Home win
28.75%
Schalke 04
GER1 · Bundesliga · Match Analysis
Schalke 04 vs
Mainz 05
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
25.53%
X
Away win
45.72%
Mainz 05
Score model
Most likely scorelines.
Exact-score probabilities from the Poisson + Dixon-Coles goal model.
Additional scorelines
0:16.26%
1:35.51%
0:05.43%
1:04.59%
2:04.03%
Team context
Strength and recent form.
Venue-adjusted team strength, Elo rating and recent xG performance.
Home
Schalke 04
Elo1479.1
Overall attack1.21
Overall defense1.90
Home attack0.90
Home defense1.49
Form signal-0.663
Last 5 xGF / xGA1.12 / 1.73
Last 10 xGF / xGA1.19 / 1.95
Last 10 xGD-0.76
League statusSTABLE · from GER1 2022/23
Away
Mainz 05
Elo1503.8
Overall attack1.66
Overall defense1.60
Away attack1.59
Away defense1.81
Form signal+0.688
Last 5 xGF / xGA2.56 / 1.88
Last 10 xGF / xGA2.59 / 1.89
Last 10 xGD+0.69
League statusSTABLE · from GER1 2025/26
Elo difference
-24.6
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.
05.43%
110.86%
222.34%
322.30%
417.67%
511.20%
65.92%
7+4.28%
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
LeagueGER1
Loaded teams25
Loaded historical matches1269
Target season2026/27
Previous seasons in history4
Season window2022/23 → 2023/24 → 2024/25 → 2025/26 → 2026/27
League tierTier 1
Historical league matches1269
xG matches1267 / 1269
Effective xG matches638.73
Observed home xG1.74
Observed away xG1.36
Model home xG baseline1.70
Model away xG baseline1.39
Total league xG baseline3.09
Home-advantage weight0.831
Model configdata/models/GER1.json
Team attack half-life365.0 days
Team defense half-life240.0 days
Attack strength weight1.097
Defense strength weight0.981
Venue prior matches6.50
DistributionPoisson + Dixon-Coles
Dixon-Coles rho-0.120 (effective -0.118)
Dixon-Coles decay0.016
Goal overdispersion0.000
Implied goal variance H / A1.39 / 1.78
Relative strengths and form diagnostics
Schalke 04
Home attack strength0.854
Home defense weakness1.063
Base lambda home1.48
Attack form xGF level1.142
Defense form xGA level (lower is better)1.805
Opponent-adjusted attack residual-0.334
Opponent-adjusted defense residual (higher is better)-0.189
Opponent-adjustment weight0.000
Model attack signal-0.404
Model defense signal-0.259
Opponent blend0.000
Form matches 5 / 105 / 10
Last 5 xGF / xGA / xGD1.12 / 1.73 / -0.61
Last 10 xGF / xGA / xGD1.19 / 1.95 / -0.76
Mainz 05
Away attack strength1.122
Away defense weakness1.030
Base lambda away1.67
Attack form xGF level2.570
Defense form xGA level (lower is better)1.883
Opponent-adjusted attack residual+0.992
Opponent-adjusted defense residual (higher is better)-0.372
Opponent-adjustment weight0.000
Model attack signal+1.024
Model defense signal-0.336
Opponent blend0.000
Form matches 5 / 105 / 10
Last 5 xGF / xGA / xGD2.56 / 1.88 / +0.69
Last 10 xGF / xGA / xGD2.59 / 1.89 / +0.69
Historical data coverage
Schalke 04
Total matches39
Home / away matches19 / 20
xG matches39 / 39
xG home / away coverage19 / 19 · 20 / 20
Effective total5.22
Effective attack / defense7.21 / 5.22
Effective home matches2.13
Effective home attack / defense3.11 / 2.13
Mainz 05
Total matches141
Home / away matches71 / 70
xG matches141 / 141
xG home / away coverage71 / 71 · 70 / 70
Effective total27.98
Effective attack / defense42.48 / 27.98
Effective away matches13.62
Effective away attack / defense20.84 / 13.62
Historical data coverage
26.82%
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 1249 historical matches.
Positive improvement means the model performed better than the league baseline.
