League One Predictions

Probabilities for League One (England) matches, computed by a Poisson + Dixon-Coles model and calibrated on real results — published and frozen before kick-off, verifiable after.

5 complete predictions free every day · no account · no ads · zero bookmaker links

The model has analysed 24 matches from League One in the next 7 days, the first on 20 October 2026.

Upcoming League One fixtures

When	Match	1 · X · 2	Most likely market
20.10 21:45	AFC Wimbledon – Mansfield Town ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Blackpool – Milton Keynes Dons ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Bromley – Leicester ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Burton Albion – Bradford ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Cambridge United – Wycombe ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Doncaster – Stockport County ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Huddersfield – Peterborough ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Luton – Barnsley ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Notts County – Sheffield Wednesday ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Oxford United – Wigan ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
20.10 21:45	Stevenage – Plymouth ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
21.10 22:00	Reading – Leyton Orient ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 14:30	Huddersfield – Wigan ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 14:30	Luton – Leicester ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	AFC Wimbledon – Wycombe ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Blackpool – Mansfield Town ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Bromley – Peterborough ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Burton Albion – Leyton Orient ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Cambridge United – Plymouth ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Doncaster – Sheffield Wednesday ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Notts County – Stockport County ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Oxford United – Bradford ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Reading – Barnsley ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership
24.10 17:00	Stevenage – Milton Keynes Dons ⚠️ uncalibrated	🔒 this match's probabilities are for members	membership

Times are Romania time (CET+1). Probabilities are the empirically calibrated ones, not the raw model output. The last column only says which of the tracked markets has the highest calibrated probability — a description of the model's output, not a recommendation; a high percentage is still a probability, not a certainty. The model computes every match in the list; 5 a day are published free, the rest are for members.

How well the model knows this league

On the calibration backtest (January–May 2026, ratings frozen on 31 December 2025) the model saw 290 matches from League One. It expected 5.8% fewer goals than were actually scored — exactly the deviation the per-league calibration corrects. ✓ calibrated

That deviation is within the ±10% we require to call the league's goal profile separately validated, not just covered by the global calibration.

The full method, with what we correct and what we don't, is on the methodology page.

What came true so far in League One

33 resolved predictions: 26 hit, 7 missed — 78.8%, with a statistical floor (Wilson 95%) of 62.2%. The sample is still small; we publish it because it is real, not because it is conclusive.

Market	N	WIN	LOSS
Under 3.5	18	13	5
Over 1.5	15	13	2

Every day we publish 5 complete predictions for free, plus the entire track record — misses included. The rest of the day's predictions, the Discord delivery and the written analyses are part of the membership. Other leagues: all league pages. Această pagină există și în română.

Empirically calibrated probabilities · informational · not betting advice · 18+