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Methodology

How we analyse football matches and generate data-driven predictions

Our predictions are model-driven statistical forecasts built from recent competitive matches. They are intended as analytical insights, not advice.

Data Source Tiers

Not all fixtures have the same type of recent historical data available. To reflect this, each match is assigned a data source tier, which describes how the recent match data was gathered for the underlying analytics.

Competition

Comp

Fixtures where both teams have sufficient recent data from the same competition and match context.

  • Based on several recent matches from the same competition
  • Uses context-specific data (home form for the home team, away form for the away team)
  • Reflects the most competition-specific dataset

Cross-Competition

Cross

Fixtures where competition-specific data is supplemented with additional relevant matches.

  • Uses competition data where available
  • Supplements with cross-competition matches when needed
  • Designed to maintain a balanced sample of recent matches

Wide Sample

Wide

Fixtures where limited recent data exists in comparable competitions.

  • Uses a broader set of recent matches across competitions
  • Provides useful context when competition-specific samples are small
  • Ensures analytics can still be calculated for all fixtures

How Data Source Tiers Are Determined

For every fixture, the system evaluates how much recent data exists for each team in the same competition and match context as the upcoming game.

  • Home team → recent home matches
  • Away team → recent away matches
  • Priority is given to recent competitive fixtures
  • Friendly matches and outdated data are excluded

The tier is determined by the least available context-specific data between the two teams.

Confidence Bands

Each published prediction is placed in a confidence bandbased on the model's probability for that market.

High

Highest model probability band for that market. Exact cutoffs differ by market (full-time vs first-half overs).

Medium

Mid model probability band for that market.

Low

Lower model probability band still above the publish threshold.

Predictions below the publish threshold are not shown. Dashboard accuracy for confidence bands uses only these three groups.

Prediction Types

Over 2.5 Goals

Predicts the match to produce 3 or more goals.

Used when both teams show strong attacking profiles and goal-heavy tendencies.

Over 1.5 Goals

Predicts the match to reach 2 or more goals.

A more conservative full-time prediction.

Over 1.5 Goals (Auto)

Included automatically for matches that already qualify for Over 2.5.

This ensures filtering captures all relevant games. Accuracy is always measured against the primary prediction, not the auto variant.

1H Over 1.5 Goals

Predicts 2 or more goals in the first half.

Based on rapid-start teams and strong early scoring patterns.

1H Over 0.5 Goals

Predicts at least 1 first-half goal.

A more conservative first-half prediction.

1H Over 0.5 Goals (Auto)

Included automatically for matches that already qualify for 1H Over 1.5 Goals.

This ensures filtering captures all relevant games. Accuracy is always measured against the primary prediction, not the auto variant.

How We Analyse Matches

Our analysis focuses on recent form, matchup dynamics, and scoring patterns, using a large set of competition-relevant statistics.

Data Inputs

  • Only recent competitive matches
  • Home/away context to match the upcoming fixture
  • Goals scored and conceded
  • First-half performance trends
  • Clean sheets, shutouts, and goalless periods
  • General attacking and defensive consistency

Market Calibration

Bookmaker odds are collected for research. They are not shown per fixture and are not used to rank or filter matches.

On settled fixtures, Pro compares each confidence band's hit rate with market-implied probability after removing overround — an aggregate dashboard view, not a fixture-level score.

Transparency, Not Guarantees

We don't promise results.

We promise clarity, consistency, and honest data-driven analysis so you can make informed decisions.