AI prediction · locked November 5, 2026 2:36 pm
Model pick 1–2
Result after 90 minutes: 1–2. The model tipped 1–2 and scored 3 points.
Most likely scores
Why
The model expects Mainz to score 1.41 goals: league home average 2.12 × Mainz home attack 0.87 × Bayern away defence 0.76.
It expects Bayern to score 2.10 goals: league away average 1.38 × Bayern away attack 1.12 × Mainz home defence 1.36.
Based on 4 home games for Mainz, 4 away games for Bayern and 72 finished matches in the competition.
Attack above 1.00 means scoring more than the league average; defence above 1.00 means conceding more than average (weaker).
Most likely outcome: Bayern (53%). This is an estimate, not a certainty.
Form & stats this competition season
| Mainz | Bayern | |
|---|---|---|
| Table position | #12 · 10 pts | #1 · 21 pts |
| Last 5 (newest first) | LLLWL | WDWWD |
| Home W-D-L (goals) | 0-1-4 (7:12) | 3-1-0 (20:4) |
| Away W-D-L (goals) | 3-0-1 (11:7) | 3-2-0 (9:5) |
| Goals per game at home (for/against) | 1.40 / 2.40 | 5.00 / 1.00 |
| Goals per game away (for/against) | 2.75 / 1.75 | 1.80 / 1.00 |
| xG | n/a | n/a |
xG is not available from the current data source (football-data.org). Competition averages: 2.12 home and 1.36 away goals per match (81 finished matches).
Model assumptions & limitations
Assumptions
- Goals for each team follow independent Poisson distributions.
- Expected goals (λ) = league average home/away goals × attack strength × opponent defence strength.
- Strengths use only this competition and season: home form for the home side, away form for the away side. If either team has too few home/away games, overall form (all games) is used instead and this is stated in the explanation.
- Strengths are shrunk towards the league average when few games have been played.
- Predictions are for the score after regular time (90 minutes plus stoppage time).
- The model's tipped score is the one with the highest expected points under the game's scoring system, not necessarily the most likely single score.
Limitations
- No injuries, suspensions, line-ups, transfers, rotation or motivation are considered.
- No xG or shot data is used – the current data source does not provide it.
- Results in other competitions (e.g. domestic league for Champions League teams) are not included.
- Independent Poisson models tend to slightly underestimate draws.
- Probabilities are estimates with considerable uncertainty, not facts or guarantees.