Live cricket scores and win probability dashboard. Built using Django and CricketData API, featuring dynamic polling, key rotation, and a custom WASP algorithm.
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Updated
Apr 18, 2026 - Python
Live cricket scores and win probability dashboard. Built using Django and CricketData API, featuring dynamic polling, key rotation, and a custom WASP algorithm.
Possession-level live win probability model for football using LSTM and GRU on StatsBomb La Liga data, with Poisson goal conversion and proper probabilistic evaluation.
Mechabellum replay and live-match analytics toolkit for data collection, model training, and win probability prediction.
XGBoost win probability model for MLB games, with WPA, Leverage Index, and a benchmark against classical sabermetrics. Live dashboard with pitch-by-pitch game replay.
Interactive NFL fourth-down decision audit using nfl4th and nflverse data. Compare coach decisions with modeled win-probability recommendations, identify conservative and aggressive misses, and explore coach decision fingerprints.
Live win probability, blunder detection, and hidden-team inference for competitive Pokémon Showdown battles — LightGBM on 19k+ ladder replays.
Live per-second round win probability for Counter-Strike 2: spatial control, bomb geometry, calibration, and an out-of-time test. Code, results, and preprint.
NBA win probability, momentum, and turning-point analytics engine.
Steel trading sales, marketing and CRM analytics on a Dynamics 365 export: sales funnel, win-probability model and campaign ROI.
Calibrated live win probabilities for men's T20 run chases from a simple logistic model — Brier 0.1114, 55.4% skill vs base rate, every probability bucket within 5pp of observed win rate. Research code for MIT Sloan SSAC27
NFL in-game win probability model on 225k plays from six seasons of nflfastR. XGBoost, log loss 0.485 / AUC 0.841 on the held-out 2023 season. Python + DuckDB.
Machine learning dashboard for NBA win probability, covering pre-game predictions, live replay, model evaluation, and automated Finals refreshes with Google Cloud.
An AI-powered IPL match win probability prediction system using XGBoost and live match-state features. The project provides separate predictions for first and second innings and exposes the trained models through a FastAPI backend for real-time web predictions.
Multi-level probabilistic framework linking risk-adjusted soccer action values to match-outcome context.
Win-probability curve calibrated to human play — held-out log-loss 0.575 vs Lichess's 0.738, re-validated on 4M off-corpus positions. Static review app runs Stockfish in a Web Worker, no backend.
Calibrated T20 win probability and score projection across five leagues, trained on 5,889 real matches of ball-by-ball data. FastAPI + scikit-learn.
CS2 win-probability & Player Impact (WPA) — end-to-end ML pipeline from parsed pro demos
NFL 4th-down decision audit. Win-probability model + coach scorecards with bootstrap confidence intervals.
Bayesian player ability model for predicting golf win probabilities — time-varying ratings, Bradley-Terry/Glicko, historical PGA Tour data
Open, pre-registered cricket win-probability and WAR from 5.9M deliveries. 22 predictions committed before any model existed; 6 held. A power check retracted the headline.
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