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Poisson score probability
calculator

Enter each team’s expected goals and get the score grid plus 1X2, Over/Under 2.5 and both-teams-to-score probabilities from a Poisson model. The values you type are not sent to a server.

Short answer

The Poisson score calculator turns two expected-goal values (λ) into the probability of each score and sums them into 1X2, Over/Under 2.5 and BTTS probabilities. For the synthetic λ 1.45 / 1.10 the single most likely score is 1–1 at 12.45%. The model treats goals as independent; it is a calculation tool, not a prediction.

Expected goals

LOCAL CALCULATION

Enter expected goals per match between 0 and 6. A dot or a comma both work.

RESULT
Most likely score—
1 / X / 2—
Over / Under 2.5—
BTTS Yes / No—

Enter two expected-goals values to see the results. The output is a model calculation, not a prediction.

Score grid

HOME ↓ · AWAY →

After you calculate, probabilities for scores from 0 to 5 goals appear here. Scores outside the grid are still counted in the 1X2 and over/under totals.

Home \ Away012345
0——————
1——————
2——————
3——————
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5——————

    Method

    The probability that a team scores k goals is P(k) = e−λ λk / k!. The two teams are assumed independent, so the probability of a score is the product of the two teams’ probabilities. 1X2, Over 2.5 (3+ goals) and BTTS (both teams ≥ 1) are summed from this grid; 0–30 goals are counted for each team.

    What is Over 2.5? ↗ What is BTTS? ↗

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    Try it on real data

    Cortenscore members can review odds pairs in past matches alongside the sample size and the probability implied by the price.

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    FREQUENTLY ASKED
    Why is the Poisson distribution used in football?

    Goals are rare, roughly independent events within a match. The Poisson distribution models counts like these with a single parameter (the average number of goals, λ), which makes it a natural starting model for rough score probabilities.

    Where do I get the expected goals (λ) value?

    You can use the average goals scored and conceded in past matches, xG data or your own model. This tool takes the value from you; it contains no match or team data.

    Are the results real match probabilities?

    No. The model treats the two teams’ goals as independent, so it ignores effects such as teams changing approach with the score or low-scoring draws being slightly more common in practice. The results are the output of a model, not a prediction or advice.

    What do λ 1.45 and 1.10 give?

    Home 45.13%, draw 26.20%, away 28.67%; Over 2.5 46.89%, BTTS Yes 51.06%. The single most likely score is 1–1 at 12.45%.

    Last updated: 28 October 2026 · Responsible: Cortenscore editorial team · Spotted an error? Report a correction. This page is for statistics education; it is not a prediction or betting advice. Example values are synthetic.