Home win
32.40%
Lorient
FRA1 · Ligue 1 · Match Analysis
Lorient vs
Monaco
Model-based match probabilities derived from multi-season xG data, team strength, venue performance, recent form, Elo ratings and league context.
Model output
Match probabilities.
Probabilities are model estimates, not certainties or betting guarantees.
Draw
26.91%
X
Away win
40.69%
Monaco
Score model
Most likely scorelines.
Exact-score probabilities from the Poisson + Dixon-Coles goal model.
Additional scorelines
0:06.98%
0:26.78%
2:25.78%
2:05.21%
1:34.39%
Team context
Strength and recent form.
Venue-adjusted team strength, Elo rating and recent xG performance.
Home
Lorient
Elo1497.0
Overall attack1.25
Overall defense1.41
Home attack1.32
Home defense1.28
Form signal-0.271
Last 5 xGF / xGA0.95 / 1.28
Last 10 xGF / xGA1.10 / 1.28
Last 10 xGD-0.18
League statusSTABLE · from FRA1 2025/26
Away
Monaco
Elo1587.5
Overall attack1.69
Overall defense1.32
Away attack1.54
Away defense1.48
Form signal-0.159
Last 5 xGF / xGA1.25 / 1.43
Last 10 xGF / xGA1.21 / 1.32
Last 10 xGD-0.12
League statusSTABLE · from FRA1 2025/26
Elo difference
-90.6
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.
Goal distribution
Total goals profile.
The model's probability distribution for the total number of goals.
06.98%
115.37%
224.74%
322.24%
415.54%
58.68%
64.04%
7+2.42%
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
LeagueFRA1
Loaded teams25
Loaded historical matches1352
Target season2026/27
Previous seasons in history4
Season window2022/23 → 2023/24 → 2024/25 → 2025/26 → 2026/27
League tierTier 1
Historical league matches1352
xG matches1351 / 1352
Effective xG matches664.83
Observed home xG1.62
Observed away xG1.31
Model home xG baseline1.62
Model away xG baseline1.30
Total league xG baseline2.92
Home-advantage weight1.016
Model configdata/models/FRA1.json
Team attack half-life240.0 days
Team defense half-life365.0 days
Attack strength weight0.881
Defense strength weight0.856
Venue prior matches4.81
DistributionPoisson + Dixon-Coles
Dixon-Coles rho-0.073 (effective -0.072)
Dixon-Coles decay0.025
Goal overdispersion0.000
Implied goal variance H / A1.31 / 1.49
Relative strengths and form diagnostics
Lorient
Home attack strength0.867
Home defense weakness0.981
Base lambda home1.33
Attack form xGF level1.005
Defense form xGA level (lower is better)1.276
Opponent-adjusted attack residual-0.475
Opponent-adjusted defense residual (higher is better)+0.169
Opponent-adjustment weight0.000
Model attack signal-0.457
Model defense signal+0.186
Opponent blend0.000
Form matches 5 / 105 / 10
Last 5 xGF / xGA / xGD0.95 / 1.28 / -0.32
Last 10 xGF / xGA / xGD1.10 / 1.28 / -0.18
Monaco
Away attack strength1.139
Away defense weakness0.925
Base lambda away1.44
Attack form xGF level1.235
Defense form xGA level (lower is better)1.393
Opponent-adjusted attack residual-0.276
Opponent-adjusted defense residual (higher is better)+0.024
Opponent-adjustment weight0.000
Model attack signal-0.227
Model defense signal+0.069
Opponent blend0.000
Form matches 5 / 105 / 10
Last 5 xGF / xGA / xGD1.25 / 1.43 / -0.18
Last 10 xGF / xGA / xGD1.21 / 1.32 / -0.12
Historical data coverage
Lorient
Total matches112
Home / away matches56 / 56
xG matches111 / 112
xG home / away coverage56 / 56 · 55 / 56
Effective total23.17
Effective attack / defense23.17 / 33.21
Effective home matches11.69
Effective home attack / defense11.69 / 16.72
Monaco
Total matches146
Home / away matches73 / 73
xG matches145 / 146
xG home / away coverage72 / 73 · 73 / 73
Effective total28.49
Effective attack / defense28.49 / 43.19
Effective away matches14.44
Effective away attack / defense14.44 / 21.84
Historical data coverage
67.54%
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 1332 historical matches.
Positive improvement means the model performed better than the league baseline.
