🏴 Premier League
Bournemouth vs Brentford
Sep 12, 02:00 PM
2 – 2
Bournemouth vs Brentford
Match Result
Bournemouth Home Win→Draw
Over/Under 2.5
Over 2.5 2.5→4 (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.→Bournemouth Home Win
41%
Predicted score: 1-0
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.→
Bournemouth Home Win
41%
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
56%
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
56%
Confidence: Normal.
2Most Likely Scores
Pre-match Outlook
Bournemouth hold a slim edge over Brentford in this Premier League match — 41% confidence puts it in the Normal tier with a 1-0 projection.
In this Premier League context, small swings in form or selection can flip the projection — treat the narrow-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.
Bournemouth vs Brentford — Bournemouth Home Win: 41%.
Predictions are produced by statistical models and cannot be guaranteed. Use as reference only.