Poisson Football Prediction Calculator: xG-Based Score & Match Probability
Poisson distribution calculator for betting
Are you curious about how bookmakers calculate odds? One way is to use the Poisson distribution. To apply it, we need to determine the expected score of the match (xGscore), that's where our service is specialized in.
The model is based on the Poisson distribution, a statistical method commonly used to model the probability of events occurring within a fixed interval. You can learn more about the Poisson distribution on Wikipedia.
By entering expected number of goals for home and away team, you will get familiar odds line, in addition you can also represent these numbers as a probability.
Note that we use an improved version of the Poisson distribution algorithm, aimed at football statistics and trends. In this version, probability of match draw is increased, as well as outcomes of the favorite team.
Enter expected goals
Match probability & odds output
| Result | Double Chance | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
Total
|
Over (0.5)
92.42%
|
Under (0.5)
7.58%
|
|
Over (1)
92.42%
|
Under (1)
7.58%
|
|
Over (1.5)
72.87%
|
Under (1.5)
27.13%
|
|
Over (2)
72.87%
|
Under (2)
27.13%
|
|
Over (2.5)
47.65%
|
Under (2.5)
52.35%
|
|
Over (3)
47.65%
|
Under (3)
52.35%
|
|
Over (3.5)
25.97%
|
Under (3.5)
74.03%
|
|
Over (4)
25.97%
|
Under (4)
74.03%
|
|
Over (4.5)
11.98%
|
Under (4.5)
88.02%
|
Handicap
|
Home (-2)
12.7%
|
Away (+2)
70.58%
|
|
Home (-1.5)
29.42%
|
Away (+1.5)
70.58%
|
|
Home (-1)
29.42%
|
Away (+1)
45.7%
|
|
Home (-0.5)
54.3%
|
Away (+0.5)
45.7%
|
|
Home (+0)
54.3%
|
Away (-0)
21.19%
|
|
Home (+0.5)
78.81%
|
Away (-0.5)
21.19%
|
|
Home (+1)
78.81%
|
Away (-1)
7.17%
|
|
Home (+1.5)
92.83%
|
Away (-1.5)
7.17%
|
|
Home (+2)
92.83%
|
Away (-2)
1.86%
|
Both to Score (BTTS)
|
Yes
48.92%
|
No
51.08%
|
Home Individual Total
|
Over (0.5)
80.79%
|
Under (0.5)
19.2%
|
|
Over (1)
80.79%
|
Under (1)
19.2%
|
|
Over (1.5)
49.11%
|
Under (1.5)
50.89%
|
|
Over (2)
49.11%
|
Under (2)
50.89%
|
|
Over (2.5)
22.96%
|
Under (2.5)
77.04%
|
|
Over (3)
22.96%
|
Under (3)
77.04%
|
|
Over (3.5)
8.59%
|
Under (3.5)
91.41%
|
|
Over (4)
8.59%
|
Under (4)
91.41%
|
|
Over (4.5)
2.65%
|
Under (4.5)
97.35%
|
Away Individual Total
|
Over (0.5)
60.54%
|
Under (0.5)
39.46%
|
|
Over (1)
60.54%
|
Under (1)
39.46%
|
|
Over (1.5)
23.85%
|
Under (1.5)
76.15%
|
|
Over (2)
23.85%
|
Under (2)
76.15%
|
|
Over (2.5)
6.79%
|
Under (2.5)
93.21%
|
|
Over (3)
6.79%
|
Under (3)
93.21%
|
|
Over (3.5)
1.5%
|
Under (3.5)
98.5%
|
|
Over (4)
1.5%
|
Under (4)
98.5%
|
|
Over (4.5)
0.27%
|
Under (4.5)
99.73%
|
How This Poisson Calculator Works
This calculator uses the following inputs:
- Home team expected goals (xG)
- Away team expected goals (xG)
Based on these values, it calculates:
- Probability of each possible scoreline
- Win, draw, and loss probabilities
- Over/Under goal probabilities
- Both Teams to Score (BTTS) probabilities
All probabilities are derived using the Poisson probability mass function, which is part of the Poisson distribution model widely used in statistics.
How to Use the Poisson Calculator
- Enter the expected goals (xG) for the home team
- Enter the expected goals (xG) for the away team
- Click "Calculate"
- Review score probabilities and match outcome distributions
This tool is ideal for analysts, bettors, and anyone interested in data-driven football predictions.
Why Poisson Distribution Is Useful for xG-Based Predictions
Using xG instead of historical goals allows predictions to reflect chance quality, not just past results.
Benefits include:
- Reducing randomness caused by finishing variance
- Aligning predictions with underlying performance
- Creating fair odds from statistical probabilities
- Identifying value bets by comparing model odds with bookmakers
This is why Poisson-based models are commonly used in AI football prediction systems.
Limitations of the Poisson Model
While powerful, the Poisson model has limitations:
- Assumes goal events are independent
- Does not account for red cards or game state changes
- Less accurate in very low or very high xG matches
For best results, Poisson models should be combined with team strength adjustments, home advantage, and recent form analysis.
Despite these limitations, the Poisson distribution remains widely used in sports analytics and statistical modeling to estimate scoring probabilities in football matches.
