Football Poisson Calculator

xG-Based Match Probability & Fair Odds Engine

INPUT EXPECTED GOALS (XG)
Advanced Options
Model uses an enhanced Poisson for football: slightly higher draw probability and favorite outcomes.
PREDICTION SNAPSHOT
Home Win
28.05%
Fair Odds 3.56
Draw
24.31%
Fair Odds 4.11
Away Win
47.63%
Fair Odds 2.1
Most Likely Score
1 - 1
Probability 10.27% Fair Odds 9.74

Match odds & output

FAIR ODDS COMPARISON
Market Market Odds Fair Odds ? Model-calculated fair price based on probability. Edge ? Difference between bookmaker odds and model fair odds. Positive edge indicates potential value.
Home Win 3.56 —
Draw 4.11 —
Away Win 2.1 —
Find Value Opportunities

Compare model fair odds with bookmaker prices to spot positive EV bets.

See Value Bets →
Correct Score Probability & Fair Odds
# Correct Score Prob Odds
1 1-1 10.27% 9.74
2 1-2 9.34% 10.7
3 0-1 7.49% 13.35
4 2-1 7.03% 14.22
5 0-2 6.82% 14.67
6 2-2 6.4% 15.63
7 1-3 5.67% 17.64
8 1-0 5.64% 17.73
9 0-3 4.14% 24.17
10 0-0 4.12% 24.29
SCORE MATRIX Home Goals ↓ · Away Goals →
0 1 2 3 4 5
0
4.12%
24.29
7.49%
13.35
6.82%
14.67
4.14%
24.17
1.88%
53.13
0.69%
145.96
1
5.64%
17.73
10.27%
9.74
9.34%
10.7
5.67%
17.64
2.58%
38.78
0.94%
106.54
2
3.86%
25.88
7.03%
14.22
6.4%
15.63
3.88%
25.76
1.77%
56.61
0.64%
155.52
3
1.76%
56.67
3.21%
31.14
2.92%
34.22
1.77%
56.4
0.81%
123.96
0.29%
340.6
4
0.6%
165.48
1.1%
90.92
1.0%
99.91
0.61%
164.69
0.28%
361.93
0.1%
994.04
5
0.17%
603.86
0.3%
331.79
0.27%
364.7
0.17%
600.96
0.08%
1321.0
0.03%
3623.19
Any other score (6+ goals either side) 1.38% · Fair: 72.71
INDIVIDUAL TEAM TOTAL GOALS
Home Team
Over Under
0.5 74.59% 25.41%
1.5 39.78% 60.22%
2.5 15.93% 84.07%
3.5 5.04% 94.96%
4.5 1.31% 98.69%
Away Team
Over Under
0.5 83.8% 16.2%
1.5 54.31% 45.69%
2.5 27.47% 72.53%
3.5 11.19% 88.81%
4.5 3.79% 96.21%
TOTAL GOALS IN MATCH
Goals Prob Odds
0 4.12% 24.29
1 13.13% 7.61
2 20.95% 4.77
3 22.28% 4.49
4 17.76% 5.63
5+ 21.76% 4.60
Over 2.5 61.8% Under 2.5 38.2%
KEY MARKET PROBABILITIES
1X2
Home Win 28.05%
Draw 24.31%
Away Win 47.63%
Over / Under 2.5
Over 2.5 61.8%
Under 2.5 38.2%
Both to score (BTTS)
Yes 62.5%
No 37.5%
Asian Handicap Probability ? Probabilities are calculated from the Poisson score model. Push applies to whole-number Asian handicap lines. Home Handicap
Line Home Side Push Away Side
-2.0 4.47% 22.37 8.26% 12.11 87.27% 1.15
-1.5 12.73% 7.85 — 87.27% 1.15
-1.0 12.73% 7.85 16.28% 6.14 70.98% 1.41
-0.5 29.02% 3.45 — 70.98% 1.41
0 (PK) 29.02% 3.45 22.86% 4.37 48.12% 2.08
+0.5 51.88% 1.93 — 48.12% 2.08
+1.0 51.88% 1.93 21.63% 4.62 26.49% 3.78
+1.5 73.51% 1.36 — 26.49% 3.78
+2.0 73.51% 1.36 14.58% 6.86 11.91% 8.4

HOW THE MODEL WORKS

Poisson Distribution
xG Input
Adjustments
Probability Output

All values use the Poisson PMF (Wikipedia, EN).

Limits of the Poisson model

Strong model, with caveats:

  • Independent goals = simplifying assumption
  • Red cards and game state shifts are not in the model
  • Very low/high xG can skew accuracy
Learn more
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How to use the Poisson calculator

  1. Enter the home xG
  2. Enter the away xG
  3. Click Calculate (or use live update)
  4. Review Correct Score probabilities/fair odds plus match outcome distributions

For anyone doing data-led football work.

Why Poisson helps xG models

xG tracks chance quality, not just past goals.

Benefits such as

  • Less noise from finishing luck
  • Matches predictions to underlying xG/quality
  • Fair-odds from clean probabilities
  • Spot model vs book value

Poisson is a staple in football AI / ML stacks.

Frequently asked questions (FAQ)

It models score odds from your xG inputs for the match and markets.

Good for goal counts; pair with xG + form/situational context for best use.

Yes: derive fair prob/odds, compare to books for value-hunting (not a tip service).

Use your best pre-kickoff xG read (team strength, form, opponent) — the tool is agnostic to the source

Yes. Your xG inputs fill the scoreline grid, each line with a probability, same model as 1X2 & BTTS.

Chance each team scores 1+ . Yes/No from the same xG-Poisson as the correct-score view.