· Segunda Division
Paysandu FC
ATT
5/10
DEF
4/10
1:1
Uruguay Montevideo
3/10
ATT
5/10
DEF
LIVE 77′
Best Pick
Under 2.5
60%
Correct Score77′
Top
1-0
15.6%
6.00
Top
2-0
11.9%
7.00
1-1
11.8%
7.50
0-0
10.2%
8.00
2-1
9%
10.00
0-1
7.7%
12.00
3-0
6.1%
11.00
3-1
4.6%
17.00
156%
3.20TOP
X26%
1.67
218%
5.50
1X82%
X244%
1274%
Goal probabilityUpdating
35%
Before FT
Next 5'
15%
Next 10'
28%
Paysandu FC xG
2.45
exp 0.93+1.52
Uruguay Montevideo xG
1.11
exp 0.93+0.18
Tactical
xG — Expected Goals
Paysandu FC
Paysandu FC exp
Uruguay Montevideo
Uruguay Montevideo exp
goal
Paysandu FC7Avg 19 · Peak 56
Tactical
Uruguay Montevideo19Avg 12 · Peak 31
Momentum
0'15'30'HT60'75'90'
GoalShot
per 15 min
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Paysandu FC
Uruguay Montevideo
77′Trends
Dead Game
Paysandu FC
10-min momentum
Uruguay Montevideo
63%37%
Paysandu FC xG
2.45
exp 1.07+1.38
Uruguay Montevideo xG
1.11
exp 1.07+0.04
Goal Probability Window
Next 5'
15%
Next 10'
28%
Next 15'
35%
Attack vs Defense
Paysandu FC Attack
5.1/10
Uruguay Montevideo Attack
1.3/10
Paysandu FC Defense
3.6/10
Uruguay Montevideo Defense
4.8/10
FT Predictions
Over 2.5
35%
Over 3.5
7%
Under 2.5TOP
65%
Under 3.5TOP
93%
No more goalsTOP
65%
4 decided
Next Goal
Paysandu FC scores next
25%
Uruguay Montevideo scores next
10%
No more goalsTOP
65%
Paysandu FC
5
exp 4.1+0.9
Uruguay Montevideo
4
exp 4.1-0.1
Goal Probability Window
Next 5'
43%
Next 10'
67%
Next 15'
76%
FT Corners · 9 scored
Over 9.5TOP
76%
Under 9.5
24%
Over 8.5TOP
100%
Under 8.5
0%
Over 7.5TOP
100%
Next Corner
Paysandu FC wins next corner
50%
Uruguay Montevideo wins next corner
50%
Paysandu FC
1
exp 1.5-0.5
Uruguay Montevideo
1
exp 1.5-0.5
Total
2/ 3.5
Late-game intensity
High
~0.3 remaining
0.3
Exp. FT
3.5
FT Cards Predictions
Over 3.5
4%
Under 3.5TOP
96%
Over 2.5
28%
Under 2.5TOP
72%
Live 1X2
Paysandu FC Win
24%
DrawTOP
68%
Uruguay Montevideo Win
9%
Goals
Over 2.5
35%
Under 2.5TOP
65%
BTTSTOP
100%
Corners
Over 9.5TOP
76%
Over 8.5TOP
100%
Pressure Index
Paysandu FC7
Uruguay Montevideo19
Probable XI4-4-2
Teuten
Ibáñez
Samudio
Wetch
Sención
Bonilla
26
Widman
Wasilewsky
Mora
Aguilera
Vargas
Impact Player Hot Head

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Paysandu FC vs Uruguay Montevideo 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 Paysandu FC vs Uruguay Montevideo 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 Paysandu FC 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 Paysandu FC vs Uruguay Montevideo 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 Paysandu FC 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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