How Bollr Calculates Historical Hit Rates

A "hit rate" on Bollr is the empirical historical frequency of an event occurring over an exact, audited sample of completed matches:

Unlike prediction engines that use proprietary black-box ML weights to generate "confidence scores", Bollr exposes the exact numerator (hits) and denominator (sample size). For example, 7/10 (70%) means the line hit in exactly 7 of the team's last 10 official matches in that competition.

Different questions require different sample horizons. Bollr divides every market across four distinct analytical windows:

Teams on Bollr are ranked using a modified Elo algorithm calibrated for football dynamics:

• Goal Margin Scaling: Blowout victories (e.g. 4-0) award higher rating shifts than narrow 1-0 penalty wins.
• Home Field Advantage: Ratings use a fixed home advantage of 60 Elo points.
• K-Factor: Every match moves ratings by a K of 20 (doubled for a short window after promotion or relegation), scaled by the square root of the goal margin, so an upset against the expected result shifts ratings more than an expected win.

Not all football competitions behave equally. Leagues whose matches produce a steady number of goals rank high; leagues with widely varying scorelines rank low. The index is a percentile rank among leagues based on goal-count consistency, not a percentage of outcomes.

Bollr computes this index across all 1,000+ tracked leagues so users can gauge competition volatility before analyzing individual fixture markets.