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
60.8%
Fair Odds 1.64
Draw
21.1%
Fair Odds 4.74
Away Win
18.11%
Fair Odds 5.52
Most Likely Score
2 - 1
Probability 9.77% Fair Odds 10.24

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 1.64 —
Draw 4.74 —
Away Win 5.52 —
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 2-1 9.77% 10.24
2 1-1 8.84% 11.31
3 2-0 8.57% 11.67
4 1-0 7.75% 12.9
5 3-1 7.2% 13.9
6 3-0 6.31% 15.84
7 2-2 5.57% 17.96
8 1-2 5.04% 19.85
9 3-2 4.1% 24.38
10 0-1 4.0% 25.0
SCORE MATRIX Home Goals ↓ · Away Goals →
0 1 2 3 4 5
0
3.51%
28.5
4.0%
25.0
2.28%
43.86
0.87%
115.43
0.25%
405.02
0.06%
1776.2
1
7.75%
12.9
8.84%
11.31
5.04%
19.85
1.91%
52.23
0.55%
183.25
0.12%
803.86
2
8.57%
11.67
9.77%
10.24
5.57%
17.96
2.12%
47.27
0.6%
165.84
0.14%
727.27
3
6.31%
15.84
7.2%
13.9
4.1%
24.38
1.56%
64.16
0.44%
225.12
0.1%
987.17
4
3.49%
28.68
3.98%
25.15
2.27%
44.13
0.86%
116.13
0.25%
407.5
0.06%
1785.71
5
1.54%
64.88
1.76%
56.91
1.0%
99.84
0.38%
262.74
0.11%
921.66
0.02%
4048.58
Any other score (6+ goals either side) 2.65% · Fair: 37.74
INDIVIDUAL TEAM TOTAL GOALS
Home Team
Over Under
0.5 89.03% 10.97%
1.5 64.78% 35.21%
2.5 37.99% 62.0%
3.5 18.26% 81.74%
4.5 7.36% 92.64%
Away Team
Over Under
0.5 68.02% 31.98%
1.5 31.56% 68.44%
2.5 10.78% 89.22%
3.5 2.88% 97.12%
4.5 0.63% 99.37%
TOTAL GOALS IN MATCH
Goals Prob Odds
0 3.51% 28.50
1 11.75% 8.51
2 19.69% 5.08
3 21.98% 4.55
4 18.41% 5.43
5+ 24.66% 4.06
Over 2.5 65.05% Under 2.5 34.95%
KEY MARKET PROBABILITIES
1X2
Home Win 60.80%
Draw 21.10%
Away Win 18.11%
Over / Under 2.5
Over 2.5 65.05%
Under 2.5 34.95%
Both to score (BTTS)
Yes 60.56%
No 39.44%
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 20.56% 4.86 18.45% 5.42 60.99% 1.64
-1.5 39.01% 2.56 — 60.99% 1.64
-1.0 39.01% 2.56 22.6% 4.42 38.39% 2.6
-0.5 61.61% 1.62 — 38.39% 2.6
0 (PK) 61.61% 1.62 19.75% 5.06 18.64% 5.36
+0.5 81.36% 1.23 — 18.64% 5.36
+1.0 81.36% 1.23 11.66% 8.58 6.98% 14.32
+1.5 93.01% 1.08 — 6.98% 14.32
+2.0 93.01% 1.08 4.91% 20.37 2.07% 48.22

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.