60.00%
1X2 accuracy · 15 predictions (3 months)
Matchday 0 of 38
0%
League Table
End of season projections
Monte Carlo simulation · 10,000 simulated seasons · updated 31 Jul 2026
Champion
Champions League
Europa League
Conference League
Relegation
| # | Team | Zone probability | Projected Pts | Schedule | Trend |
|---|---|---|---|---|---|
| 1 |
53 (25–83)
pos. ~10.3°
|
C19 · T19
ELO 1553
|
▲0% | ||
| 2 |
50 (18–79)
pos. ~12.0°
|
C19 · T19
ELO 1555
|
▼1% | ||
| 3 |
46 (20–80)
pos. ~14.3°
|
C19 · T19
ELO 1559
|
▲1% | ||
| 4 |
58 (32–83)
pos. ~6.9°
|
C19 · T19
ELO 1548
|
· | ||
| 5 |
51 (22–81)
pos. ~11.3°
|
C19 · T19
ELO 1554
|
▼0% | ||
| 6 |
59 (25–88)
pos. ~6.7°
|
C19 · T19
ELO 1548
|
▲1% | ||
| 7 |
47 (17–79)
pos. ~13.8°
|
C19 · T19
ELO 1558
|
▼1% | ||
| 8 |
62 (31–90)
pos. ~5.0°
|
C19 · T19
ELO 1545
|
▼1% | ||
| 9 |
55 (27–83)
pos. ~8.6°
|
C19 · T19
ELO 1551
|
▲0% | ||
| 10 |
50 (22–81)
pos. ~12.0°
|
C19 · T19
ELO 1555
|
▲1% | ||
| 11 |
46 (17–76)
pos. ~14.8°
|
C19 · T19
ELO 1559
|
▲0% | ||
| 12 |
52 (22–80)
pos. ~10.7°
|
C19 · T19
ELO 1554
|
▼0% | ||
| 13 |
56 (27–86)
pos. ~8.4°
|
C19 · T19
ELO 1551
|
▼0% | ||
| 14 |
55 (24–85)
pos. ~9.1°
|
C19 · T19
ELO 1552
|
▼0% | ||
| 15 |
47 (20–78)
pos. ~14.0°
|
C19 · T19
ELO 1558
|
▲0% | ||
| 16 |
57 (30–91)
pos. ~7.4°
|
C19 · T19
ELO 1549
|
▲0% | ||
| 17 |
48 (19–81)
pos. ~13.0°
|
C19 · T19
ELO 1557
|
▲1% | ||
| 18 |
47 (19–80)
pos. ~13.6°
|
C19 · T19
ELO 1558
|
▼1% | ||
| 19 |
51 (20–79)
pos. ~11.7°
|
C19 · T19
ELO 1555
|
▲0% | ||
| 20 |
59 (31–88)
pos. ~6.3°
|
C19 · T19
ELO 1548
|
▼0% |
% = probability of reaching that zone or better. Each sparkline shows the trend of the most relevant probability for each team over the last 12 daily simulations.
Upcoming matches
Model & advanced data
Model calibration for this league▾
| Probability band | Sample | Expected (mid) | Actual | Δ |
|---|---|---|---|---|
| 50–60%% | 25 | 55.00% | 48.0% | -7.00% |
| 60–70%% | 12 | 65.00% | 83.3% | +18.30% |
| 70–100%% | 4 | 85.00% | 75.0% | -10.00% |
Based on 41 verified predictions · Δ ≤ 5% = excellent calibration
Squad value & Efficiency▾
| # | Team | Value (€M) | Pts | Over/Under | Δ pts ↓ | Eff. rank |
|---|---|---|---|---|---|---|
Udinese
|
€139.9M | 0 |
|
+0.0 | ||
Torino
|
€136.9M | 0 |
|
+0.0 | ||
Sassuolo
|
€162.4M | 0 |
|
+0.0 | ||
AS Roma
|
€410.5M | 0 |
|
+0.0 | ||
Parma
|
€151.0M | 0 |
|
+0.0 | ||
Napoli
|
€421.3M | 0 |
|
+0.0 | ||
AC Milan
|
€493.5M | 0 |
|
+0.0 | ||
Lecce
|
€95.4M | 0 |
|
+0.0 | ||
Lazio
|
€224.8M | 0 |
|
+0.0 | ||
Juventus
|
€549.7M | 0 |
|
+0.0 | ||
Inter
|
€666.8M | 0 |
|
+0.0 | ||
Genoa
|
€137.4M | 0 |
|
+0.0 | ||
Fiorentina
|
€248.0M | 0 |
|
+0.0 | ||
Como
|
€312.8M | 0 |
|
+0.0 | ||
Cagliari
|
€133.3M | 0 |
|
+0.0 | ||
Bologna
|
€291.0M | 0 |
|
+0.0 | ||
Atalanta
|
€421.1M | 0 |
|
+0.0 | ||
Monza
|
n/d | 0 | ||||
Frosinone
|
n/d | 0 | ||||
Venezia
|
n/d | 0 |
Source: Transfermarkt · Δ pts = actual points − expected points from squad value regression
Frequently Asked Questions
What predictions are available for Serie A?
For Serie A, 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 A?
Accuracy for Serie A is tracked match by match and shown on this page. The model is calibrated specifically for Serie A using per-league historical data.
How are Serie A 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.