AI prediction · locked November 4, 2026 7:09 pm
Model pick 2–1
Result after 90 minutes: 4–1. The model tipped 2–1 and scored 1 point.
Most likely scores
Why
The model expects Porto to score 1.88 goals: league home average 2.33 × Porto overall attack 0.75 × Napoli overall defence 1.07.
It expects Napoli to score 1.51 goals: league away average 1.59 × Napoli overall attack 0.94 × Porto overall defence 1.01.
Thin data: there are too few home/away games yet, so this uses overall form instead – 3 games for Porto and 3 for Napoli in this competition, plus 63 finished matches overall. Home advantage comes only from the league averages. Treat this prediction with extra caution.
Attack above 1.00 means scoring more than the league average; defence above 1.00 means conceding more than average (weaker).
Most likely outcome: Porto (47%). This is an estimate, not a certainty.
Form & stats this competition season
| Porto | Napoli | |
|---|---|---|
| Table position | #26 · 3 pts | #27 · 3 pts |
| Last 5 (newest first) | WLLL | LWLL |
| Home W-D-L (goals) | 1-0-2 (4:4) | 1-0-1 (4:4) |
| Away W-D-L (goals) | 0-0-1 (2:3) | 0-0-2 (2:7) |
| Goals per game at home (for/against) | 1.33 / 1.33 | 2.00 / 2.00 |
| Goals per game away (for/against) | 2.00 / 3.00 | 1.00 / 3.50 |
| xG | n/a | n/a |
xG is not available from the current data source (football-data.org). Competition averages: 2.32 home and 1.72 away goals per match (72 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.