- Home: scored 1 or more goals in 77.0%, 2 or more in 43.6% and 3 or more in 19.3%.
- Away: scored 1 or more goals in 68.6%, 2 or more in 33.5% and 3 or more in 12.6%.
- Poisson: with average goals it reproduces team-goal frequencies within about 1 point; see the table.
What is a team goals over/under?
It is a market that looks at a single team.
Home over 0.5 means the home team scores at least one goal.
Over 1.5 needs two or more, and over 2.5 needs three or more.
What the opponent does does not matter.
Only the goals of the chosen team count.
That is why it differs from the total goals over/under 2.5 and from both teams to score.
How often does a home team score?
This is the base for any estimate.
Look at the frequency of each league, not the overall average.
| League (home team) | 1 or more goals | 2 or more goals | 3 or more goals |
|---|---|---|---|
| Eredivisie | 80.6% | 50.4% | 26.3% |
| Bundesliga | 80.6% | 50.7% | 26.4% |
| 2. Bundesliga | 80.3% | 48.8% | 22.9% |
| Süper Lig | 78.7% | 46.8% | 21.7% |
| Pro League (Belgium) | 77.8% | 46.5% | 21.3% |
| Premier League | 77.5% | 46.8% | 21.6% |
| Premiership (Scotland) | 77.3% | 45.7% | 20.5% |
| Ligue 1 | 77.3% | 44.0% | 19.9% |
| LaLiga | 77.6% | 42.3% | 18.2% |
| Primeira Liga | 74.9% | 41.2% | 18.3% |
| Serie A | 76.0% | 42.5% | 17.3% |
| Championship | 76.5% | 41.7% | 17.0% |
| Super League (Greece) | 72.4% | 40.4% | 18.2% |
| Serie B | 77.5% | 40.0% | 15.7% |
| LaLiga 2 | 75.6% | 38.5% | 14.5% |
| Ligue 2 | 71.8% | 37.0% | 14.6% |
| Total | 77.0% | 43.6% | 19.3% |
Source: football-data.co.uk, seasons 2018/19, 2019/20, 2021/22 through 2025/26, plus the matches played so far in 2026/27.
Sample: 39,920 matches from 16 European leagues.
Leagues: top two divisions of England, Spain, Italy, Germany and France, plus the Netherlands, Portugal, Belgium, Greece, Scotland and Turkey.
Our own calculation.
Sorted from highest to lowest average goals for the home team.
The home team scores at least once between 71.8% and 80.6% of the time, depending on the league.
With 3 or more goals, the gap between leagues is bigger.
A home over 2.5 in an attacking league is nothing like one in a tight league.
And how often does an away team score?
| League (away team) | 1 or more goals | 2 or more goals | 3 or more goals |
|---|---|---|---|
| Eredivisie | 71.5% | 38.8% | 17.3% |
| Bundesliga | 73.9% | 39.8% | 18.8% |
| 2. Bundesliga | 72.2% | 38.1% | 15.7% |
| Süper Lig | 70.0% | 34.2% | 13.8% |
| Pro League (Belgium) | 71.1% | 36.0% | 14.0% |
| Premier League | 71.1% | 37.0% | 14.5% |
| Premiership (Scotland) | 66.1% | 33.6% | 13.0% |
| Ligue 1 | 69.2% | 34.0% | 13.2% |
| LaLiga | 66.7% | 30.8% | 9.9% |
| Primeira Liga | 67.5% | 33.4% | 12.2% |
| Serie A | 70.4% | 35.9% | 13.1% |
| Championship | 68.7% | 31.9% | 10.5% |
| Super League (Greece) | 63.6% | 30.7% | 10.1% |
| Serie B | 68.1% | 30.2% | 9.7% |
| LaLiga 2 | 63.2% | 26.3% | 8.5% |
| Ligue 2 | 64.9% | 29.8% | 10.9% |
| Total | 68.6% | 33.5% | 12.6% |
Source: football-data.co.uk, seasons 2018/19, 2019/20, 2021/22 through 2025/26, plus the matches played so far in 2026/27.
Sample: 39,920 matches from 16 European leagues.
Leagues: top two divisions of England, Spain, Italy, Germany and France, plus the Netherlands, Portugal, Belgium, Greece, Scotland and Turkey.
Our own calculation.
Same order as the home table.
The away side scored 1.20 goals on average and the home side 1.50.
That gap explains why the home team beats the away team in every row.
But do not back the home side just for being at home: that is already in the price.
How it connects with over/under 2.5 and both teams to score
The three markets look at the same thing from different angles.
If both teams score, 3 or more goals are more likely.
When both scored, there was an over 2.5 in 76.8% of matches.
When one of them stayed at zero, only in 22.3%.
| Match outcome | Frequency |
|---|---|
| Both teams to score | 52.8% |
| Over 2.5 total goals | 51.1% |
| Over 2.5 if both scored | 76.8% |
| Over 2.5 if one stayed at zero | 22.3% |
| Both scored if there was an over 2.5 | 79.4% |
Source: football-data.co.uk, seasons 2018/19, 2019/20, 2021/22 through 2025/26, plus the matches played so far in 2026/27.
Sample: 39,920 matches from 16 European leagues.
Leagues: top two divisions of England, Spain, Italy, Germany and France, plus the Netherlands, Portugal, Belgium, Greece, Scotland and Turkey.
Our own calculation.
That is why it pays to look at the three markets together.
An over 1.5 for each team is very close to a match with both teams scoring and 3 or more goals.
