Eredivisie · Netherlands · Regular Season - 1

Sparta Rotterdam–Feyenoord

0–1

HT 0–1

Kick-off: Sunday, 9 August 2026 at 10:15
Status: Match Finished
Venue: Sparta Stadion Het Kasteel, Rotterdam

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

35'FeyenoordL. Valente (assist: G. Zechiël)

Match statistics

Match statistics
Sparta Rotterdam		Feyenoord
10	Shots	22
0	Shots on target	6
8	Shots inside the box	17
6	Goalkeeper saves	1
5	Corners	10
5	Offsides	2
40%	Possession	60%
336	Passes	510
257	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Sparta Rotterdam 1.21 · Feyenoord 1.79. On the pitch: 0-1.
Shots Sparta Rotterdam 10 · Feyenoord 22; on target 0 and 6.
Feyenoord kept the ball more (60%).

Unavailable players

Sparta Rotterdam

J. Baasout · yellow-card suspension

Feyenoord

B. Nieuwkoopout · injury
G. Smalout · Ankle Injury
J. Bosout · Knee Injury
J. Moderout · Knee Injury
T. Beelenout · Broken Leg
T. Watanabeout · Ribs Injury

Provider data — may change until the line-ups are announced. Last updated: Wednesday, 16 September 2026 at 15:10.

Referee

Sander van der Eijk, Netherlands→

3.91

yellows per match

0.64

reds per match

matches of data

11 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 50.8%: “Feyenoord to win”. Second comes “a draw” at 25.0%.
Behind that distribution are the expected goals: 1.21 for Sparta Rotterdam, 1.79 for Feyenoord.
The highest double chance value is 75.8% (X2 — draw or Feyenoord win).
These values were computed from 1,229 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.

Sparta Rotterdam to win24.2%

Draw25.0%

Feyenoord to win50.8%

When the model has said 50–55% in the past, 1,337 of 2,542 predictions were correct (52.6%). Accuracy record →

11	Fouls	8

3	Yellow cards	1

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.

When the model has said 60–65% in the past, 1,567 of 2,553 predictions were correct (61.4%). Accuracy record →

Double chance

1X — Sparta Rotterdam win or draw49.2%

12 — any result other than a draw75.0%

X2 — draw or Feyenoord win75.8%

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 (25.0%).

First half

Actual: 0–1

Sparta Rotterdam lead at half-time24.9%

Level at half-time42.8%

Feyenoord lead at half-time32.3%

First-half double chance

1X — Sparta Rotterdam ahead or level67.7%

12 — not level at half-time57.2%

X2 — level or Feyenoord ahead75.1%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 1229 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

Sparta Rotterdam: at least 10Actual: 11
Feyenoord: at least 9Actual: 8

Corners

Sparta Rotterdam: at least 3Actual: 5
Feyenoord: at least 6Actual: 10

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

The 3+ goals prediction is not published for this match.

The model gives a probability below the baseline (60.1%). In backtesting the model's edge in the "fewer goals" direction could not be confirmed; we don't publish an unconfirmed prediction.

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 Sparta Rotterdam score1.21

Attack: Sparta Rotterdam score close to the league average.

Opponent's defence: Feyenoord concede 24% fewer than the league average, which pulls the expectation down.

Result: These two effects give an expectation of 1.21 goals (including home advantage).

How many goals Feyenoord score1.79

Attack: Feyenoord score above the league average (29% more).

Opponent's defence: Sparta Rotterdam's defence is close to the league average (1.01×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.79 goals (including the away penalty).

Most likely scorelines

1–112.2%1–210.7%0–18.0%

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 1229 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.