MatchPulse
Transparent · Independently Backtested

Model Accuracy

Every prediction we make is testable. Here is how our 7 models actually performed — measured honestly, with no look-ahead bias, across thousands of real matches.

4,857 predictions evaluated point-in-time: each match was predicted using only data available before kickoff.

Over 2.5 Goals — Combined model

When we say 54%, it happens ~54% of the time

Predicted probabilityActual rate
4,857 predsBrier 0.250

Match Result (1X2) — Elo model

Our best-calibrated outcome model

Predicted probabilityActual rate
14,571 predsBrier 0.201
How to read these charts: The dashed line is perfect calibration. Each dot is a group of predictions — its position shows what we predicted (horizontal) versus what actually happened (vertical). Dots on the line mean our probabilities are honest. Dot size reflects sample size.

Calibration by model & market

ModelOver 1.5Over 2.5Over 3.51X2Exact Score
Combined ⭐
77.5%
said 75.5%
53.4%
said 52.3%
31.2%
said 31.5%
33.3%
said 33.4%
12.3%
said 12.0%
Elo
77.5%
said 75.9%
53.4%
said 52.7%
31.2%
said 31.3%
33.3%
said 33.3%
12.8%
said 11.9%
Poisson
77.5%
said 75.9%
53.4%
said 52.7%
31.2%
said 31.3%
33.3%
said 33.3%
12.8%
said 11.9%
Dixon-Coles
77.5%
said 77.4%
53.4%
said 52.7%
31.2%
said 31.3%
33.3%
said 33.3%
12.2%
said 12.9%
Weighted Form
77.5%
said 76.2%
53.4%
said 52.8%
31.2%
said 31.3%
33.3%
said 33.3%
12.4%
said 11.7%
Normalized
77.5%
said 72.3%
53.4%
said 49.9%
31.2%
said 30.4%
33.3%
said 33.3%
10.1%
said 14.2%
Shots
77.5%
said 74.8%
53.4%
said 52.7%
31.2%
said 32.7%
33.3%
said 33.3%
11.1%
said 12.6%
Large number = how often it actually happened. Below = what the model predicted on average. Green = calibrated within 2 points.

1X2 — how often the predicted winner was correct

Elo
50.6%
Combined
50.4%
Weighted Form
49.9%
Poisson
49.3%
Dixon-Coles
49.2%
Normalized
48.6%
Shots
48.4%
Share of matches where the model's most likely outcome (home/draw/away) was the actual result.

How we test

We replay history match by match in chronological order. For each fixture, the models are fed only the data that existed before kickoff — rolling team form, home/away goal rates, shots and Elo ratings. The prediction is recorded, then compared to the real result. This eliminates look-ahead bias, the most common flaw in published accuracy claims. BTTS is excluded while we improve its calibration.

Last updated: 3 Jun 2026