Total goals log-loss vs baseline+1.19%
1X2 log-loss vs baseline+7.92%
BTTS Brier vs baseline+0.78%
Over 2.5 Brier vs baseline+2.40%
Full backtest metrics
Model
MAE total goals1.3963
Exact score log-loss3.1021
Total goals Brier0.8384
Total goals log-loss1.9562
1X2 Brier0.5886
1X2 log-loss0.9889
BTTS Brier0.2385
Over 1.5 Brier0.1358
Over 2.5 Brier0.2321
Over 3.5 Brier0.2377
League baseline
MAE total goals1.4093
Exact score log-loss3.2441
Total goals Brier0.8429
Total goals log-loss1.9798
1X2 Brier0.6498
1X2 log-loss1.0740
BTTS Brier0.2404
Over 1.5 Brier0.1375
Over 2.5 Brier0.2378
Over 3.5 Brier0.2474
Calibration diagnostics
Home win · ECE 3.36%
0- 10% n=25 avg= 7.5% actual= 8.0% 10- 20% n=80 avg= 16.0% actual= 17.5% 20- 30% n=183 avg= 25.9% actual= 21.3% 30- 40% n=279 avg= 35.3% actual= 38.4% 40- 50% n=277 avg= 44.9% actual= 43.0% 50- 60% n=182 avg= 54.3% actual= 53.8% 60- 70% n=125 avg= 64.4% actual= 73.6% 70- 80% n=64 avg= 74.4% actual= 73.4% 80- 90% n=30 avg= 84.4% actual= 93.3% 90-100% n=4 avg= 91.5% actual= 25.0%
Draw · ECE 1.45%
0- 10% n=14 avg= 8.1% actual= 14.3% 10- 20% n=158 avg= 16.1% actual= 17.7% 20- 30% n=1008 avg= 25.9% actual= 26.5% 30- 40% n=69 avg= 31.0% actual= 18.8%
Away win · ECE 2.01%
0- 10% n=74 avg= 6.6% actual= 6.8% 10- 20% n=214 avg= 15.4% actual= 12.1% 20- 30% n=338 avg= 25.0% actual= 26.0% 30- 40% n=281 avg= 34.7% actual= 35.6% 40- 50% n=178 avg= 44.2% actual= 41.6% 50- 60% n=86 avg= 54.4% actual= 57.0% 60- 70% n=47 avg= 64.1% actual= 61.7% 70- 80% n=22 avg= 74.8% actual= 59.1% 80- 90% n=9 avg= 82.6% actual= 88.9%
BTTS · ECE 1.91%
40- 50% n=85 avg= 47.7% actual= 49.4% 50- 60% n=766 avg= 55.8% actual= 56.3% 60- 70% n=378 avg= 63.4% actual= 68.3% 70- 80% n=20 avg= 71.0% actual= 70.0%
Over 2.5 · ECE 4.25%
30- 40% n=21 avg= 37.7% actual= 42.9% 40- 50% n=215 avg= 46.4% actual= 50.7% 50- 60% n=543 avg= 55.2% actual= 60.4% 60- 70% n=343 avg= 64.3% actual= 67.3% 70- 80% n=107 avg= 73.7% actual= 76.6% 80- 90% n=20 avg= 83.4% actual= 80.0%
Walk-forward - latest periods
| Period | N | Model 1X2 LL | Baseline 1X2 LL | Improvement |
|---|---|---|---|---|
| 2025-09 | 27 | 0.8925 | 1.0895 | +18.08% |
| 2025-10 | 28 | 0.8254 | 1.0409 | +20.70% |
| 2025-11 | 35 | 0.9936 | 1.0578 | +6.06% |
| 2025-12 | 27 | 1.0363 | 1.0708 | +3.22% |
| 2026-01 | 42 | 1.0133 | 1.0827 | +6.41% |
| 2026-02 | 35 | 0.9249 | 1.0164 | +9.00% |
| 2026-03 | 31 | 0.8909 | 1.0953 | +18.66% |
| 2026-04 | 36 | 0.9567 | 1.1201 | +14.58% |
| 2026-05 | 27 | 1.1104 | 1.0679 | -3.97% |
| 2026-08 | 9 | 0.8221 | 0.9155 | +10.20% |
| 2026-09 | 27 | 0.9516 | 1.0644 | +10.61% |
| 2026-10 | 9 | 1.1236 | 1.0674 | -5.26% |
Football is data.
NILYTIX turns match data into transparent model probabilities and measurable analytical signals.