vs
Based on our model, this is what we expect for this match: a standard officiating night, and the exposure leans evenly between both sides.
22DataPitch 36% · Market 27%
4DataPitch 46% · Market 40%
Every row worth a look, priced in words. Pick one or several, then Share renders the card.
4DataPitch 46% · Market 40%
5DataPitch 38% · Market 33%
22DataPitch 36% · Market 27%
22DataPitch 21% · Market 11%
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Expected XI. Attack at the top, keeper at the bottom.
Match-level, not per player. Set what you think, then Simulate.
Simulate re-prices every row above against what you set, in your browser, and tells you which ones moved and by how much.
How strict you think the referee will be
Our card model already has his record in it. This is your view on top of ours. Touches: cards, fouls and fouls drawn.
Who has the ball and who is chasing it
The side chasing shoots more and gets fouled more; the side in front tackles more. Touches: every market.
We lean on the market where it is sharp
Off means our own numbers stand alone: the cards line stops setting the level and the goalscorer price stops lifting shots. Touches: cards, shots and shots on target.
Pick an attacker and the defender on him
We apply our matchup pivot to that pair and show you every row it moves. Touches: fouls, fouls drawn and cards for those two.
This re-prices the rows we already evaluated. It does not re-decide which rows to evaluate or re-run the match itself.
Referee deck not live for this fixture.
Price = the latest market price we hold (book if any, else exchange). Gap is our simulated probability minus the price's own implied one, in percentage points, never printed as a price of ours. Both percentages are on every row.
