· League One
Leyton Orient
ATT
4/10
DEF
4/10
vs
Cambridge
6/10
ATT
6/10
DEF
Scheduled· Sat 31 Oct · 12:30

AI Match Analysis

Leyton Orient’s attack may be low-powered, but at home they have enough expected threat to find a way through, especially against a Cambridge side with a solid attack of its own. Cambridge should make the most of Orient’s leaky defending, while the hosts are likely to respond and keep both teams to score firmly in play.

Both Teams to ScoreYes
Best Pick
BTTS
53%
Correct Score
Top
1-1
12.5%
6.50
Top
0-1
9.7%
9.50
1-0
9.6%
9.00
1-2
8.2%
10.00
2-1
8.1%
10.00
0-0
7.4%
11.00
0-2
6.3%
13.00
2-0
6.2%
13.00
136%
2.50
X26%
3.40
237%
2.70TOP
1X62%
X263%
1273%
Confirmed XI4-5-1
1
Baxter
2
Stevens
4
Edmonds-Green
12
Gilchrist
19
Boniface
20
Gilbert
8
Mizouni
10
Connolly
17
Dobra
7
O'Neill
9
Kabia
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Leyton Orient30 players
50.4/ 99Average
Top Rated
1Armando DobraFWD76
2Joseph OlowuDEF70
3Dane Scarlett FWD70
Cambridge22 players
51.5/ 99Average
Top Rated
1Patrick BauerDEF80
2Glenn McConnellMID70
3Shayne Francis LaveryFWD70
Leyton Orient37
PlayerOverall RatingImpactAggressionDiscipline
Armando Dobra76699983
Joseph Olowu70585185
Dane Scarlett 70595791
Nicholas Oyekunle68608272
Alfie Gilchrist64644172
Phillip Chinedu63395291
Idris El Mizouni62458663
Tyreeq Bakinson60595259
Dylan Levitt59465472
Sean Clare58277591
W. Forrester57753741
Dominic Ballard57543575
Nathan Baxter5456950
Cambridge33
PlayerOverall RatingImpactAggressionDiscipline
Patrick Bauer80696481
Glenn McConnell70687956
Shayne Francis Lavery7099511
Sullay Kaikai64683761
Gassan Ahadme63516784
Mamadou Jobe59473789
Owen Moxon59495668
George Hoddle57593961
Jake Eastwood51509956
Cathal Heffernan51633546
Isaac Heath51493761
Liam Bennett48484056
S. Curtis48517134
Player Rankings
Snipers
Top goal threats
1
Shayne Francis LaveryCambridge
99
2
Armando DobraLeyton Orient
69
3
Sullay KaikaiCambridge
68
4
Nicholas OyekunleLeyton Orient
60
5
Dane Scarlett Leyton Orient
59
Wall
Top defenders
1
W. ForresterLeyton Orient
75
2
Patrick BauerCambridge
69
3
Alfie GilchristLeyton Orient
64
4
Cathal HeffernanCambridge
63
5
Kelland WattsCambridge
60
Control
Top playmakers
1
Alex GilbertLeyton Orient
85
2
Glenn McConnellCambridge
68
3
Tyreeq BakinsonLeyton Orient
59
4
George HoddleCambridge
59
5
Dominic BallCambridge
57
Bad Boys
Most likely to get booked
1
Alex GilbertLeyton Orient
1
2
Isaac HaydenLeyton Orient
1
3
Theodore ArchibaldLeyton Orient
1
4
Shayne Francis LaveryCambridge
1
5
Ben KnightCambridge
7
Power Rankings
Strongest overall
1
Patrick BauerCambridge
80
2
Armando DobraLeyton Orient
76
3
Joseph OlowuLeyton Orient
70
4
Dane Scarlett Leyton Orient
70
5
Glenn McConnellCambridge
70

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Leyton Orient vs Cambridge based on each team's expected goals (xG). The top-3 most likely scorelines are shown above with their probability percentages. Even the highest-probability score rarely exceeds 12-15% chance, as football is a low-scoring sport.

The Bet Builder combines multiple selections from the Leyton Orient vs Cambridge match into one bet. Our AI identifies outcomes that complement each other — for example, a home win paired with over 2.5 goals and both teams to score. All selections must win for the combined bet to pay out, which means higher combined odds but also higher risk.

xG (expected goals) measures the quality of scoring chances. If Leyton Orient has an xG of 1.8, it means they are expected to score around 1-2 goals based on chance quality. The model uses pre-match xG to build a probability table for all possible scorelines. A team can overperform xG (score more than expected) or underperform xG (score fewer).

Yes, all predictions on ProSoccer are completely free. You can view predicted scorelines, over/under probabilities, and bet builder suggestions for Leyton Orient vs Cambridge without paying or registering. Odds values are revealed after a tap to keep the page compliant with search engine guidelines.

A value bet occurs when the probability of an outcome is higher than what the bookmaker odds suggest. For example, if our model gives Leyton Orient a 55% chance of winning but the odds imply only 40%, that is a value bet. Our AI highlights selections where the model probability exceeds the implied probability from the odds.

AI predictions use statistical modeling (Poisson distribution) based on historical data and pre-match metrics. They are more reliable over large samples than for any single match. No prediction is guaranteed — football has inherent unpredictability. Our model typically identifies the correct top-3 scorelines in 25-30% of matches, which is significantly better than random chance.

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