ITA1 · Serie A · Match Analysis

Lecce vs
Bologna

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

Analysis date11 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
20.68%
Lecce
Draw
31.65%
X
Expected goals 0.79 – 1.33 2.12 total
BTTS 41.86% Both teams to score
Over 1.5 64.19% 2+ total goals
Over 2.5 35.58% 3+ total goals
Score model

Most likely scorelines.

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

#10:114.29%
#21:114.27%
#30:013.64%
#40:210.58%
#51:28.38%
Additional scorelines
1:07.87%
2:15.00%
0:34.68%
2:03.77%
1:33.71%
Team context

Strength and recent form.

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

Home

Lecce

Elo1453.5
Overall attack0.91
Overall defense1.64
Home attack0.99
Home defense1.52
Form signal-1.329
Last 5 xGF / xGA0.88 / 2.30
Last 10 xGF / xGA0.94 / 2.11
Last 10 xGD-1.17
League statusSTABLE · from ITA1 2025/26
Away

Bologna

Elo1504.6
Overall attack1.19
Overall defense1.11
Away attack1.00
Away defense1.09
Form signal+0.028
Last 5 xGF / xGA1.09 / 1.02
Last 10 xGF / xGA1.05 / 1.09
Last 10 xGD-0.04
League statusSTABLE · from ITA1 2025/26
Elo difference
-51.1

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 matches8Effective: 2.23
Average goals2.31Lecce 0.59 · Bologna 1.72
H2H 3+ goals33.35%Historical context
H2H BTTS32.47%Model BTTS: 41.86%
H2H 2+ goals74.18%
H2H 3+ goals33.35%
H2H 4+ goals33.35%
H2H BTTS32.47%
Goal distribution

Total goals profile.

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

013.64%
122.16%
228.61%
319.06%
410.10%
54.28%
61.51%
7+0.62%
0–1 goals35.81%Low total
2+ goals64.19%Over 1.5
3+ goals35.58%Over 2.5
4+ goals16.52%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 matches793.77
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 / A0.79 / 1.33
Relative strengths and form diagnostics

Lecce

Home attack strength0.793
Home defense weakness1.226
Base lambda home0.92
Attack form xGF level0.902
Defense form xGA level (lower is better)2.231
Opponent-adjusted attack residual-0.330
Opponent-adjusted defense residual (higher is better)-0.925
Opponent-adjustment weight0.000
Model attack signal-0.366
Model defense signal-0.964
Opponent blend0.000
Form matches 5 / 105 / 10
Last 5 xGF / xGA / xGD0.88 / 2.30 / -1.41
Last 10 xGF / xGA / xGD0.94 / 2.11 / -1.17

Bologna

Away attack strength0.895
Away defense weakness0.846
Base lambda away1.28
Attack form xGF level1.075
Defense form xGA level (lower is better)1.047
Opponent-adjusted attack residual-0.208
Opponent-adjusted defense residual (higher is better)+0.207
Opponent-adjustment weight0.000
Model attack signal-0.192
Model defense signal+0.220
Opponent blend0.000
Form matches 5 / 105 / 10
Last 5 xGF / xGA / xGD1.09 / 1.02 / +0.07
Last 10 xGF / xGA / xGD1.05 / 1.09 / -0.04
Historical data coverage

Lecce

Total matches157
Home / away matches78 / 79
xG matches157 / 157
xG home / away coverage78 / 78 · 79 / 79
Effective total31.24
Effective attack / defense31.24 / 31.24
Effective home matches15.05
Effective home attack / defense15.05 / 15.05

Bologna

Total matches157
Home / away matches79 / 78
xG matches157 / 157
xG home / away coverage79 / 79 · 78 / 78
Effective total31.33
Effective attack / defense31.33 / 31.33
Effective away matches15.11
Effective away attack / defense15.11 / 15.11
Historical data coverage
95.99%

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
PeriodNModel 1X2 LLBaseline 1X2 LLImprovement
2025-08200.97951.0890+10.05%
2025-09300.98761.0892+9.33%
2025-10401.04721.1022+4.99%
2025-11391.02381.0935+6.37%
2025-12371.06631.0804+1.31%
2026-01580.94981.0988+13.56%
2026-02400.96271.0955+12.12%
2026-03360.98981.0612+6.73%
2026-04401.00621.0889+7.60%
2026-05401.10311.1105+0.67%
2026-08200.81521.0882+25.09%
2026-09301.02581.0708+4.20%

Football is data.

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