Total goals log-loss vs baseline+0.13%
1X2 log-loss vs baseline+6.78%
BTTS Brier vs baseline+0.15%
Over 2.5 Brier vs baseline+0.67%
Full backtest metrics
Model
MAE total goals1.3466
Exact score log-loss2.9655
Total goals Brier0.8292
Total goals log-loss1.9099
1X2 Brier0.5970
1X2 log-loss0.9986
BTTS Brier0.2482
Over 1.5 Brier0.1771
Over 2.5 Brier0.2461
Over 3.5 Brier0.2140
League baseline
MAE total goals1.3378
Exact score log-loss3.0550
Total goals Brier0.8301
Total goals log-loss1.9123
1X2 Brier0.6483
1X2 log-loss1.0711
BTTS Brier0.2486
Over 1.5 Brier0.1771
Over 2.5 Brier0.2478
Over 3.5 Brier0.2150
Calibration diagnostics
Home win · ECE 3.26%
0- 10% n=6 avg= 7.7% actual= 0.0% 10- 20% n=58 avg= 16.5% actual= 12.1% 20- 30% n=236 avg= 25.6% actual= 22.5% 30- 40% n=316 avg= 35.2% actual= 40.5% 40- 50% n=270 avg= 44.5% actual= 44.4% 50- 60% n=240 avg= 54.3% actual= 53.3% 60- 70% n=163 avg= 64.5% actual= 71.2% 70- 80% n=33 avg= 73.7% actual= 69.7% 80- 90% n=10 avg= 83.4% actual=100.0%
Draw · ECE 1.22%
0- 10% n=2 avg= 8.9% actual= 0.0% 10- 20% n=112 avg= 17.4% actual= 18.8% 20- 30% n=1206 avg= 25.4% actual= 24.4% 30- 40% n=12 avg= 30.7% actual= 8.3%
Away win · ECE 1.77%
0- 10% n=25 avg= 7.2% actual= 4.0% 10- 20% n=247 avg= 15.4% actual= 12.1% 20- 30% n=339 avg= 24.7% actual= 25.1% 30- 40% n=331 avg= 34.8% actual= 36.6% 40- 50% n=230 avg= 44.4% actual= 45.7% 50- 60% n=116 avg= 54.0% actual= 51.7% 60- 70% n=32 avg= 63.7% actual= 65.6% 70- 80% n=10 avg= 73.4% actual= 60.0% 80- 90% n=2 avg= 82.1% actual=100.0%
BTTS · ECE 1.61%
30- 40% n=1 avg= 39.0% actual=100.0% 40- 50% n=110 avg= 47.8% actual= 45.5% 50- 60% n=905 avg= 55.3% actual= 54.4% 60- 70% n=314 avg= 62.8% actual= 59.9% 70- 80% n=2 avg= 71.0% actual=100.0%
Over 2.5 · ECE 1.55%
30- 40% n=9 avg= 37.5% actual= 66.7% 40- 50% n=278 avg= 47.1% actual= 47.5% 50- 60% n=705 avg= 54.8% actual= 53.9% 60- 70% n=308 avg= 63.9% actual= 61.4% 70- 80% n=31 avg= 73.2% actual= 64.5% 80- 90% n=1 avg= 80.2% actual=100.0%
Walk-forward - latest periods
| Period | N | Model 1X2 LL | Baseline 1X2 LL | Improvement |
|---|---|---|---|---|
| 2025-09 | 27 | 0.9625 | 1.0441 | +7.82% |
| 2025-10 | 36 | 1.0534 | 1.0920 | +3.53% |
| 2025-11 | 36 | 1.0088 | 1.0660 | +5.36% |
| 2025-12 | 18 | 0.8662 | 0.9834 | +11.92% |
| 2026-01 | 31 | 1.0056 | 1.0859 | +7.40% |
| 2026-02 | 36 | 0.9691 | 1.0515 | +7.84% |
| 2026-03 | 31 | 0.9884 | 1.0880 | +9.15% |
| 2026-04 | 35 | 1.0260 | 1.1181 | +8.24% |
| 2026-05 | 29 | 1.1218 | 1.0794 | -3.93% |
| 2026-08 | 18 | 1.0714 | 1.1311 | +5.28% |
| 2026-09 | 27 | 1.0297 | 1.0661 | +3.42% |
| 2026-10 | 9 | 0.7451 | 0.9251 | +19.46% |
Football is data.
NILYTIX turns match data into transparent model probabilities and measurable analytical signals.