AI prediction · locked November 5, 2026 3:04 pm
Model pick 2–1
Result after 90 minutes: 1–1. The model tipped 2–1 and scored 0 points.
Most likely scores
Why
The model expects Fulham to score 1.72 goals: league home average 1.50 × Fulham home attack 1.00 × Newcastle away defence 1.15.
It expects Newcastle to score 1.60 goals: league away average 1.20 × Newcastle away attack 1.11 × Fulham home defence 1.20.
Based on 4 home games for Fulham, 4 away games for Newcastle and 90 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).
The outcome is close to a toss-up according to the model – treat the pick with extra caution.
Form & stats this competition season
| Fulham | Newcastle | |
|---|---|---|
| Table position | #15 · 10 pts | #12 · 12 pts |
| Last 5 (newest first) | DDWWL | DLWLL |
| Home W-D-L (goals) | 1-2-2 (7:8) | 1-2-2 (6:7) |
| Away W-D-L (goals) | 1-2-2 (3:4) | 2-1-2 (7:9) |
| Goals per game at home (for/against) | 1.40 / 1.60 | 1.20 / 1.40 |
| Goals per game away (for/against) | 0.60 / 0.80 | 1.40 / 1.80 |
| xG | n/a | n/a |
xG is not available from the current data source (football-data.org). Competition averages: 1.53 home and 1.20 away goals per match (100 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.