This Week's Fixtures
FC Halifax Town
v
Yeovil Town
England · National League
Sat 31 Oct, 12:30 UTC
Both teams to score
· 61% model probability
· odds 1.57
Model
Goals 3.0
BTTS 61%
O2.5 58%
Scores
1-1 11.1%
2-1 8.4%
1-2 8.2%
Odds
Home 2.05
Draw 3.60
Away 3.10
BTTS 1.57
O2.5 1.65
Forest Green
v
Harrogate Town
England · National League
Sat 31 Oct, 12:30 UTC
Both teams to score
· 62% model probability
· odds 1.53
Model
Goals 3.0
Corners 8.7 (4.4H · 4.2A)
Cards 4.1
BTTS 62%
O2.5 59%
Scores
1-1 12.4%
2-1 9.2%
1-0 7.5%
Odds
Home 2.45
Draw 3.60
Away 2.55
BTTS 1.53
O2.5 1.62
Aldershot Town
v
Gateshead
England · National League
Sat 31 Oct, 15:00 UTC
Aldershot Town to win
· 61% model probability
· odds 1.53
Model
Goals 3.2
BTTS 58%
O2.5 61%
Scores
1-1 10.6%
2-1 9.3%
1-2 6.7%
Odds
Home 1.53
Draw 4.00
Away 5.00
BTTS 1.67
O2.5 1.57
Altrincham
v
Carlisle
England · National League
Sat 31 Oct, 15:00 UTC
Both teams to score
· 63% model probability
· odds 1.50
Model
Goals 3.1
BTTS 63%
O2.5 60%
Scores
1-1 14.1%
0-0 9.4%
0-1 9.3%
Odds
Home 2.88
Draw 3.60
Away 2.20
BTTS 1.50
O2.5 1.57
Barrow
v
Eastleigh
England · National League
Sat 31 Oct, 15:00 UTC
Barrow to win
· 63% model probability
· odds 1.48
Model
Goals 3.1
BTTS 55%
O2.5 59%
Scores
1-1 13.8%
1-0 11.7%
0-0 10.2%
Odds
Home 1.48
Draw 4.20
Away 5.50
BTTS 1.70
O2.5 1.57
Boreham Wood
v
Hartlepool
England · National League
Sat 31 Oct, 15:00 UTC
Boreham Wood to win
· 75% model probability
· odds 1.25
Model
Goals 3.6
BTTS 54%
O2.5 69%
Scores
2-1 9.2%
1-1 7.9%
3-1 7.8%
Odds
Home 1.25
Draw 5.25
Away 8.00
BTTS 1.70
O2.5 1.40
Solihull Moors
v
Kidderminster Harriers
England · National League
Sat 31 Oct, 15:00 UTC
Both teams to score
· 60% model probability
· odds 1.57
Model
Goals 2.9
BTTS 60%
O2.5 56%
Scores
1-1 11%
1-2 9.9%
0-2 9.1%
Odds
Home 2.45
Draw 3.50
Away 2.50
BTTS 1.57
O2.5 1.70
Tamworth
v
Woking
England · National League
Sat 31 Oct, 15:00 UTC
Both teams to score
· 65% model probability
· odds 1.44
Model
Goals 3.3
BTTS 65%
O2.5 63%
Scores
1-1 12.2%
2-1 8.8%
1-2 8%
Odds
Home 2.20
Draw 3.70
Away 2.75
BTTS 1.44
O2.5 1.50
Wealdstone
v
Southend
England · National League
Sat 31 Oct, 15:00 UTC
Southend to win
· 54% model probability
· odds 1.73
Model
Goals 3.5
BTTS 66%
O2.5 67%
Scores
1-1 9.4%
1-2 9.2%
2-2 6.6%
Odds
Home 3.80
Draw 4.00
Away 1.73
BTTS 1.44
O2.5 1.44
Worthing
v
Sutton Utd
England · National League
Sat 31 Oct, 15:00 UTC
Both teams to score
· 61% model probability
· odds 1.57
Model
Goals 3.1
BTTS 61%
O2.5 61%
Scores
1-1 11.3%
2-1 9.9%
2-0 9.3%
Odds
Home 1.85
Draw 3.75
Away 3.50
BTTS 1.57
O2.5 1.57
Boston United
v
Scunthorpe
England · National League
Sat 31 Oct, 17:30 UTC
Both teams to score
· 66% model probability
· odds 1.44
Model
Goals 3.3
BTTS 66%
O2.5 64%
Scores
1-1 12.7%
1-2 8.7%
2-1 8%
Odds
Home 2.38
Draw 3.70
Away 2.45
BTTS 1.44
O2.5 1.48
Gateshead
v
Tamworth
England · National League
Sat 7 Nov, 15:00 UTC
Tamworth to win
· 55% model probability
· odds 1.62
Model
BTTS 61%
O2.5 61%
Odds
Home 4.20
Draw 4.00
Away 1.62
O2.5 1.57
Betting the National League in 2026/27
The National League is the deepest division we cover, and it is unlike everything above it. The fifth tier mixes full-time former Football League clubs with part-time sides, budgets that differ by an order of magnitude, and squads that can turn over almost entirely in a summer. It is also where bookmaker coverage is at its thinnest: prices go up later, move on small money, and carry wider margins. That combination — high variance football and low-attention markets — is why we track it at all.
The football itself is attritional. Goals sit in the mid-2s, the draw rate is high in the way of all lower-league English football, and home advantage is among the strongest in the country — long trips, tight grounds and surfaces that punish passing sides all contribute. Big-budget relegated clubs do not simply walk through this division, and the market's habit of pricing them as if they will is one of the most persistent inefficiencies we see anywhere.
How the model handles it
Data is the constraint. Fifth-tier matches generate less statistical depth than Football League fixtures, so the model works primarily from results, goals and opposition-adjusted ratings rather than the richer inputs available higher up. It compensates by demanding a larger edge before publishing: a National League selection has to clear a wider margin between model probability and market price than a Premier League one, precisely because the underlying estimate carries more uncertainty.
That discipline matters most in the season's opening weeks. Squad turnover at this level makes August ratings genuinely provisional, and the model stays deliberately quiet until current-season results accumulate. From mid-autumn, when its ratings reflect the actual teams on the pitch rather than last season's, the National League becomes one of our most productive divisions relative to fixtures played.
Expect selections concentrated in the match result and goals markets, with the occasional generously priced draw. Every pick is archived at kickoff, settled at the odds available when published, and recorded on the model results page — the losses as prominently as the wins.