Home win
33.64%
Getafe
ESP1 · La Liga · Match Analysis
Getafe vs
Rayo Vallecano
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
33.07%
X
Away win
33.29%
Rayo Vallecano
Score model
Most likely scorelines.
Exact-score probabilities from the Poisson + Dixon-Coles goal model.
Additional scorelines
0:26.72%
2:16.65%
1:26.61%
2:23.25%
3:02.23%
Team context
Strength and recent form.
Venue-adjusted team strength, Elo rating and recent xG performance.
Home
Getafe
Elo1482.9
Overall attack0.89
Overall defense1.22
Home attack0.99
Home defense0.98
Form signal-0.711
Last 5 xGF / xGA0.53 / 1.24
Last 10 xGF / xGA0.55 / 1.26
Last 10 xGD-0.72
League statusSTABLE · from ESP1 2025/26
Away
Rayo Vallecano
Elo1515.4
Overall attack1.30
Overall defense1.35
Away attack1.14
Away defense1.60
Form signal-0.203
Last 5 xGF / xGA1.33 / 1.51
Last 10 xGF / xGA1.30 / 1.55
Last 10 xGD-0.25
League statusSTABLE · from ESP1 2025/26
Elo difference
-32.5
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.
Goal distribution
Total goals profile.
The model's probability distribution for the total number of goals.
015.00%
125.76%
227.98%
317.68%
48.67%
53.40%
61.11%
7+0.41%
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
LeagueESP1
Loaded teams29
Loaded historical matches1598
Target season2026/27
Previous seasons in history4
Season window2022/23 → 2023/24 → 2024/25 → 2025/26 → 2026/27
League tierTier 1
Historical league matches1598
xG matches1598 / 1598
Effective xG matches814.56
Observed home xG1.52
Observed away xG1.17
Model home xG baseline1.52
Model away xG baseline1.17
Total league xG baseline2.68
Home-advantage weight1.006
Model configdata/models/ESP1.json
Team attack half-life365.0 days
Team defense half-life365.0 days
Attack strength weight1.113
Defense strength weight1.038
Venue prior matches5.00
DistributionPoisson + Dixon-Coles
Dixon-Coles rho-0.068 (effective -0.068)
Dixon-Coles decay0.006
Goal overdispersion0.000
Implied goal variance H / A0.98 / 0.98
Relative strengths and form diagnostics
Getafe
Home attack strength0.711
Home defense weakness0.874
Base lambda home1.08
Attack form xGF level0.537
Defense form xGA level (lower is better)1.247
Opponent-adjusted attack residual-0.781
Opponent-adjusted defense residual (higher is better)+0.129
Opponent-adjustment weight0.000
Model attack signal-0.806
Model defense signal+0.095
Opponent blend0.000
Form matches 5 / 105 / 10
Last 5 xGF / xGA / xGD0.53 / 1.24 / -0.71
Last 10 xGF / xGA / xGD0.55 / 1.26 / -0.72
Rayo Vallecano
Away attack strength0.981
Away defense weakness1.040
Base lambda away0.99
Attack form xGF level1.321
Defense form xGA level (lower is better)1.524
Opponent-adjusted attack residual+0.022
Opponent-adjusted defense residual (higher is better)-0.133
Opponent-adjustment weight0.000
Model attack signal-0.021
Model defense signal-0.181
Opponent blend0.000
Form matches 5 / 105 / 10
Last 5 xGF / xGA / xGD1.33 / 1.51 / -0.18
Last 10 xGF / xGA / xGD1.30 / 1.55 / -0.25
Historical data coverage
Getafe
Total matches160
Home / away matches80 / 80
xG matches160 / 160
xG home / away coverage80 / 80 · 80 / 80
Effective total49.57
Effective attack / defense49.57 / 49.57
Effective home matches24.87
Effective home attack / defense24.87 / 24.87
Rayo Vallecano
Total matches159
Home / away matches79 / 80
xG matches159 / 159
xG home / away coverage79 / 79 · 80 / 80
Effective total48.62
Effective attack / defense48.62 / 48.62
Effective away matches24.45
Effective away attack / defense24.45 / 24.45
Historical data coverage
96.10%
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 1578 historical matches.
Positive improvement means the model performed better than the league baseline.
