2026-10-25 · 5 fixtures
Live matches first, then by kick-off time.
| Kick | Match | 1 | X | 2 | Over 2.5 | Under | Our picks |
|---|---|---|---|---|---|---|---|
11:30Sun | Inter Milan Fiorentina Serie A | 79% | 14% | 7% | 61% | 39% | 1X93%Over 2.561% |
11:30Sun Inter Milan Fiorentina Serie A 179% X14% 27% O2.561% U2.539% 1X93%Over 2.561% | |||||||
14:00Sun | Genoa Venezia Serie A | 50% | 25% | 25% | 48% | 52% | 1X75%Over 1.573% |
14:00Sun Genoa Venezia Serie A 150% X25% 225% O2.548% U2.552% 1X75%Over 1.573% | |||||||
14:00Sun | Atalanta BC Frosinone Serie A | 50% | 26% | 25% | 47% | 53% | 1X76%Over 1.572% |
14:00Sun Atalanta BC Frosinone Serie A 150% X26% 225% O2.547% U2.553% 1X76%Over 1.572% | |||||||
17:00Sun | Lecce Juventus Serie A | 25% | 27% | 47% | 42% | 58% | X274%Over 1.568% |
17:00Sun Lecce Juventus Serie A 125% X27% 247% O2.542% U2.558% X274%Over 1.568% | |||||||
19:45Sun | Udinese Calcio AC Milan Serie A | 29% | 27% | 44% | 43% | 57% | 1273%Over 1.569% |
19:45Sun Udinese Calcio AC Milan Serie A 129% X27% 244% O2.543% U2.557% 1273%Over 1.569% | |||||||
Standings and table positions. Combined with our match predictions and analysis above for full context.
| # | Team | P | W | D | L | GF | GA | GD | Pts |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Lazio | 8 | 7 | 1 | 0 | 16 | 5 | +11 | 22 |
| 2 | Inter Milan | 7 | 6 | 1 | 0 | 21 | 9 | +12 | 19 |
| 3 | AS Roma | 8 | 5 | 3 | 0 | 19 | 6 | +13 | 18 |
| 4 | Como | 8 | 5 | 2 | 1 | 14 | 7 | +7 | 17 |
| 5 | AC Milan | 7 | 4 | 3 | 0 | 14 | 7 | +7 | 15 |
| 6 | Frosinone | 7 | 4 | 1 | 2 | 13 | 9 | +4 | 13 |
| 7 | Torino | 8 | 4 | 1 | 3 | 13 | 11 | +2 | 13 |
| 8 | Cagliari | 8 | 4 | 1 | 3 | 6 | 9 | -3 | 13 |
| 9 | Napoli | 8 | 3 | 2 | 3 | 13 | 10 | +3 | 11 |
| 10 | Juventus | 7 | 3 | 2 | 2 | 9 | 8 | +1 | 11 |
| 11 | Atalanta BC | 7 | 3 | 0 | 4 | 10 | 11 | -1 | 9 |
| 12 | Lecce | 7 | 3 | 0 | 4 | 9 | 12 | -3 | 9 |
| 13 | Bologna FC | 8 | 2 | 2 | 4 | 8 | 10 | -2 | 8 |
| 14 | Sassuolo | 8 | 2 | 2 | 4 | 12 | 16 | -4 | 8 |
| 15 | AC Monza Brianza | 8 | 2 | 1 | 5 | 15 | 18 | -3 | 7 |
| 16 | Udinese Calcio | 7 | 1 | 1 | 5 | 9 | 16 | -7 | 4 |
| 17 | Genoa | 7 | 1 | 1 | 5 | 5 | 13 | -8 | 4 |
| 18 | Fiorentina | 7 | 1 | 1 | 5 | 8 | 17 | -9 | 4 |
| 19 | Parma | 8 | 1 | 1 | 6 | 5 | 15 | -10 | 4 |
| 20 | Venezia | 7 | 1 | 0 | 6 | 6 | 16 | -10 | 3 |
Our power ratings measure each team's attacking and defensive strength on a 1-10 scale. Attack power is derived from expected goals (xG) creation, while defense power reflects xG conceded. A rating of 10 means elite, 5 is average, and 1 is weak. These ratings feed into the Poisson model that generates match predictions.
The attack number (ATT) shows how dangerous a team is at scoring — higher means more goals expected. The defense number (DEF) shows how well a team prevents goals — higher means fewer goals conceded. Together they determine the expected goals (xG) for each team in every match, which drives all scoreline probabilities.
Predictions use a Poisson distribution model. For each match, we calculate expected goals for both teams from their attack/defense power ratings. The model then computes the probability of every possible scoreline (0-0 through 5-5) and ranks them by likelihood. The same method applies to over/under, BTTS, and correct score markets.
Expected goals (xG) is a statistical measure that quantifies the likelihood of a shot becoming a goal. A team's cumulative xG across a match estimates how many goals they should score based on chance quality. In Serie A, xG data comes from the SSTrader API and reflects pre-match projections from team form and historical performance.
Yes, all Serie A predictions on ProSoccer are free. You can see match-by-match predictions including 1X2 probabilities, over/under lines, correct scores, and bet builder suggestions without paying or registering. Bookmaker odds are shown only after you tap to expand, keeping the content search-engine compliant.
Over/Under 2.5 goals is typically the most accurate market for statistical models, with 55-65% accuracy. Correct score predictions are lower-probability by nature but can identify value. 1X2 (match winner) accuracy varies by league competitiveness. Our model performs best on goal-line markets because goal distribution follows a Poisson pattern.