Saga
SK Slavia Praha
#34 · 1 pts
1–2
Arsenal FC
#3 · 10 pts
AI prediction
No model prediction was made for this match.
Form & stats this competition season
| Slavia Praha | Arsenal | |
|---|---|---|
| Table position | #34 · 1 pts | #3 · 10 pts |
| Last 5 (newest first) | LDLL | WDWW |
| Home W-D-L (goals) | 0-0-2 (3:5) | 1-0-0 (3:0) |
| Away W-D-L (goals) | 0-1-1 (2:4) | 2-1-0 (5:3) |
| Goals per game at home (for/against) | 1.50 / 2.50 | 3.00 / 0.00 |
| Goals per game away (for/against) | 1.00 / 2.00 | 1.67 / 1.00 |
| 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).
Schedule, form & head-to-head
| Slavia Praha | Arsenal | |
|---|---|---|
| Days since last match | 15.1 | 3.1 |
| Matches in last 14 days | 0 | 2 |
| Next match | +20.9 d: vs Villarreal (CL) | +2.8 d: vs Hull City (PL) |
| Points per game, last 5 (all comps) | 0.33 | 2.60 |
| Clean sheets / failed to score (this comp) | 0 / 1 (4) | 2 / 0 (4) |
| Over 2.5 / both scored (this comp) | 3 / 3 (4) | 3 / 2 (4) |
Slavia Praha – recent matches, all competitions: D @ Fenerbahçe 2–2 · L @ Sabah FK 0–2 · L vs RC Lens 2–3
Arsenal – recent matches, all competitions: W @ Liverpool 1–0 · W vs Everton 2–0 · D @ Bayern 2–2 · W @ Nottingham 1–0 · W vs Lille 3–0 · W vs Leeds United 2–1
Only the six tracked competitions count; domestic cups are not included.
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.