Football Poisson Calculator

xG-Based Match Probability & Fair Odds Engine

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INPUT EXPECTED GOALS (XG)
Advanced Options
Model uses an enhanced Poisson for football: slightly higher draw probability and favorite outcomes.
PREDICTION SNAPSHOT
Home Win
33.76%
Fair Odds 2.96
Draw
27.25%
Fair Odds 3.67
Away Win
38.99%
Fair Odds 2.57
Most Likely Score
1 - 1
Probability 12.2% Fair Odds 8.19

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 2.96 —
Draw 3.67 —
Away Win 2.57 —
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 12.2% 8.19
2 0-1 9.32% 10.74
3 1-0 8.72% 11.47
4 1-2 8.54% 11.71
5 2-1 7.99% 12.51
6 0-0 6.65% 15.03
7 0-2 6.52% 15.34
8 2-0 5.71% 17.52
9 2-2 5.59% 17.87
10 1-3 3.99% 25.09
SCORE MATRIX Home Goals ↓ · Away Goals →
0 1 2 3 4 5
0
6.65%
15.03
9.32%
10.74
6.52%
15.34
3.04%
32.86
1.06%
93.9
0.3%
335.35
1
8.72%
11.47
12.2%
8.19
8.54%
11.71
3.99%
25.09
1.4%
71.67
0.39%
255.95
2
5.71%
17.52
7.99%
12.51
5.59%
17.87
2.61%
38.3
0.91%
109.42
0.26%
390.78
3
2.49%
40.11
3.49%
28.65
2.44%
40.93
1.14%
87.71
0.4%
250.63
0.11%
895.26
4
0.82%
122.47
1.14%
87.49
0.8%
124.98
0.37%
267.81
0.13%
765.11
0.04%
2732.24
5
0.21%
467.51
0.3%
333.89
0.21%
477.1
0.1%
1022.49
0.03%
2923.98
0.01%
10416.67
Any other score (6+ goals either side) 0.55% · Fair: 181.52
INDIVIDUAL TEAM TOTAL GOALS
Home Team
Over Under
0.5 73.02% 26.98%
1.5 37.67% 62.33%
2.5 14.52% 85.48%
3.5 4.41% 95.59%
4.5 1.1% 98.9%
Away Team
Over Under
0.5 75.34% 24.66%
1.5 40.82% 59.18%
2.5 16.65% 83.35%
3.5 5.37% 94.63%
4.5 1.43% 98.57%
TOTAL GOALS IN MATCH
Goals Prob Odds
0 6.65% 15.03
1 18.03% 5.55
2 24.43% 4.09
3 22.07% 4.53
4 14.95% 6.69
5+ 13.86% 7.22
Over 2.5 50.88% Under 2.5 49.12%
KEY MARKET PROBABILITIES
1X2
Home Win 33.76%
Draw 27.25%
Away Win 38.99%
Over / Under 2.5
Over 2.5 50.88%
Under 2.5 49.12%
Both to score (BTTS)
Yes 55.01%
No 44.99%
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 5.4% 18.53 10.11% 9.9 84.5% 1.18
-1.5 15.5% 6.45 — 84.5% 1.18
-1.0 15.5% 6.45 19.56% 5.11 64.94% 1.54
-0.5 35.06% 2.85 — 64.94% 1.54
0 (PK) 35.06% 2.85 25.73% 3.89 39.2% 2.55
+0.5 60.8% 1.64 — 39.2% 2.55
+1.0 60.8% 1.64 20.91% 4.78 18.3% 5.47
+1.5 81.7% 1.22 — 18.3% 5.47
+2.0 81.7% 1.22 11.54% 8.66 6.76% 14.8

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.