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
43.42%
Fair Odds 2.3
Draw
26.61%
Fair Odds 3.76
Away Win
29.97%
Fair Odds 3.34
Most Likely Score
1 - 1
Probability 11.86% Fair Odds 8.43

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 2.3 —
Draw 3.76 —
Away Win 3.34 —
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 11.86% 8.43
2 1-0 9.49% 10.54
3 2-1 9.08% 11.02
4 0-1 7.75% 12.9
5 1-2 7.42% 13.49
6 2-0 7.26% 13.77
7 0-0 6.2% 16.12
8 2-2 5.67% 17.63
9 0-2 4.85% 20.63
10 3-1 4.63% 21.6
SCORE MATRIX Home Goals ↓ · Away Goals →
0 1 2 3 4 5
0
6.2%
16.12
7.75%
12.9
4.85%
20.63
2.02%
49.52
0.63%
158.45
0.16%
633.71
1
9.49%
10.54
11.86%
8.43
7.42%
13.49
3.09%
32.36
0.97%
103.56
0.24%
414.25
2
7.26%
13.77
9.08%
11.02
5.67%
17.63
2.36%
42.31
0.74%
135.37
0.18%
541.42
3
3.7%
27.0
4.63%
21.6
2.89%
34.56
1.21%
82.95
0.38%
265.46
0.09%
1061.57
4
1.42%
70.6
1.77%
56.48
1.11%
90.37
0.46%
216.87
0.14%
693.96
0.04%
2777.78
5
0.43%
230.73
0.54%
184.57
0.34%
295.33
0.14%
708.72
0.04%
2267.57
0.01%
9090.91
Any other score (6+ goals either side) 0.67% · Fair: 148.77
INDIVIDUAL TEAM TOTAL GOALS
Home Team
Over Under
0.5 78.35% 21.65%
1.5 45.22% 54.78%
2.5 19.87% 80.13%
3.5 6.95% 93.05%
4.5 2.0% 98.0%
Away Team
Over Under
0.5 71.35% 28.65%
1.5 35.54% 64.46%
2.5 13.15% 86.85%
3.5 3.83% 96.17%
4.5 0.91% 99.09%
TOTAL GOALS IN MATCH
Goals Prob Odds
0 6.20% 16.12
1 17.25% 5.80
2 23.97% 4.17
3 22.21% 4.50
4 15.44% 6.48
5+ 14.92% 6.70
Over 2.5 52.58% Under 2.5 47.42%
KEY MARKET PROBABILITIES
1X2
Home Win 43.42%
Draw 26.61%
Away Win 29.97%
Over / Under 2.5
Over 2.5 52.58%
Under 2.5 47.42%
Both to score (BTTS)
Yes 55.9%
No 44.1%
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 8.68% 11.52 13.15% 7.6 78.17% 1.28
-1.5 21.83% 4.58 — 78.17% 1.28
-1.0 21.83% 4.58 21.97% 4.55 56.2% 1.78
-0.5 43.8% 2.28 — 56.2% 1.78
0 (PK) 43.8% 2.28 25.1% 3.98 31.1% 3.22
+0.5 68.9% 1.45 — 31.1% 3.22
+1.0 68.9% 1.45 17.95% 5.57 13.15% 7.6
+1.5 86.85% 1.15 — 13.15% 7.6
+2.0 86.85% 1.15 8.78% 11.39 4.37% 22.87

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.