Peterborough
v
Sheffield Wednesday
Both teams to score · 64% model probability · odds 1.44
Model BTTS 64% O2.5 62%
Odds Home 3.10 Draw 3.50 Away 2.15 BTTS 1.44 O2.5 1.53
Wigan
v
Stockport County
Both teams to score · 59% model probability · odds 1.57
Model BTTS 59% O2.5 55%
Odds Home 3.00 Draw 3.40 Away 2.25 BTTS 1.57 O2.5 1.70
Barnsley
v
Stevenage
Barnsley to win · 44% model probability · odds 2.10 ▼ Steaming 12.2%
Model BTTS 54% O2.5 49%
Odds Home 2.10 Draw 3.30 Away 3.40 BTTS 1.75 O2.5 1.95
Bradford
v
Mansfield Town
Bradford to win · 51% model probability · odds 1.83
Model BTTS 53% O2.5 50%
Odds Home 1.83 Draw 3.60 Away 4.00 BTTS 1.80 O2.5 1.85
Burton Albion
v
Cambridge United
Cambridge United to win · 36% model probability · odds 2.50 ▼ Steaming 10.7%
Model BTTS 51% O2.5 44%
Odds Home 2.70 Draw 3.25 Away 2.50 BTTS 1.80 O2.5 2.08
Doncaster
v
Plymouth
Both teams to score · 59% model probability · odds 1.62
Model BTTS 59% O2.5 54%
Odds Home 2.40 Draw 3.40 Away 2.75 BTTS 1.62 O2.5 1.75
Huddersfield
v
Notts County
Huddersfield to win · 58% model probability · odds 1.67
Model BTTS 52% O2.5 52%
Odds Home 1.67 Draw 3.80 Away 5.00 BTTS 1.80 O2.5 1.80
Leicester
v
Oxford United
Leicester to win · 55% model probability · odds 1.67
Model BTTS 52% O2.5 51%
Odds Home 1.67 Draw 3.75 Away 4.75 BTTS 1.75 O2.5 1.75
Luton
v
Leyton Orient
Luton to win · 57% model probability · odds 1.67
Model BTTS 58% O2.5 59%
Odds Home 1.67 Draw 4.00 Away 4.50 BTTS 1.62 O2.5 1.60
Reading
v
Blackpool
Reading to win · 49% model probability · odds 1.95
Model BTTS 57% O2.5 55%
Odds Home 1.95 Draw 3.40 Away 3.75 BTTS 1.67 O2.5 1.75
Wycombe
v
Milton Keynes Dons
Both teams to score · 58% model probability · odds 1.62
Model BTTS 58% O2.5 53%
Odds Home 2.30 Draw 3.40 Away 2.88 BTTS 1.62 O2.5 1.75
Bromley
v
AFC Wimbledon
Bromley to win · 41% model probability · odds 2.38
Model BTTS 55% O2.5 49%
Odds Home 2.38 Draw 3.25 Away 2.88 BTTS 1.70 O2.5 1.95
Oxford United
v
Reading
Oxford United to win · 38% model probability
Model BTTS 50% O2.5 43%
Stevenage
v
Luton
Stevenage to win · 46% model probability
Model BTTS 50% O2.5 44%
| # | Team | P | W | D | L | GD | Pts | Form |
|---|---|---|---|---|---|---|---|---|
| 1 | Huddersfield | 4 | 3 | 1 | 0 | 6 | 10 | WWDW |
| 2 | Sheffield Wednesday | 4 | 3 | 0 | 1 | 6 | 9 | WWLW |
| 3 | Blackpool | 4 | 2 | 1 | 1 | 4 | 7 | LWWD |
| 4 | Burton Albion | 4 | 2 | 1 | 1 | 3 | 7 | WLWD |
| 5 | Barnsley | 4 | 2 | 1 | 1 | 2 | 7 | WWDL |
| 6 | Cambridge United | 4 | 2 | 1 | 1 | 1 | 7 | WLDW |
| 7 | Luton | 4 | 2 | 1 | 1 | 0 | 7 | WLDW |
| 8 | Leyton Orient | 4 | 2 | 0 | 2 | 4 | 6 | WLWL |
| 9 | Stockport County | 4 | 2 | 0 | 2 | 3 | 6 | LWLW |
| 10 | Notts County | 4 | 1 | 3 | 0 | 1 | 6 | DWDD |
| 11 | Bradford | 4 | 2 | 0 | 2 | 0 | 6 | LLWW |
| 12 | Mansfield Town | 4 | 2 | 0 | 2 | -2 | 6 | LWLW |
| 13 | Leicester | 4 | 1 | 2 | 1 | 1 | 5 | WDLD |
| 14 | Reading | 3 | 1 | 1 | 1 | 4 | 4 | WDL |
| 15 | Oxford United | 3 | 1 | 1 | 1 | -1 | 4 | LWD |
| 16 | Plymouth | 4 | 1 | 1 | 2 | -2 | 4 | LWDL |
| 17 | Peterborough | 4 | 1 | 1 | 2 | -5 | 4 | DLWL |
| 18 | AFC Wimbledon | 4 | 1 | 1 | 2 | -5 | 4 | LWDL |
| 19 | Bromley | 4 | 1 | 1 | 2 | -9 | 4 | LLDW |
| 20 | Doncaster | 4 | 0 | 3 | 1 | -1 | 3 | DDDL |
| 21 | Stevenage | 4 | 0 | 3 | 1 | -1 | 3 | DDLD |
| 22 | Wigan | 4 | 1 | 0 | 3 | -2 | 3 | WLLL |
| 23 | Milton Keynes Dons | 4 | 0 | 3 | 1 | -2 | 3 | LDDD |
| 24 | Wycombe | 4 | 0 | 2 | 2 | -5 | 2 | LLDD |
League One sits at the point in the English pyramid where bookmaker attention starts to thin out. The Premier League gets the sharpest prices in world football; by the third tier, odds compilers are covering 46 rounds of twelve fixtures with a fraction of the scrutiny, and lines move on far less money. For a statistical model, that is opportunity: the same probability estimate that finds nothing to bet in a top-flight fixture will regularly find a mispriced line here.
The division's profile is mid-scoring — usually around 2.5 to 2.6 goals per game — with a draw rate near 26 per cent and robust home advantage. What distinguishes League One from the divisions above it is variance in squad quality across a season. Third-tier squads are thin, so a single injury to a starting striker or a January loan recall changes a team's output in a way that simply doesn't happen at clubs carrying internationals in reserve. Form swings are sharper and longer-lasting.
The model's recent-form weighting earns its keep in this division. Because it rates teams on a rolling window of results weighted for opposition quality, a genuine mid-season collapse or surge feeds through within a few matches — faster than season-long league position, which is what the casual market anchors on. Clubs relegated from the Championship arrive with inflated reputations and deflated squads, and their early-season prices are among the most reliably wrong in English football; the reverse applies to sides promoted with momentum from League Two.
Early in 2026/27 the usual caveat applies: until around six rounds are played, ratings lean on last season's data adjusted for division changes, and the model widens its uncertainty accordingly. It is deliberately quieter in August than in March.
The markets that produce the most League One selections are the match result — where honest probabilities meet soft lines — and over/under goals in fixtures where a team's true scoring rate has moved ahead of its reputation. Every selection is archived at kickoff, settled at publication odds, and published on the model results page, wins and losses alike.