🏴 English League Two
Notts County vs Salford City
May 25, 02:00 PM
Full Time
3 – 0
Notts County vs Salford City
Our prediction: Salford City Away Win ✗ Missed
Drama Profile
How both teams have handled pressure across the season.
Historical pattern, informational only.
Normal PREDICTIONConfidence 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.→
Salford City Away Win
36%
Predicted score: 0-1
Outcome Probabilities
1X2 — 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.→
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).→
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.→
Most Likely Scores
0-1
12.3%
1-2
7.7%
0-2
7.1%
Pre-match Outlook
Salford City hold a slim edge over Notts County in this English League Two match — 36% confidence puts it in the Normal tier with a 0-1 projection.
In this English League Two 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.
Notts County vs Salford City — Salford City Away Win: 36%.
Predictions are produced by statistical models and cannot be guaranteed. Use as reference only.