🇫🇷 Ligue 1
Estac Troyes vs Strasbourg
Sep 06, 01:00 PM
2 – 6
Estac Troyes vs Strasbourg
Match Result
Strasbourg Away Win→Strasbourg Away Win
Over/Under 2.5
Over 2.5 2.5→8 (Over 2.5)
Both Teams Score
BTTS: Yes→BTTS: Yes
Recorded before kickoff · never revised after
Normal PREDICTION
Confidence ThresholdGoalence groups predictions into three tiers by the probability of the picked outcome: Elite (≥ 70%), Safe (55-70%), and Normal (< 55%). Accuracy is reported separately for each tier so users can see how the model performs at its strongest signal.→Strasbourg Away Win
52%
Predicted score: 0-2
1Outcome Probabilities
Match ResultMatch Result (1X2)The traditional outcome market: Home win (1), Draw (X), or Away win (2). Goalence outputs three probabilities summing to 100% for every fixture.→
Strasbourg Away Win
52%
Over/Under 2.5Over/Under 2.5A prediction market that resolves Over if the total goals in the match are 3 or more, Under if 2 or fewer. Computed from Goalence's two lambdas: P(home_goals + away_goals ≥ 3).→
Over 2.5 2.5
53%
Both Teams ScoreBTTS — Both Teams To ScoreA prediction market that resolves Yes if both teams score at least one goal in the match, No otherwise. Goalence outputs a BTTS probability for every fixture by integrating the Poisson distribution over scorelines.→
BTTS: Yes
54%
Confidence: Normal.
2Most Likely Scores
Pre-match Outlook
Strasbourg enter this Ligue 1 fixture with a measured advantage over Estac Troyes (52% confidence, Normal tier) and a projected 0-2 result.
In this Ligue 1 context, small swings in form or selection can flip the projection — treat the moderate-confidence pick as a starting point rather than a lock.
How the Model Works
We use an iterative Pi-Ratings model: each team has separate home and away attack/defense ratings, updated after every match. Lambda values are converted to outcome probabilities via Poisson distribution. Match result, over/under, and BTTS predictions are all derived from a single coherent model.
Estac Troyes vs Strasbourg — Strasbourg Away Win: 52%.
Predictions are produced by statistical models and cannot be guaranteed. Use as reference only.