Everything on this tab comes from one score matrix: the LOAD90 forecast (EloLambda with attack and defence, availability, playing style and High Congestion) turned into a probability for every scoreline with the Dixon–Coles low-score correction. Fair odds are 1 ÷ probability, with no bookmaker margin. This is a probability model, not betting advice; for odds and value see eScored.
How this opponent changes expected goals compared with an average opponent from each team's domestic league.
VfB StuttgartBaseline: average Bundesliga opponent
Atletico MadridBaseline: average La Liga opponent
The same LOAD90 model is run against a virtual opponent with the league's average Elo, raw attack and defence parameters and standardised possession, with no extra absences or high congestion. Your team's strength, squad availability, congestion and the match's venue context are kept. This measures opponent opportunity, not a change in your team's form. Positive attack change is favorable; negative conceding change is favorable. Clean-sheet changes are percentage points. Values are locked at kick-off.
| VfB Stuttgart ↓ · Atletico Madrid → | 0 | 1 | 2 | 3 | 4 | 5 | 6+ |
|---|---|---|---|---|---|---|---|
| 0 | 3.8 | 6.0 | 6.3 | 4.1 | 2.0 | 0.8 | 0.4 |
| 1 | 4.3 | 9.9 | 9.2 | 6.0 | 2.9 | 1.1 | 0.5 |
| 2 | 3.5 | 6.8 | 6.7 | 4.3 | 2.1 | 0.8 | 0.4 |
| 3 | 1.7 | 3.3 | 3.2 | 2.1 | 1.0 | 0.4 | 0.2 |
| 4 | 0.6 | 1.2 | 1.2 | 0.8 | 0.4 | 0.1 | 0.1 |
| 5 | 0.2 | 0.3 | 0.3 | 0.2 | 0.1 | 0.0 | 0.0 |
| 6+ | 0.1 | 0.1 | 0.1 | 0.1 | 0.0 | 0.0 | 0.0 |
Chance of each exact score, in %. Rows are VfB Stuttgart goals, columns Atletico Madrid goals; 6+ adds up six goals or more.
| LOAD90 | EloLambda | Change | |
|---|---|---|---|
| VfB Stuttgart win | 28.2% | 28.1% | +0.1 pp |
| Draw | 22.9% | 23.6% | -0.6 pp |
| Atletico Madrid win | 48.9% | 48.3% | +0.6 pp |
| Over 2.5 | 66.1% | 63.2% | +2.9 pp |
| Both teams score | 66.2% | 64.0% | +2.2 pp |
| Expected goals VfB Stuttgart | 1.45 | 1.39 | +0.06 |
| Expected goals Atletico Madrid | 1.95 | 1.87 | +0.08 |
EloLambda is the stable eScored model without the LOAD90 factors. The change column is what playing style and High Congestion add for this match; see the methodology.
Corners, cards and shots are not forecast by LOAD90; their actual averages are on the Overview tab.
All LOAD90 forecasts before this match.
| Favourite chance | Matches | Predicted | Actually won |
|---|---|---|---|
| 30–40% | 2 | 39.6% | 0.0% |
| 40–50% | 13 | 45.7% | 69.2% |
| 50–60% | 9 | 55.5% | 77.8% |
| 60–70% | 4 | 65.7% | 75.0% |
| 70–80% | 1 | 79.1% | 100.0% |
| 80%+ | 6 | 85.0% | 83.3% |
Compared on the same 35 of 35 scored matches.
| LOAD90 | Bookmaker | |
|---|---|---|
| 1X2 Brier (lower is better) | 0.4618 | 0.4614 |
| Avg chance given to result | 49.9% | 50.9% |
| Favourite won | 71.4% | 65.7% |
Bookmaker probabilities come from pre-match 1X2 odds supplied by eScored, with the margin removed. Prices may have been recorded at different times before kick-off. Bookmaker identity is unavailable for 17 archived lines; these prices may come from different bookmakers.
Pre-match forecasts only. 16 of 35 were published live before kick-off; the rest were rebuilt after the match from pre-match data, never using the result. Numbers are home · draw · away chances, the actual result in bold. A good model's favourites in the 60–70% row should win about 65% of the time.
