ITA1 · Serie A · Match Analysis

Monza vs
Cagliari

Model-based match probabilities derived from multi-season xG data, team strength, venue performance, recent form, Elo ratings and league context.

Analysis date19 Oct 2026

Target season2026/27

History window5 seasons

League tierTier 1

Model output

Match probabilities.

Probabilities are model estimates, not certainties or betting guarantees.

Home win

39.17%

Monza

Draw

29.41%

Away win

31.42%

Cagliari

Expected goals 1.35 - 1.18 2.53 total

BTTS 52.60% Both teams to score

Over 1.5 73.15% 2+ total goals

Over 2.5 46.30% 3+ total goals

Score model

Most likely scorelines.

Exact-score probabilities from the Poisson + Dixon-Coles goal model.

#11:114.04%

#21:09.41%

#30:09.33%

#42:18.54%

#50:18.10%

Additional scorelines

1:27.50%

2:07.23%

0:25.58%

2:25.05%

3:13.83%

Team context

Strength and recent form.

Venue-adjusted team strength, Elo rating and recent xG performance.

Home

Monza

Elo1380.0

Overall attack1.22

Overall defense1.39

Home attack1.15

Home defense1.34

Form signal+0.413

Last 5 xGF / xGA1.82 / 1.32

Last 10 xGF / xGA1.60 / 1.36

Last 10 xGD+0.24

League statusSTABLE · from ITA1 2024/25

Away

Cagliari

Elo1512.7

Overall attack1.05

Overall defense1.47

Away attack1.06

Away defense1.57

Form signal-0.847

Last 5 xGF / xGA0.98 / 1.95

Last 10 xGF / xGA1.12 / 1.75

Last 10 xGD-0.63

League statusSTABLE · from ITA1 2025/26

Elo difference

-132.6

Elo is one input among several and does not determine the final 1X2 probability on its own.

Head-to-head

Historical matchup context.

H2H values provide context and are not used as a standalone prediction.

H2H matches4Effective: 0.93

Average goals2.50Monza 0.63 · Cagliari 1.87

H2H 3+ goals67.77%Historical context

H2H BTTS45.61%Model BTTS: 52.60%

H2H 2+ goals82.19%

H2H 3+ goals67.77%

H2H 4+ goals0.00%

H2H BTTS45.61%

Goal distribution

Total goals profile.

The model's probability distribution for the total number of goals.

09.33%

117.51%

226.85%

321.49%

413.57%

56.86%

62.89%

7+1.49%

0-1 goals26.85%Low total

2+ goals73.15%Over 1.5

3+ goals46.30%Over 2.5

4+ goals24.81%Over 3.5

Technical detail

How the model reached the estimate.

Detailed diagnostics are kept below the headline probabilities so the public report remains readable.

League baseline and model setup

LeagueITA1

Loaded teams27

Loaded historical matches1580

Target season2026/27

Previous seasons in history4

Season window2022/23 → 2023/24 → 2024/25 → 2025/26 → 2026/27

League tierTier 1

Historical league matches1580

xG matches1580 / 1580

Effective xG matches797.60

Observed home xG1.37

Observed away xG1.17

Model home xG baseline1.36

Model away xG baseline1.18

Total league xG baseline2.54

Home-advantage weight0.875

Model configdata/models/ITA1.json

Team attack half-life240.0 days

Team defense half-life240.0 days

Attack strength weight1.050

Defense strength weight1.081

Venue prior matches3.31

DistributionPoisson + Dixon-Coles

Dixon-Coles rho-0.106 (effective -0.106)

Dixon-Coles decay0.034

Goal overdispersion0.000

Implied goal variance H / A1.35 / 1.18

Relative strengths and form diagnostics

Monza

Home attack strength0.924

Home defense weakness1.079

Base lambda home1.40

Attack form xGF level1.747

Defense form xGA level (lower is better)1.334

Opponent-adjusted attack residual+0.552

Opponent-adjusted defense residual (higher is better)+0.019

Opponent-adjustment weight0.000

Model attack signal+0.476

Model defense signal-0.063

Opponent blend0.000

Form matches 5 / 105 / 10

Last 5 xGF / xGA / xGD1.82 / 1.32 / +0.50

Last 10 xGF / xGA / xGD1.60 / 1.36 / +0.24

Cagliari

Away attack strength0.917

Away defense weakness1.112

Base lambda away1.17

Attack form xGF level1.031

Defense form xGA level (lower is better)1.878

Opponent-adjusted attack residual-0.229

Opponent-adjusted defense residual (higher is better)-0.596

Opponent-adjustment weight0.000

Model attack signal-0.240

Model defense signal-0.607

Opponent blend0.000

Form matches 5 / 105 / 10

Last 5 xGF / xGA / xGD0.98 / 1.95 / -0.96

Last 10 xGF / xGA / xGD1.12 / 1.75 / -0.63

Historical data coverage

Monza

Total matches120

Home / away matches59 / 61

xG matches120 / 120

xG home / away coverage59 / 59 · 61 / 61

Effective total14.20

Effective attack / defense14.20 / 14.20

Effective home matches6.14

Effective home attack / defense6.14 / 6.14

Cagliari

Total matches120

Home / away matches60 / 60

xG matches120 / 120

xG home / away coverage60 / 60 · 60 / 60

Effective total30.73

Effective attack / defense30.73 / 30.73

Effective away matches15.33

Effective away attack / defense15.33 / 15.33

Historical data coverage

39.17%

This measures usable historical evidence. It is not the probability that the prediction is correct.

