Open-source football market efficiency analytics for AQX Sports Analytics Data Bowl 3.0.
PitchValue answers a simple sports-economics question:
How much on-pitch production do clubs and players deliver for the wages and market prices they command?
Football clubs still silo performance data and squad economics. Recruitment reviews goals and xG; finance reviews wage bills and amortisation. Without a shared board:
- High payroll can hide weak process quality (
xG − xGA) - Breakout contributors stay underpriced until the public market jumps
- Finishing variance gets mistaken for sustainable form
An interactive dashboard that merges:
| Layer | Signal |
|---|---|
| Club efficiency | Points per wage £, process delta, finishing luck, composite score, value gap |
| Player pricing | Performance index → age/position fair value → under / fair / over tags |
| Form & forecast | Last-8 contribution series + short-horizon forecast |
| Decision layer | Auto-generated buy / sell / watch / hold notes |
Demo data is Premier League–style and fully offline so the prototype runs with zero API keys. Swap in FBref, StatsBomb, Transfermarkt, or club feeds for production.
npm install
npm run devProduction build:
npm run build
npm run previewDeploy free on Vercel or Netlify (vercel.json included). Node.js 18+ recommended.
- Club board — wage vs points scatter, efficiency ranking, full table
- Player board — market vs performance scatter, position & pricing filters
- Scouting card — fair value, premium, /90 contribution, wage, form chart
- Actions feed — board-ready recommendations
- Method section — transparent model notes for judges & contributors
Club efficiency blends wage productivity, process quality, and a mild penalty for extreme finishing luck. Value gap compares actual wages to the league’s wage-per-point norm.
Player fair value starts from a performance index (goals, assists, xG/xA, progressive passes & carries, tackles won, minutes), then adjusts for age and position. Market premium tags undervalued / fair / overvalued bands.
These models are explanatory demos for an open-source competition prototype, not production valuations.
- Recruitment — shortlist high output-per-pound players early
- Sporting / finance — flag payroll that fails to match process
- Analysts & media — narrate the table with economics + xG, not vibes
src/
data/league.ts # Teams, players, wages, market values, form
data/meta.ts # Project name & event label
lib/analytics.ts # Efficiency, valuation, insights
App.tsx # Interactive UI
index.css # Brand system
PitchValue is an open-source football analytics web app built for AQX Sports Analytics Data Bowl 3.0. It links club wage bills and player market values to on-pitch process metrics (xG, progressive actions, form) to surface undervalued talent and inefficient payrolls. Users explore interactive club and player boards and receive auto-generated buy/sell/watch actions. Demo data ships in-repo so anyone can run and extend the project immediately.
MIT — free to use, fork, and extend.
Built for AQX Sports Analytics Data Bowl 3.0 · Sport: Football (soccer)