2026-11-15 · 8 fixtures
Live matches first, then by kick-off time.
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 | Palermo | 11 | 8 | 3 | 0 | 25 | 13 | +12 | 27 |
| 2 | Modena | 11 | 7 | 2 | 2 | 20 | 10 | +10 | 23 |
| 3 | Ascoli | 11 | 5 | 5 | 1 | 17 | 7 | +10 | 20 |
| 4 | Mantova | 11 | 5 | 4 | 2 | 15 | 11 | +4 | 19 |
| 5 | Verona | 11 | 4 | 4 | 3 | 19 | 13 | +6 | 16 |
| 6 | Avellino | 11 | 4 | 4 | 3 | 16 | 11 | +5 | 16 |
| 7 | Benevento | 11 | 4 | 4 | 3 | 15 | 11 | +4 | 16 |
| 8 | Pisa | 11 | 4 | 4 | 3 | 20 | 17 | +3 | 16 |
| 9 | Cremonese | 11 | 4 | 3 | 4 | 14 | 12 | +2 | 15 |
| 10 | Südtirol | 11 | 3 | 6 | 2 | 13 | 12 | +1 | 15 |
| 11 | Padova | 11 | 4 | 3 | 4 | 12 | 13 | -1 | 15 |
| 12 | Cesena | 11 | 3 | 6 | 2 | 12 | 14 | -2 | 15 |
| 13 | Juve Stabia | 11 | 4 | 4 | 3 | 12 | 11 | +1 | 14 |
| 14 | Sampdoria | 11 | 3 | 2 | 6 | 11 | 18 | -7 | 11 |
| 15 | Arezzo | 11 | 3 | 2 | 6 | 9 | 20 | -11 | 11 |
| 16 | Virtus Entella | 11 | 2 | 4 | 5 | 11 | 14 | -3 | 10 |
| 17 | Carrarese | 11 | 3 | 1 | 7 | 9 | 14 | -5 | 10 |
| 18 | Empoli | 11 | 2 | 3 | 6 | 12 | 19 | -7 | 9 |
| 19 | Vicenza | 11 | 2 | 3 | 6 | 14 | 24 | -10 | 9 |
| 20 | Catanzaro | 11 | 1 | 3 | 7 | 11 | 23 | -12 | 6 |
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 B, xG data comes from the SSTrader API and reflects pre-match projections from team form and historical performance.
Yes, all Serie B 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.