· MLS
Dallas
ATT
5/10
DEF
5/10
vs
Columbus Crew
6/10
ATT
5/10
DEF
Scheduled· Thu 29 Oct · 00:30
Best Pick
BTTS
62%
Correct Score
Top
1-1
10.3%
7.50
Top
2-1
9.4%
9.00
1-0
7.8%
11.00
2-0
7.1%
12.00
1-2
6.9%
13.00
2-2
6.3%
11.00
3-1
5.7%
13.00
0-1
5.7%
17.00
149%
1.90TOP
X23%
3.70
228%
3.60
1X72%
X251%
1277%
Probable XI3-5-2
Thompson
Augusto
Newman
Jesus
Cappis
Swann
Holstad
García
Johansson
Julio
Kamungo
Impact Player Hot Head Shooter

Anderson Julio — lives for the goal, and when he smells a chance he rarely hesitates

Logan Farrington — the go-to finisher in this side, and he loves these nights

Petar Musa — lives for the goal, and when he smells a chance he rarely hesitates

Lineups not yet announced — full squad analysis below
Dallas26 players
51.0/ 99Average
Top Rated
1Petar MusaFWD83
2Osaze UrhoghideDEF73
3Nolan NorrisDEF66
Columbus Crew31 players
50.5/ 99Average
Top Rated
1Gonzalo TapiaFWD87
2A. SejdićMID80
3André GomesMID73
Dallas40
PlayerOverall RatingImpactAggressionDiscipline
Petar Musa83874876
Osaze Urhoghide73717456
Nolan Norris66716948
Logan Farrington64567470
Shaq Moore59495666
Herman Johansson57385774
Santiago Moreno57436679
Daniel56574450
Lalas Abubakar56577343
Sebastien Ibeagha56703548
Clay Holstad54623950
Jonathan Sirois5252950
Kaick52545149
Columbus Crew43
PlayerOverall RatingImpactAggressionDiscipline
Gonzalo Tapia87849991
A. Sejdić80757372
André Gomes73735868
Taha Habroune72537691
Dylan Chambost70875149
Yevgen Cheberko68517670
Sean Zawadzki65574285
Dániel Gazdag62366089
Brais Méndez58604956
Sekou Tidiany Bangoura54619829
Diego Martín Rossi Marachlian53561472
Hugo Picard52364378
Santiago Rodríguez 51515448
Pre-Match Predictions· Lineups not yet announced
Top Goalscorers
Attackers with highest impact
1
Petar Musa
Dallas
Impact
87
1.80
2
Gonzalo Tapia
Columbus Crew
Impact
84
3.50
3
Sam Sarver
Dallas
Impact
74
2.75
4
Logan Farrington
Dallas
Impact
56
2.60
5
Daniel Job
Dallas
Impact
50
3.40
6
Nicholas Simmonds
Dallas
Impact
47
2.75
Player Rankings
Snipers
Top goal threats
1
Petar MusaDallas
87
2
Gonzalo TapiaColumbus Crew
84
3
Sam SarverDallas
74
4
Wessam Abou AliColumbus Crew
60
5
Logan FarringtonDallas
56
Wall
Top defenders
1
Nolan NorrisDallas
71
2
Osaze UrhoghideDallas
71
3
Sebastien IbeaghaDallas
70
4
Rudy CamachoColumbus Crew
60
5
Lalas AbubakarDallas
57
Control
Top playmakers
1
Dylan ChambostColumbus Crew
87
2
A. SejdićColumbus Crew
75
3
André GomesColumbus Crew
73
4
RamiroDallas
65
5
Clay HolstadDallas
62
Bad Boys
Most likely to get booked
1
Sam SarverDallas
1
2
Jamal ThiaréColumbus Crew
1
3
Wessam Abou AliColumbus Crew
1
4
C. RuvalcabaColumbus Crew
4
5
Patrickson DelgadoDallas
13
Power Rankings
Strongest overall
1
Gonzalo TapiaColumbus Crew
87
2
Petar MusaDallas
83
3
A. SejdićColumbus Crew
80
4
Osaze UrhoghideDallas
73
5
André GomesColumbus Crew
73

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Dallas vs Columbus Crew 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 Dallas vs Columbus Crew 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 Dallas 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 Dallas vs Columbus Crew 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 Dallas 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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