Validation

Historical model performance.

Leakage-safe backtesting compares the fitted model with a league baseline over 1560 historical matches.

Positive improvement means the model performed better than the league baseline.

Total goals log-loss vs baseline+0.63%

1X2 log-loss vs baseline+9.07%

BTTS Brier vs baseline+0.37%

Over 2.5 Brier vs baseline+1.34%

Full backtest metrics

Model

MAE total goals1.2171

Exact score log-loss2.7695

Total goals Brier0.8119

Total goals log-loss1.8027

1X2 Brier0.5899

1X2 log-loss0.9879

BTTS Brier0.2496

Over 1.5 Brier0.1909

Over 2.5 Brier0.2463

Over 3.5 Brier0.1841

League baseline

MAE total goals1.2442

Exact score log-loss2.8998

Total goals Brier0.8136

Total goals log-loss1.8143

1X2 Brier0.6583

1X2 log-loss1.0864

BTTS Brier0.2505

Over 1.5 Brier0.1925

Over 2.5 Brier0.2497

Over 3.5 Brier0.1866

Calibration diagnostics

Home win · ECE 2.51%

 0- 10%  n=22   avg=  8.3% actual=  9.1%
10- 20%  n=177  avg= 15.9% actual= 15.8%
20- 30%  n=282  avg= 25.2% actual= 25.5%
30- 40%  n=333  avg= 35.2% actual= 33.6%
40- 50%  n=297  avg= 44.7% actual= 48.1%
50- 60%  n=218  avg= 54.8% actual= 51.8%
60- 70%  n=161  avg= 64.5% actual= 70.8%
70- 80%  n=59   avg= 73.8% actual= 79.7%
80- 90%  n=11   avg= 83.1% actual= 63.6%

Draw · ECE 1.65%

 0- 10%  n=1    avg=  8.3% actual=  0.0%
10- 20%  n=94   avg= 17.1% actual= 21.3%
20- 30%  n=1059 avg= 26.5% actual= 25.3%
30- 40%  n=406  avg= 31.5% actual= 33.7%

Away win · ECE 3.79%

 0- 10%  n=73   avg=  7.7% actual=  6.8%
10- 20%  n=308  avg= 15.0% actual= 12.3%
20- 30%  n=368  avg= 25.0% actual= 22.0%
30- 40%  n=343  avg= 34.6% actual= 30.6%
40- 50%  n=208  avg= 44.6% actual= 53.4%
50- 60%  n=160  avg= 54.3% actual= 53.8%
60- 70%  n=74   avg= 63.6% actual= 70.3%
70- 80%  n=25   avg= 73.6% actual= 76.0%
80- 90%  n=1    avg= 83.8% actual=  0.0%

BTTS · ECE 1.92%

30- 40%  n=64   avg= 37.9% actual= 45.3%
40- 50%  n=823  avg= 45.9% actual= 48.4%
50- 60%  n=637  avg= 53.6% actual= 53.1%
60- 70%  n=36   avg= 61.8% actual= 58.3%

Over 2.5 · ECE 2.49%

20- 30%  n=17   avg= 28.1% actual= 23.5%
30- 40%  n=300  avg= 36.9% actual= 40.0%
40- 50%  n=705  avg= 44.9% actual= 47.1%
50- 60%  n=455  avg= 53.9% actual= 51.6%
60- 70%  n=78   avg= 63.4% actual= 60.3%
70- 80%  n=5    avg= 71.5% actual= 80.0%

Walk-forward - latest periods

Period	N	Model 1X2 LL	Baseline 1X2 LL	Improvement
2025-09	30	0.9825	1.0882	+9.71%
2025-10	40	1.0491	1.1060	+5.14%
2025-11	39	1.0141	1.0922	+7.15%
2025-12	37	1.0639	1.0763	+1.15%
2026-01	58	0.9365	1.0986	+14.75%
2026-02	40	0.9507	1.0931	+13.03%
2026-03	36	0.9894	1.0574	+6.43%
2026-04	40	1.0026	1.0882	+7.87%
2026-05	40	1.1007	1.1080	+0.66%
2026-08	20	0.7777	1.0805	+28.03%
2026-09	30	1.0237	1.0700	+4.33%
2026-10	10	0.8909	1.0354	+13.96%

Football is data.

NILYTIX turns match data into transparent model probabilities and measurable analytical signals.

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Monza vsCagliari

Match probabilities.

Most likely scorelines.

Strength and recent form.

Monza

Cagliari

Historical matchup context.

Total goals profile.

How the model reached the estimate.

Monza

Cagliari

Monza

Cagliari

Historical model performance.

Home win · ECE 2.51%

Draw · ECE 1.65%

Away win · ECE 3.79%

BTTS · ECE 1.92%

Over 2.5 · ECE 2.49%

Football is data.

Monza vs
Cagliari