Paris Saint-Germain FC vs ES Troyes AC

Paris Saint-Germain FC
#1 · 23 pts
1–0
Full time
Half-time 1–0
ES Troyes AC
#17 · 8 pts

AI prediction · locked November 5, 2026 8:05 pm

PSG 55%Draw 25%Troyes 20%
Over 2.545%
Both score46%
Model goals1.60–0.87

Model pick 1–0

Result after 90 minutes: 1–0. The model tipped 1–0 and scored 3 points.

Most likely scores

1–0 · 13.5%1–1 · 11.8%2–0 · 10.8%2–1 · 9.4%0–0 · 8.4%0–1 · 7.4%

Why

The model expects PSG to score 1.60 goals: league home average 1.70 × PSG home attack 1.07 × Troyes away defence 0.88.

It expects Troyes to score 0.87 goals: league away average 1.33 × Troyes away attack 0.72 × PSG home defence 0.91.

Based on 3 home games for PSG, 4 away games for Troyes and 81 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: PSG (55%). This is an estimate, not a certainty.

Form & stats this competition season

PSGTroyes
Table position#1 · 23 pts#17 · 8 pts
Last 5 (newest first)WWWWWLWDLL
Home W-D-L (goals)3-0-1 (7:3)1-1-3 (5:11)
Away W-D-L (goals)4-2-0 (15:7)1-1-3 (2:6)
Goals per game at home (for/against)1.75 / 0.751.00 / 2.20
Goals per game away (for/against)2.50 / 1.170.40 / 1.20
xGn/an/a

xG is not available from the current data source (football-data.org). Competition averages: 1.63 home and 1.32 away goals per match (90 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.

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