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
31.41%
Fair Odds 3.18
Draw
33.61%
Fair Odds 2.98
Away Win
34.98%
Fair Odds 2.86
Most Likely Score
0 - 0
Probability 15.26% Fair Odds 6.55

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 3.18 —
Draw 2.98 —
Away Win 2.86 —
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 0-0 15.26% 6.55
2 0-1 14.65% 6.83
3 1-0 14.04% 7.12
4 1-1 13.48% 7.42
5 0-2 7.03% 14.22
6 1-2 6.47% 15.46
7 2-0 6.46% 15.49
8 2-1 6.2% 16.13
9 2-2 2.98% 33.61
10 0-3 2.25% 44.44
SCORE MATRIX Home Goals ↓ · Away Goals →
0 1 2 3 4 5
0
15.26%
6.55
14.65%
6.83
7.03%
14.22
2.25%
44.44
0.54%
185.19
0.1%
964.32
1
14.04%
7.12
13.48%
7.42
6.47%
15.46
2.07%
48.31
0.5%
201.29
0.1%
1048.22
2
6.46%
15.49
6.2%
16.13
2.98%
33.61
0.95%
105.02
0.23%
437.64
0.04%
2277.9
3
1.98%
50.5
1.9%
52.6
0.91%
109.59
0.29%
342.47
0.07%
1426.53
0.01%
7407.41
4
0.46%
219.54
0.44%
228.68
0.21%
476.42
0.07%
1488.1
0.02%
6211.18
0.0%
32258.06
5
0.08%
1193.32
0.08%
1242.24
0.04%
2590.67
0.01%
8064.52
0.0%
33333.33
0.0%
166666.67
Any other score (6+ goals either side) 0.09% · Fair: 1157.41
INDIVIDUAL TEAM TOTAL GOALS
Home Team
Over Under
0.5 60.15% 39.85%
1.5 23.48% 76.52%
2.5 6.62% 93.38%
3.5 1.45% 98.55%
4.5 0.26% 99.74%
Away Team
Over Under
0.5 61.71% 38.29%
1.5 24.95% 75.05%
2.5 7.31% 92.69%
3.5 1.66% 98.34%
4.5 0.31% 99.69%
TOTAL GOALS IN MATCH
Goals Prob Odds
0 15.26% 6.55
1 28.69% 3.49
2 26.97% 3.71
3 16.90% 5.92
4 7.94% 12.59
5+ 4.25% 23.54
Over 2.5 29.09% Under 2.5 70.91%
KEY MARKET PROBABILITIES
1X2
Home Win 31.41%
Draw 33.61%
Away Win 34.98%
Over / Under 2.5
Over 2.5 29.09%
Under 2.5 70.91%
Both to score (BTTS)
Yes 37.12%
No 62.88%
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 3.11% 32.11 8.58% 11.65 88.3% 1.13
-1.5 11.7% 8.55 — 88.3% 1.13
-1.0 11.7% 8.55 21.22% 4.71 67.08% 1.49
-0.5 32.92% 3.04 — 67.08% 1.49
0 (PK) 32.92% 3.04 32.02% 3.12 35.06% 2.85
+0.5 64.94% 1.54 — 35.06% 2.85
+1.0 64.94% 1.54 22.14% 4.52 12.92% 7.74
+1.5 87.08% 1.15 — 12.92% 7.74
+2.0 87.08% 1.15 9.34% 10.7 3.58% 27.95

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.