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
49.43%
Fair Odds 2.02
Draw
23.4%
Fair Odds 4.27
Away Win
27.17%
Fair Odds 3.68
Most Likely Score
1 - 1
Probability 9.52% Fair Odds 10.5

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 2.02 —
Draw 4.27 —
Away Win 3.68 —
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 9.52% 10.5
2 2-1 9.28% 10.77
3 1-2 6.76% 14.79
4 1-0 6.71% 14.91
5 2-2 6.59% 15.17
6 2-0 6.54% 15.29
7 3-1 6.03% 16.57
8 0-1 4.88% 20.48
9 3-2 4.28% 23.34
10 3-0 4.25% 23.53
SCORE MATRIX Home Goals ↓ · Away Goals →
0 1 2 3 4 5
0
3.44%
29.08
4.88%
20.48
3.47%
28.84
1.64%
60.93
0.58%
171.64
0.17%
604.23
1
6.71%
14.91
9.52%
10.5
6.76%
14.79
3.2%
31.25
1.14%
88.02
0.32%
309.98
2
6.54%
15.29
9.28%
10.77
6.59%
15.17
3.12%
32.05
1.11%
90.28
0.31%
317.86
3
4.25%
23.53
6.03%
16.57
4.28%
23.34
2.03%
49.31
0.72%
138.89
0.2%
489.0
4
2.07%
48.27
2.94%
33.99
2.09%
47.87
0.99%
101.14
0.35%
284.9
0.1%
1003.01
5
0.81%
123.76
1.15%
87.15
0.81%
122.76
0.39%
259.34
0.14%
730.46
0.04%
2570.69
Any other score (6+ goals either side) 1.82% · Fair: 54.95
INDIVIDUAL TEAM TOTAL GOALS
Home Team
Over Under
0.5 85.77% 14.23%
1.5 58.03% 41.97%
2.5 30.98% 69.02%
3.5 13.4% 86.6%
4.5 4.82% 95.17%
Away Team
Over Under
0.5 75.83% 24.17%
1.5 41.51% 58.49%
2.5 17.14% 82.86%
3.5 5.6% 94.4%
4.5 1.51% 98.49%
TOTAL GOALS IN MATCH
Goals Prob Odds
0 3.44% 29.08
1 11.59% 8.63
2 19.53% 5.12
3 21.94% 4.56
4 18.48% 5.41
5+ 25.03% 4.00
Over 2.5 65.44% Under 2.5 34.56%
KEY MARKET PROBABILITIES
1X2
Home Win 49.43%
Draw 23.40%
Away Win 27.17%
Over / Under 2.5
Over 2.5 65.44%
Under 2.5 34.56%
Both to score (BTTS)
Yes 65.04%
No 34.96%
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 13.45% 7.43 15.1% 6.62 71.45% 1.4
-1.5 28.55% 3.5 — 71.45% 1.4
-1.0 28.55% 3.5 21.41% 4.67 50.04% 2.0
-0.5 49.96% 2.0 — 50.04% 2.0
0 (PK) 49.96% 2.0 21.97% 4.55 28.06% 3.56
+0.5 71.93% 1.39 — 28.06% 3.56
+1.0 71.93% 1.39 15.59% 6.41 12.47% 8.02
+1.5 87.53% 1.14 — 12.47% 8.02
+2.0 87.53% 1.14 8.01% 12.49 4.47% 22.39

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.