ITA1 · Serie A · Match Analysis

Inter Milan vs
Parma

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

Analysis date10 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

81.50%

Inter Milan

Draw

13.43%

Away win

5.07%

Parma

Expected goals 2.82 – 0.64 3.45 total

BTTS 44.98% Both teams to score

Over 1.5 86.63% 2+ total goals

Over 2.5 67.02% 3+ total goals

Score model

Most likely scorelines.

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

#12:012.56%

#23:011.79%

#34:08.30%

#41:08.18%

#52:17.99%

Additional scorelines

3:17.50%

1:16.41%

4:15.28%

5:04.68%

0:03.91%

Team context

Strength and recent form.

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

Home

Inter Milan

Elo1676.3

Overall attack2.02

Overall defense1.00

Home attack2.19

Home defense0.92

Form signal+1.515

Last 5 xGF / xGA2.99 / 1.39

Last 10 xGF / xGA2.69 / 1.33

Last 10 xGD+1.36

League statusSTABLE · from ITA1 2025/26

Away

Parma

Elo1471.8

Overall attack0.87

Overall defense1.52

Away attack0.78

Away defense1.64

Form signal-0.926

Last 5 xGF / xGA0.70 / 1.60

Last 10 xGF / xGA0.73 / 1.70

Last 10 xGD-0.97

League statusSTABLE · from ITA1 2025/26

Elo difference

+204.5

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: 1.96

Average goals2.64Inter Milan 2.14 · Parma 0.50

H2H 3+ goals32.09%Historical context

H2H BTTS32.09%Model BTTS: 44.98%

H2H 2+ goals100.00%

H2H 3+ goals32.09%

H2H 4+ goals32.09%

H2H BTTS32.09%

Goal distribution

Total goals profile.

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

03.91%

19.46%

219.62%

321.72%

418.75%

512.94%

67.45%

7+6.15%

0–1 goals13.37%Low total

2+ goals86.63%Over 1.5

3+ goals67.02%Over 2.5

4+ goals45.29%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 matches1570

Target season2026/27

Previous seasons in history4

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

League tierTier 1

Historical league matches1570

xG matches1570 / 1570

Effective xG matches794.53

Observed home xG1.37

Observed away xG1.17

Model home xG baseline1.37

Model away xG baseline1.17

Total league xG baseline2.53

Home-advantage weight1.000

Model configdata/models/ITA1.json

Team attack half-life240.0 days

Team defense half-life240.0 days

Attack strength weight1.000

Defense strength weight1.000

Venue prior matches0.00

DistributionPoisson + Dixon-Coles

Dixon-Coles rho-0.130 (effective -0.130)

Dixon-Coles decay0.000

Goal overdispersion0.000

Implied goal variance H / A2.82 / 0.64

Relative strengths and form diagnostics

Inter Milan

Home attack strength1.460

Home defense weakness0.842

Base lambda home2.29

Attack form xGF level2.887

Defense form xGA level (lower is better)1.371

Opponent-adjusted attack residual+1.555

Opponent-adjusted defense residual (higher is better)-0.163

Opponent-adjustment weight0.000

Model attack signal+1.500

Model defense signal-0.104

Opponent blend0.000

Form matches 5 / 105 / 10

Last 5 xGF / xGA / xGD2.99 / 1.39 / +1.60

Last 10 xGF / xGA / xGD2.69 / 1.33 / +1.36

Parma

Away attack strength0.758

Away defense weakness1.147

Base lambda away0.75

Attack form xGF level0.709

Defense form xGA level (lower is better)1.635

Opponent-adjusted attack residual-0.571

Opponent-adjusted defense residual (higher is better)-0.375

Opponent-adjustment weight0.000

Model attack signal-0.558

Model defense signal-0.368

Opponent blend0.000

Form matches 5 / 105 / 10

Last 5 xGF / xGA / xGD0.70 / 1.60 / -0.90

Last 10 xGF / xGA / xGD0.73 / 1.70 / -0.97

Historical data coverage

Inter Milan

Total matches157

Home / away matches79 / 78

xG matches157 / 157

xG home / away coverage79 / 79 · 78 / 78

Effective total31.36

Effective attack / defense31.36 / 31.36

Effective home matches15.92

Effective home attack / defense15.92 / 15.92

Parma

Total matches81

Home / away matches41 / 40

xG matches81 / 81

xG home / away coverage41 / 41 · 40 / 40

Effective total28.43

Effective attack / defense28.43 / 28.43

Effective away matches13.83

Effective away attack / defense13.83 / 13.83

Historical data coverage

87.18%

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 1550 historical matches.

