63.30%
1X2 accuracy · 30 predictions (3 months)
Playoff stage
Regular season
| # | Team | P | W | D | L | GF–GA | GD | Pts | Form |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Venezia | 38 | 24 | 10 | 4 | 77–31 | +46 | 82 |
V
P
V
V
P
|
| 2 | Frosinone | 38 | 23 | 12 | 3 | 76–34 | +42 | 81 |
V
V
V
V
P
|
| 3 | Monza | 38 | 22 | 10 | 6 | 61–32 | +29 | 76 |
P
S
V
V
V
|
| 4 | Palermo | 38 | 20 | 12 | 6 | 61–33 | +28 | 72 |
S
V
P
V
P
|
| 5 | Catanzaro | 38 | 15 | 14 | 9 | 62–51 | +11 | 59 |
S
S
V
P
P
|
| 6 | Modena | 38 | 15 | 10 | 13 | 49–36 | +13 | 55 |
S
V
S
S
P
|
| 7 | Juve Stabia | 38 | 11 | 18 | 9 | 44–45 | -1 | 51 |
P
S
P
P
V
|
| 8 | Avellino | 38 | 13 | 10 | 15 | 43–55 | -12 | 49 |
V
S
V
V
P
|
| 9 | Mantova | 38 | 13 | 7 | 18 | 45–57 | -12 | 46 |
S
V
V
S
V
|
| 10 | Padova | 38 | 12 | 10 | 16 | 39–49 | -10 | 46 |
V
V
S
V
V
|
| 11 | Cesena | 38 | 12 | 10 | 16 | 45–56 | -11 | 46 |
S
P
P
S
S
|
| 12 | Carrarese | 38 | 10 | 14 | 14 | 47–52 | -5 | 44 |
S
P
S
P
S
|
| 13 | Sampdoria | 38 | 11 | 11 | 16 | 35–48 | -13 | 44 |
S
V
P
S
V
|
| 14 | Virtus Entella | 38 | 10 | 12 | 16 | 36–51 | -15 | 42 |
V
S
V
P
P
|
| 15 | Empoli | 38 | 9 | 14 | 15 | 47–54 | -7 | 41 |
P
V
S
P
S
|
| 16 | Sudtirol | 38 | 8 | 17 | 13 | 38–48 | -10 | 41 |
P
S
S
S
P
|
| 17 | Bari | 38 | 10 | 10 | 18 | 38–60 | -22 | 40 |
V
V
S
S
S
|
| 18 | Reggiana | 38 | 9 | 10 | 19 | 36–56 | -20 | 37 |
V
S
P
S
V
|
| 19 | Spezia | 38 | 8 | 11 | 19 | 43–59 | -16 | 35 |
P
P
S
V
S
|
| 20 | Pescara | 38 | 7 | 14 | 17 | 51–66 | -15 | 35 |
P
S
P
P
S
|
Champion
Promotion
Promotion Playoff
Relegation Playoff
Relegation
Player statistics
⚽ Top scorers
1
25
J. Pohjanpalo
Palermo
2
17
A. Adorante
Venezia
3
15
F. Ghedjemis
Frosinone
4
15
S. Shpendi
Empoli
5
14
Antonio Di Nardo
Pescara
6
13
G. Artistico
Spezia
7
13
P. Iemmello
Catanzaro
8
13
P. Nuamah
Catanzaro
9
12
T. Biasci
Avellino
10
12
F. Pittarello
Catanzaro
👟 Assists
1
15
G. Calò
Frosinone
2
10
P. Iemmello
Catanzaro
3
10
P. Nuamah
Catanzaro
4
10
A. Palumbo
Palermo
5
9
J. Yeboah
Venezia
6
9
S. Elia
Empoli
7
7
J. Pohjanpalo
Palermo
8
7
S. Pontisso
Catanzaro
9
7
T. Berti
Cesena
10
7
D. Casiraghi
Sudtirol
🟨 Yellow cards
1
15
J. Illanes
Carrarese
2
14
I. Marconi
Virtus Entella
3
13
P. Fusi
Padova
4
12
G. Bracaglia
Frosinone
5
12
L. Henderson
Sampdoria
6
12
M. Perrotta
Padova
7
11
N. Radaelli
Mantova
8
11
S. Trimboli
Mantova
9
11
J. Petriccione
Catanzaro
10
10
O. Correia
Juve Stabia
Model calibration for this league
| Probability band | Sample | Expected (mid) | Actual | Δ |
|---|---|---|---|---|
| 50–60%% | 10 | 55.00% | 40.0% | -15.00% |
| 60–70%% | 15 | 65.00% | 73.3% | +8.30% |
| 70–100%% | 5 | 85.00% | 80.0% | -5.00% |
Based on 30 verified predictions · Δ ≤ 5% = excellent calibration
xG: who scores more (or less) than they deserve
| # | Team | Goals | xG | Δ | |
|---|---|---|---|---|---|
| 1 |
Catanzaro
|
54 | 42.30 | +11.70 |
|
| 2 |
Frosinone
|
59 | 48.98 | +10.02 |
|
| 3 |
Monza
|
52 | 46.25 | +5.75 |
|
| 4 |
Bari
|
27 | 25.12 | +1.88 |
|
| 5 |
Mantova
|
37 | 35.41 | +1.59 |
|
| 6 |
Avellino
|
27 | 26.57 | +0.43 |
|
| 7 |
Padova
|
22 | 22.31 | -0.31 |
|
| 8 |
Palermo
|
46 | 46.36 | -0.36 |
|
| 9 |
Juve Stabia
|
31 | 31.60 | -0.60 |
|
| 10 |
Pescara
|
33 | 34.86 | -1.86 |
|
| 11 |
Sampdoria
|
23 | 25.82 | -2.82 |
|
| 12 |
Venezia
|
56 | 59.69 | -3.69 |
|
| 13 |
Carrarese
|
31 | 34.90 | -3.90 |
|
| 14 |
Virtus Entella
|
24 | 29.65 | -5.65 |
|
| 15 |
Empoli
|
34 | 39.70 | -5.70 |
|
| 16 |
Sudtirol
|
21 | 27.26 | -6.26 |
|
| 17 |
Spezia
|
31 | 38.31 | -7.31 |
|
| 18 |
Reggiana
|
16 | 24.17 | -8.17 |
|
| 19 |
Modena
|
28 | 38.18 | -10.18 |
|
| 20 |
Cesena
|
28 | 39.90 | -11.90 |
|
Δ = Goals scored − accumulated xG · green = overperforms, red = underperforms
Frequently Asked Questions
What predictions are available for Serie B?
For Serie B, ForzaPitch provides 1X2 win probabilities, expected goals (xG), Over 1.5 and Over 2.5 signals and season projections for title, European qualification and relegation per team.
How accurate are predictions for Serie B?
Accuracy for Serie B is tracked match by match and shown on this page. The model is calibrated specifically for Serie B using per-league historical data.
How are Serie B season projections calculated?
Season projections use 10,000 Monte Carlo simulations of the remaining fixtures, sampling from match probability distributions to estimate title, Champions League, Europa League and relegation probabilities per team.