· Serie B
Vicenza
ATT
5/10
DEF
4/10
1:2
Modena
5/10
ATT
6/10
DEF
Full-time
Best Pick
Under 2.5
54%
Correct Score94′
Top
1-1
12.7%
6.50
Top
1-0
10.8%
13.00
0-1
9.3%
8.50
2-1
8.6%
13.00
0-0
8%
11.00
1-2
7.4%
9.00
2-0
7.4%
21.00
0-2
5.5%
10.00
141%
2.43TOP
X27%
3.75
232%
3.11
1X68%
X259%
1273%
xG — Expected Goals
Vicenza
Vicenza exp
Modena
Modena exp
goal
per 15 min
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Vicenza
Modena
Confirmed XI3-5-2
16
Gagno
66
Papetti
23
Brighenti
5
Marchizza
28
Caferri
26
Pellizzari
8
Bellemo
10
Valoti
21
Corazza
7
Rauti
33
Merkaj
Impact Player Hot Head
Vicenza24 players
48.5/ 99Average
Top Rated
1Alessandro PietrelliMID68
2Claudio MorraFWD65
3Giuseppe CuomoDEF63
Modena26 players
54.4/ 99Average
Top Rated
1Daniele MontevagoFWD91
2Gastón BrugmanMID83
3Simone SantoroMID69
Player Rankings
Snipers
Top goal threats
1
Daniele MontevagoModena
99
2
Andrea BelottiModena
93
3
Nicola RautiVicenza
65
4
Giuseppe AmbrosinoModena
60
5
Claudio MorraVicenza
53
Wall
Top defenders
1
Nicolò BrighentiVicenza
59
2
Steven NadorModena
59
3
Davide AdorniModena
55
4
Giuseppe CuomoVicenza
53
5
Thomas SandonVicenza
47
Control
Top playmakers
1
Gastón BrugmanModena
95
2
Alessandro BiancoModena
73
3
Simone SantoroModena
63
4
Marco CarraroVicenza
54
5
Wisdom AcquahModena
53
Bad Boys
Most likely to get booked
1
Andrea BelottiModena
4
2
StênioModena
10
3
Alessandro BellemoVicenza
12
4
Kleis BozhanajModena
20
5
Lorenzo CaferriVicenza
23
Power Rankings
Strongest overall
1
Daniele MontevagoModena
91
2
Gastón BrugmanModena
83
3
Simone SantoroModena
69
4
Alessandro PietrelliVicenza
68
5
Andrea BelottiModena
66

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Vicenza vs Modena 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 Vicenza vs Modena 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 Vicenza 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 Vicenza vs Modena 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 Vicenza 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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