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

Total goals log-loss vs baseline+0.67%

1X2 log-loss vs baseline+8.58%

BTTS Brier vs baseline+0.50%

Over 2.5 Brier vs baseline+1.36%

Full backtest metrics

Model

MAE total goals1.2186

Exact score log-loss2.7775

Total goals Brier0.8123

Total goals log-loss1.8045

1X2 Brier0.5943

1X2 log-loss0.9942

BTTS Brier0.2495

Over 1.5 Brier0.1911

Over 2.5 Brier0.2462

Over 3.5 Brier0.1842

League baseline

MAE total goals1.2465

Exact score log-loss2.9028

Total goals Brier0.8142

Total goals log-loss1.8167

1X2 Brier0.6590

1X2 log-loss1.0874

BTTS Brier0.2507

Over 1.5 Brier0.1929

Over 2.5 Brier0.2496

Over 3.5 Brier0.1867

Calibration diagnostics

Home win · ECE 3.20%

 0- 10%  n=6    avg=  8.4% actual= 33.3%
10- 20%  n=131  avg= 16.3% actual= 11.5%
20- 30%  n=287  avg= 25.2% actual= 24.4%
30- 40%  n=370  avg= 35.1% actual= 32.2%
40- 50%  n=332  avg= 44.6% actual= 47.0%
50- 60%  n=244  avg= 54.7% actual= 57.0%
60- 70%  n=141  avg= 64.2% actual= 70.9%
70- 80%  n=36   avg= 73.2% actual= 83.3%
80- 90%  n=3    avg= 82.8% actual= 33.3%

Draw · ECE 1.11%

10- 20%  n=45   avg= 17.9% actual= 17.8%
20- 30%  n=951  avg= 26.9% actual= 25.1%
30- 40%  n=554  avg= 31.7% actual= 31.6%

Away win · ECE 4.02%

 0- 10%  n=46   avg=  8.2% actual=  2.2%
10- 20%  n=319  avg= 15.4% actual= 11.9%
20- 30%  n=417  avg= 25.1% actual= 22.8%
30- 40%  n=370  avg= 34.6% actual= 34.1%
40- 50%  n=227  avg= 45.0% actual= 56.4%
50- 60%  n=123  avg= 54.6% actual= 57.7%
60- 70%  n=43   avg= 64.2% actual= 79.1%
70- 80%  n=5    avg= 73.8% actual= 60.0%

BTTS · ECE 1.86%

30- 40%  n=43   avg= 38.3% actual= 44.2%
40- 50%  n=766  avg= 46.2% actual= 48.2%
50- 60%  n=697  avg= 53.8% actual= 52.4%
60- 70%  n=44   avg= 62.1% actual= 59.1%

Over 2.5 · ECE 2.60%

20- 30%  n=12   avg= 28.2% actual= 25.0%
30- 40%  n=319  avg= 37.1% actual= 40.4%
40- 50%  n=722  avg= 45.0% actual= 47.2%
50- 60%  n=437  avg= 53.8% actual= 51.0%
60- 70%  n=59   avg= 63.1% actual= 64.4%
70- 80%  n=1    avg= 70.2% actual=100.0%

Walk-forward - latest periods

Period	N	Model 1X2 LL	Baseline 1X2 LL	Improvement
2025-08	20	0.9795	1.0890	+10.05%
2025-09	30	0.9876	1.0892	+9.33%
2025-10	40	1.0472	1.1022	+4.99%
2025-11	39	1.0238	1.0935	+6.37%
2025-12	37	1.0663	1.0804	+1.31%
2026-01	58	0.9498	1.0988	+13.56%
2026-02	40	0.9627	1.0955	+12.12%
2026-03	36	0.9898	1.0612	+6.73%
2026-04	40	1.0062	1.0889	+7.60%
2026-05	40	1.1031	1.1105	+0.67%
2026-08	20	0.8152	1.0882	+25.09%
2026-09	30	1.0258	1.0708	+4.20%

Football is data.

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

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Inter Milan vsParma

Match probabilities.

Most likely scorelines.

Strength and recent form.

Inter Milan

Parma

Historical matchup context.

Total goals profile.

How the model reached the estimate.

Inter Milan

Parma

Inter Milan

Parma

Historical model performance.

Home win · ECE 3.20%

Draw · ECE 1.11%

Away win · ECE 4.02%

BTTS · ECE 1.86%

Over 2.5 · ECE 2.60%

Football is data.

Inter Milan vs
Parma