Win Probability Model
Real-time estimates of each team's likelihood of winning based on current game state. Updated pitch-by-pitch (baseball) or play-by-play (football/basketball).
Definition
Win probability is the estimated chance a team wins given the current score, inning/quarter/period, base-out state (baseball), down-and-distance (football), or shot clock situation (basketball). It's expressed as a percentage from 0 to 100 for each team, always summing to 100%.
Inputs
Current lead/deficit between teams
Inning + outs (baseball), quarter + time remaining (football/basketball)
Baseball only: runners on base + out count creates 24 distinct leverage states
Historical home-field advantage factor by sport and venue
Team quality estimates from season record, RPI, or power ratings
Assumptions
- •Teams play at their season-average level for the remainder of the game. No in-game adjustments for pitching changes, injuries, or momentum shifts are modeled yet.
- •Historical leverage data (base-out × inning × score) comes from MLB play-by-play archives. College baseball leverage is extrapolated from pro data with conference strength adjustments.
- •Home-field advantage is static per sport (baseball: ~54%, football: ~57%, basketball: ~60%). Venue-specific effects are not yet incorporated.
Validation
Calibration target: when the model says a team has a 70% win probability, that team should win approximately 70% of the time across a large sample.
Failure Modes
Blowouts in early innings — the model can overstate comeback probability when the score differential is extreme but the game is young.
Pitching changes — a dominant reliever entering changes the true WP significantly, but the model doesn't yet account for individual pitcher quality.
Weather delays — suspended games or rain-shortened games break the inning-based framework.
Small-sample sports — college baseball has fewer plate appearances per game than MLB, making leverage tables noisier.
Version History
Initial methodology documentation. Model framework established. Calibration pending against college baseball dataset.
Austin Humphrey. (2026, February 17). BSI Win Probability Model. Blaze Sports Intel. https://blazesportsintel.com/models/win-probability