Do not bet it three times: it is almost the same bet.
How to estimate the team over/under with Poisson
Poisson is a formula that gives the probability of a team scoring 0, 1, 2 or more goals.
It needs just one input: the team's expected goals in that match.
With that number, it calculates every line.
Numerical example, calculated with code
All the numbers in this section are an example.
We checked every calculation with a program, not by hand.
Suppose a home team with attack 1.15 and an away team with defense 1.04 (example values).
With the home average of 1.50, the home side expects 1.8 goals.
For the away side, we use 1.1 expected goals.
| Goals | Home (λ = 1.8) | Away (λ = 1.1) |
|---|---|---|
| 0 | 16.5% | 33.3% |
| 1 | 29.8% | 36.6% |
| 2 | 26.8% | 20.1% |
| 3 | 16.1% | 7.4% |
| 4 or more | 10.9% | 2.6% |
| Market (example) | Probability | Fair odds |
|---|---|---|
| Home over 0.5 | 83.5% | 1.20 |
| Home over 1.5 | 53.7% | 1.86 |
| Away over 0.5 | 66.7% | 1.50 |
| Away over 1.5 | 30.1% | 3.32 |
| Match over 2.5 | 55.4% | 1.80 |
| Both teams to score | 55.7% | 1.80 |
Fair odds are 1 divided by the probability.
If a sportsbook pays more than that, there is value according to this model.
If it pays less, there is not.
Remember the model is simple.
Check your calculation with the expected value calculator and convert with the odds converter.
Does Poisson get it right? Verification against real data
We tested the simplest possible model.
We used only each league's average goals, with no attack or defense for each team.
Then we compared with what really happened.
| Measure (all leagues) | Poisson | Real | Difference |
|---|---|---|---|
| Home 1 or more goals | 77.8% | 77.0% | +0.8 pp |
| Home 2 or more | 44.4% | 43.6% | +0.7 pp |
| Home 3 or more | 19.2% | 19.3% | 0.0 pp |
| Away 1 or more | 69.9% | 68.6% | +1.3 pp |
| Away 2 or more | 33.8% | 33.5% | +0.3 pp |
| Away 3 or more | 12.1% | 12.6% | −0.5 pp |
| Match over 2.5 | 50.8% | 51.1% | −0.3 pp |
| Both teams to score | 54.4% | 52.8% | +1.5 pp |
Source: football-data.co.uk, seasons 2018/19, 2019/20, 2021/22 through 2025/26, plus the matches played so far in 2026/27.
Sample: 39,920 matches from 16 European leagues.
Leagues: top two divisions of England, Spain, Italy, Germany and France, plus the Netherlands, Portugal, Belgium, Greece, Scotland and Turkey.
Our own calculation.
pp: percentage points.
Poisson got team goals right within a little over one point.
It missed more on both teams to score: it overestimated it by about 1.5 points.
That hints that the two teams' goals are not completely independent.
That is why it pays to treat that market with more care.
Careful: what this model does not measure
- Absences: without the top scorer, the average drops.
- Style: teams that defend a lead score less.
- Sample: with few matches, attacking strength is noise.
- Context: a final, the weather or the pitch change the expectation.
- Price: if the real odds already include all that, there is no extra value.
A high frequency is not a bet with value.
That a team scores often is already in the price.
Value appears only if your estimate is better than the sportsbook's.
Prompt to estimate a team over/under
Act as a statistical football analyst. Match: [HOME] vs [AWAY], league [LEAGUE]. Data I am giving you: goals for and against of each team in their last [N] matches, and the league's average goals [HOME AVERAGE] and [AWAY AVERAGE]. Calculate: attacking and defensive strength of each team, expected goals of each, and with Poisson the probability of 0, 1, 2, 3 or more goals. Then compare it with the odds [ODDS] of the market [team over/under]. Show me every calculation. Do not invent data.
Always ask it to show the calculations.
And check them with a calculator before using them.
More prompt ideas in the best betting markets with AI.
What to read next
For markets by half, continue with first-half betting.
To get the best odds, see how to use an odds comparison site and line shopping.
The football basics are in football statistics for betting and in AI for football betting.
To build your own model, read build your own AI and the comparison of AIs.
The full picture is in the complete guide.
And you can see our picks in the public record and the Betting Journal.
Responsible gambling: betting is for adults over 18 only.
Only bet money you can afford to lose.
Frequently asked questions
What is a team goals over/under?
It is a bet on how many goals one particular team scores.
For example, home over 1.5 means the home team scores 2 or more.
It does not matter how many the opponent scores.
How often does a home team score 2 or more goals?
In our data, 43.6%.
It is our own calculation on 39,920 matches from 16 European leagues.
It varies a lot by league and by team.
And an away team?
The away team scored 2 or more goals in 33.5% of matches.
It is less frequent than for the home team (43.6%), because the away side's average goals are lower.
Is Poisson useful for estimating team goals?
It works as a starting point.
With the league's average goals, Poisson estimated team-goal frequencies within a little over 1 point.
But it overestimated both teams to score (54.4% against 52.8% real).
How does it relate to over/under 2.5 and both teams to score?
They are connected.
When both teams scored, there were 3 or more goals in 76.8% of matches.
When one of them did not score, only in 22.3%.
Is the league frequency enough?
No.
It is a starting point.
You have to adjust for the team's attacking strength, the opponent's defense and absences.
A simple Poisson model lets you do it with numbers.