🏴 English National League · Regular Season - 4
Barrow vs Yeovil Town
Aug 28, 06:45 PM · Holker Street
✓ Recorded before kickoffNormal 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.→Barrow Home Win
37%
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.→
Barrow Home Win
37%
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).→
Under 2.5 2.5
51%
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
3Drama Profile
How both teams have handled pressure across the season.
Historical pattern, informational only.
Pre-match Outlook
Barrow hold a slim edge over Yeovil Town in this English National League match — 37% confidence puts it in the Normal tier with a 1-0 projection.
In this English National 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.
Barrow vs Yeovil Town — Barrow Home Win: 37%.
Predictions are produced by statistical models and cannot be guaranteed. Use as reference only.