share model is fitted on DK's "what could've been" payout lists (data/pickshare-<season>.json; partial lists through the listed players' shares of one another), with the post texts kept in data/posts/. Most lists come from u/DraftKings' posts on r/DKAssist, which have to be pasted in (Reddit blocks scripts). The public follows win chances loosely, leans toward big season averages, and piles onto rookies (about 3.4× the picks of a comparable veteran). Last season's average counts as 10 games of the current one, so early-season averages don't swing on one game.

node scripts/parse-dk-post.mjs <dk-network-url> --date YYYY-MM-DD --pool 2000000 --write
pbpaste | node scripts/parse-dk-post.mjs --file - --date YYYY-MM-DD --source <url> --partial --write  # pasted text
node scripts/fit-share.mjs        # compares variants on held-out nights, prints MODEL.share coefficients

The Tonight page leads with the top 3 value picks, leaving out "chalk": anyone expected to draw 10%+ of the picks, plus the hand-kept list in data/chalk.json. A "Most picked" card shows who the crowd is on and what they'd pay. The Model page tracks each way of picking (favorite, best value, chalk left out, filling in for a missing star, public favorite) with DK's actual payouts, and how Tonight's three picks did night by night (won or lost, where each finished, and what it paid or would have paid).

Data and automation

All data comes from ESPN's public site API (no key). .github/workflows/update-data.yml runs every 2 hours from October to April:

1. scripts/build-data.mjs: box scores, schedule, rosters and injuries → data/<season>.json, plus data/leaders-<season>.json for the pages. Seasons are named by start year (2026 = 2026-27).
2. scripts/predict.mjs: the model's predictions for today and the next promo night → data/predictions-<season>.json. A night's prediction locks at its first tip-off.
3. scripts/grade.mjs: grades locked predictions once the night's games are final, including how each of the night's three picks finished. A losing pick counts right away; a winning one counts once DK's payout is in data/promos-<season>.json.

Edited by hand:

• data/promos-<season>.json: the promo dates, format, pool, who DK paid, and the payout per winning bet.
• data/chalk.json: the players always left out of the suggested picks.
• data/posts/<night>.txt: pasted "what could've been" posts, parsed into data/pickshare-<season>.json.

The model

Projected PRA = recent minutes × PRA per minute (both weighted toward recent games and pulled toward last season), scaled by the game's betting total, then adjusted for teammates who are out (relative to the player's recent games) and the opponent's PRA allowed (model v2). Each night is then simulated 10,000 times; a questionable teammate's bump only applies in the simulations where they sit. The constants were fit on October–January 2025-26 and tested on February–April. Rerun the fit and the backtest with:

node scripts/backtest.mjs --fit        # v2 context constants (teammates, defense), prints the best
node scripts/backtest.mjs --fit-base   # v1 projection constants
node scripts/backtest.mjs              # writes data/backtest-2025.json, incl. the ablation

Run locally

node scripts/build-data.mjs && node scripts/predict.mjs && node scripts/grade.mjs
python3 -m http.server   # http://localhost:8000

Not affiliated with DraftKings.