Total goals log-loss vs baseline+1.53%
1X2 log-loss vs baseline+8.46%
BTTS Brier vs baseline+0.35%
Over 2.5 Brier vs baseline+3.43%
Full backtest metrics
Model
MAE total goals1.2686
Exact score log-loss2.8030
Total goals Brier0.8153
Total goals log-loss1.8368
1X2 Brier0.5779
1X2 log-loss0.9733
BTTS Brier0.2478
Over 1.5 Brier0.1908
Over 2.5 Brier0.2410
Over 3.5 Brier0.1840
League baseline
MAE total goals1.3152
Exact score log-loss2.9255
Total goals Brier0.8204
Total goals log-loss1.8654
1X2 Brier0.6420
1X2 log-loss1.0633
BTTS Brier0.2487
Over 1.5 Brier0.1953
Over 2.5 Brier0.2495
Over 3.5 Brier0.1904
Calibration diagnostics
Home win · ECE 2.73%
0- 10% n=9 avg= 8.4% actual= 11.1% 10- 20% n=97 avg= 15.9% actual= 20.6% 20- 30% n=220 avg= 25.5% actual= 23.6% 30- 40% n=339 avg= 35.3% actual= 36.3% 40- 50% n=393 avg= 44.7% actual= 46.1% 50- 60% n=231 avg= 54.5% actual= 55.8% 60- 70% n=144 avg= 64.4% actual= 69.4% 70- 80% n=99 avg= 74.5% actual= 87.9% 80- 90% n=46 avg= 83.0% actual= 87.0%
Draw · ECE 1.95%
0- 10% n=6 avg= 9.0% actual= 0.0% 10- 20% n=198 avg= 16.0% actual= 9.6% 20- 30% n=1141 avg= 26.3% actual= 27.5% 30- 40% n=233 avg= 31.4% actual= 29.6%
Away win · ECE 2.89%
0- 10% n=122 avg= 7.2% actual= 6.6% 10- 20% n=286 avg= 15.3% actual= 13.6% 20- 30% n=459 avg= 24.9% actual= 20.7% 30- 40% n=341 avg= 34.3% actual= 32.8% 40- 50% n=202 avg= 44.4% actual= 46.0% 50- 60% n=105 avg= 54.6% actual= 57.1% 60- 70% n=42 avg= 64.4% actual= 45.2% 70- 80% n=18 avg= 73.2% actual= 77.8% 80- 90% n=3 avg= 81.7% actual=100.0%
BTTS · ECE 3.15%
30- 40% n=67 avg= 37.8% actual= 47.8% 40- 50% n=729 avg= 45.9% actual= 50.6% 50- 60% n=662 avg= 54.0% actual= 53.6% 60- 70% n=115 avg= 63.1% actual= 67.8% 70- 80% n=5 avg= 73.1% actual= 60.0%
Over 2.5 · ECE 1.86%
20- 30% n=21 avg= 27.7% actual= 38.1% 30- 40% n=277 avg= 36.4% actual= 33.6% 40- 50% n=624 avg= 45.0% actual= 46.0% 50- 60% n=396 avg= 54.5% actual= 52.8% 60- 70% n=191 avg= 64.4% actual= 64.4% 70- 80% n=66 avg= 73.7% actual= 65.2% 80- 90% n=3 avg= 81.2% actual=100.0%
Walk-forward - latest periods
| Period | N | Model 1X2 LL | Baseline 1X2 LL | Improvement |
|---|---|---|---|---|
| 2025-09 | 39 | 0.9408 | 1.0522 | +10.58% |
| 2025-10 | 31 | 1.0046 | 1.0833 | +7.27% |
| 2025-11 | 38 | 0.8748 | 1.0447 | +16.26% |
| 2025-12 | 32 | 0.9668 | 1.0451 | +7.49% |
| 2026-01 | 43 | 0.9594 | 1.0625 | +9.71% |
| 2026-02 | 40 | 0.9680 | 1.0579 | +8.49% |
| 2026-03 | 36 | 0.9530 | 1.0198 | +6.56% |
| 2026-04 | 40 | 1.0503 | 1.0215 | -2.82% |
| 2026-05 | 50 | 1.0095 | 1.0529 | +4.12% |
| 2026-08 | 30 | 0.9317 | 1.0290 | +9.46% |
| 2026-09 | 39 | 0.9791 | 1.0986 | +10.88% |
| 2026-10 | 9 | 0.9149 | 1.0794 | +15.24% |
Football is data.
NILYTIX turns match data into transparent model probabilities and measurable analytical signals.