How Footylab H2H Value Score Works

Each team gets a score from the H2H stat categories shown on the match page.

Every category has a weight, and Footylab combines the available category scores with availability, venue and injury context where that data exists.

That means missing categories do not break the page. The score is built from the evidence that is present, then adjusted only by visible context.

Once both teams have an overall stats score, Footylab turns the score gap into a stats-implied win chance.

The current model uses a calibrated logistic curve and bucket context from completed match snapshots, with sensible caps so it does not pretend any side is certain.

This keeps the comparison transparent: the question becomes how much chance the stats are assigning to each side before price is considered.

Footylab then estimates the market's view from the bookmaker odds board.

For H2H, the implied probabilities from the two sides are normalised into a market chance split, which strips out the two-way bookmaker margin before comparison.

This creates an apples-to-apples comparison between the stats view and the bookmaker view.

The H2H overall value score is the gap between the stats-implied chance and the market-implied chance.

If the stats share is higher than the market share, the score moves positive and the offer looks more like value.

If the stats share is lower than the market share, the score moves negative and the offer looks more like a ripoff.