AI prediction · locked November 5, 2026 2:36 pm
Model pick 3–1
Result after 90 minutes: 5–2. The model tipped 3–1 and scored 1 point.
Most likely scores
Why
The model expects RB Leipzig to score 3.48 goals: league home average 2.12 × RB Leipzig home attack 1.50 × Augsburg away defence 1.10.
It expects Augsburg to score 1.10 goals: league away average 1.38 × Augsburg away attack 1.44 × RB Leipzig home defence 0.56.
Based on 4 home games for RB Leipzig, 3 away games for Augsburg 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: RB Leipzig (81%). This is an estimate, not a certainty.
Form & stats this competition season
| RB Leipzig | Augsburg | |
|---|---|---|
| Table position | #4 · 18 pts | #14 · 9 pts |
| Last 5 (newest first) | WWWLW | LLDLD |
| Home W-D-L (goals) | 5-0-0 (23:2) | 1-3-1 (9:7) |
| Away W-D-L (goals) | 1-0-3 (4:11) | 1-0-3 (11:13) |
| Goals per game at home (for/against) | 4.60 / 0.40 | 1.80 / 1.40 |
| Goals per game away (for/against) | 1.00 / 2.75 | 2.75 / 3.25 |
| 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.