Bundesliga · Germany · Regular Season - 1

Bayern München–VfB Stuttgart

5–1

HT 1–0

Kick-off: Friday, 28 August 2026 at 18:30
Status: Match Finished

What the model said, and what happened

Prediction correct

This verdict goes into the public record unchanged; we do not filter out the ones we get wrong. The model's track record

Goals and red cards

21'Bayern MünchenD. Upamecano (assist: J. Kimmich)
52'VfB StuttgartJ. Vagnoman
55'Bayern MünchenM. Olise (assist: J. Kimmich)
57'Bayern MünchenJ. Vagnoman (own goal)
82'Bayern MünchenA. Pavlović (assist: I. Saibari)
90+2'Bayern MünchenL. Díaz (assist: I. Saibari)

Match statistics

Match statistics
Bayern München		VfB Stuttgart
20	Shots	11
8	Shots on target	4
13	Shots inside the box	7
3	Goalkeeper saves	5
9	Corners	3
2	Offsides	1
58%	Possession	42%
506	Passes	353
414	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Bayern München 2.79 · VfB Stuttgart 1.15. On the pitch: 5-1.
Shots Bayern München 20 · VfB Stuttgart 11; on target 8 and 4.
Bayern München kept the ball more (58%).

Unavailable players

Bayern München

B. Zaragozaout · Knee Injury
J. Musialaout · Health problems
S. Gnabryout · Muscle Injury
T. Buchmannout · Knee Injury
L. Karldoubtful · Thigh Injury

VfB Stuttgart

C. Fuhrichout · Muscle Injury
D. Seimenout · Thigh Injury
D. Zagadouout · Muscle Injury
J. Arevaloout · Back Injury
J. Diehlout · Muscle Injury
L. Assignonout · Shoulder Injury
L. Jaquezout · Muscle Injury
L. Sauerout · Muscle Injury
N. Nartey

Referee

Sören Storks, Germany→

5.23

yellows per match

0.46

reds per match

matches of data

13 matches is a small sample — these averages are noisy and should not be read as a tendency.

Model prediction

Why this prediction?

The model puts the most likely outcome at 78.9%: “Bayern München to win”. Second comes “a draw” at 12.8%.
Behind that distribution are the expected goals: 3.21 for Bayern München, 1.13 for VfB Stuttgart.
The highest double chance value is 91.6% (1X — Bayern München win or draw).
These values were computed from 1,224 past matches.

This is a prediction, not a guarantee; a probability is not a certainty.

These sentences are built by a fixed template; every number in them comes straight from the model's computation, none invented while the text was written.

Bayern München to win78.9%

Draw12.8%

VfB Stuttgart to win8.4%

When the model has said 75–80% in the past, 449 of 540 predictions were correct (83.1%). Accuracy record →

10	Fouls	15

1	Yellow cards	2

0	Red cards	0

The measurements our data provider sent for this match. A row that was not measured shows “—”; writing 0 into an empty field would claim we measured it and found none.

Provider data — may change until the line-ups are announced. Last updated: Wednesday, 16 September 2026 at 15:11.

When the model has said 65–70% in the past, 575 of 859 predictions were correct (66.9%). Accuracy record →

Double chance

1X — Bayern München win or draw91.6%

12 — any result other than a draw87.2%

X2 — draw or VfB Stuttgart win21.1%

These three values add up to 200%, not 100% — and that is not a mistake. The options are not mutually exclusive; every outcome is counted in two of them. For the same reason 1X plus X2 exceeds 100% by exactly the probability of a draw (12.8%).

First half

Actual: 1–0

Bayern München lead at half-time49.8%

Level at half-time33.4%

VfB Stuttgart lead at half-time16.8%

First-half double chance

1X — Bayern München ahead or level83.2%

12 — not level at half-time66.6%

X2 — level or VfB Stuttgart ahead50.2%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 1224 matches. Its edge over the base rate is markedly smaller than the full-match model's — the measured figure is on the accuracy record. Read them more cautiously. First-half goal markets are not published because they failed to beat the base rate.

Expected fouls and corners

Fouls

Bayern München: at least 9Actual: 10
VfB Stuttgart: at least 8Actual: 15

Corners

Bayern München: at least 5Actual: 9
VfB Stuttgart: at least 3Actual: 3

These figures are set to hold in at least 60% of matches; in the rest the count comes in below them. No upper bound is stated — we make no "at most" claim. Yellow cards were measured and are not published: there our model did not beat the historical average.

Goals market

3+ goals82.3%

When the model has said 80–85% in the past, 43 of 53 predictions were correct (81.1%). Accuracy record →

The league's historical "3+ goals" rate is 61.6%. For this match the model gives a value above that baseline — and in backtesting the model's edge was confirmed only in this direction.

What these probabilities rest on

Expected goals comes out of a team's attack weighed against its opponent's defence. A strong attack is damped when it meets a strong defence — which is why comparing the ratings on their own is misleading.

How many goals Bayern München score2.79

Attack: Bayern München score 85% more than the league's average team — one of the sharpest attacks in the league.

Opponent's defence: VfB Stuttgart's defence is close to the league average (0.94×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 2.79 goals (including home advantage).

How many goals VfB Stuttgart score1.15

Attack: VfB Stuttgart score above the league average (22% more).

Opponent's defence: Bayern München concede 20% fewer than the league average, which pulls the expectation down.

Result: These two effects give an expectation of 1.15 goals (including the away penalty).

Most likely scorelines

3–19.0%2–18.1%3–07.3%

A single scoreline is always less likely than an outcome: “home win” is the sum of 1-0, 2-0, 2-1 and dozens more. So the most likely single score can be a draw while the most likely outcome is a home win; the two do not contradict each other.

Ratings were computed from 1224 matches played in this league before kick-off; the team with fewer has 136 matches. No data from after the match was used. The model's track record is published unfiltered.

Week 1 of the season. This prediction was computed from previous seasons. Summer transfers, budget changes and squad rebuilds aren't in the ratings yet — the model can only see that a team has been rebuilt once new results come in.

We measured this and we're not hiding it: in the opening week of past seasons the model came in 3.3 points below the accuracy it claimed (n=220) — for the rest of the season it beats its own claim. The tendency points this way, though it is not proof on its own: in the opening week it slightly over-calls home wins (said 42.7%, got 39.5%) and slightly under-calls draws (said 26.1%, got 28.2%).

This sample is small and not statistically established, which is why we do not correct the model for it. The correction we tried (pulling probabilities toward the league average) didn't win on holdout, so it wasn't added. Read opening-week predictions with a little more caution.