Championship · England · Regular Season - 3

Derby–Swansea

0–3

HT 0–2

Kick-off: Saturday, 29 August 2026 at 11:30
Status: Match Finished
Venue: Pride Park Stadium, Derby

What the model said, and what happened

Incorrect — we gave this result 30%double chance: 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

2'SwanseaJoseph Okopu (assist: Eom Ji-Sung)
44'SwanseaEom Ji-Sung
90+1'SwanseaRonald (assist: S. Eustáquio)

Match statistics

Match statistics
Derby		Swansea
8	Shots	23
0	Shots on target	12
5	Shots inside the box	15
9	Goalkeeper saves	0
5	Corners	6
5	Offsides	4
47%	Possession	53%
404	Passes	475
308	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Derby 1.39 · Swansea 1.09. On the pitch: 0-3.
Shots Derby 8 · Swansea 23; on target 0 and 12.

Unavailable players

Derby

D. Murkinout · Hamstring Injury
M. Clarkeout · Calf Injury
P. Agyemangout · Achilles Tendon Injury
S. Szmodicsdoubtful · Thigh Injury

Swansea

B. Cabangoout · not in squad
C. Burgessout · Achilles Tendon Injury
G. Francoout · Ankle Injury

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

Referee

David Webb, England→

2.73

yellows per match

0.00

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 41.1%: “Derby to win”. Second comes “Swansea to win” at 29.9%.
Behind that distribution are the expected goals: 1.36 for Derby, 1.13 for Swansea.
The highest double chance value is 71.1% (12 — any result other than a draw).
These values were computed from 2,233 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.

Derby to win41.1%

Draw28.9%

Swansea to win29.9%

When the model has said 40–45% in the past, 1,778 of 3,998 predictions were correct (44.5%). Accuracy record →

16	Fouls	7

3	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.

When the model has said 50–55% in the past, 2,597 of 5,092 predictions were correct (51.0%). Accuracy record →

Double chance

1X — Derby win or draw70.1%

12 — any result other than a draw71.1%

X2 — draw or Swansea win58.9%

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 (28.9%).

First half

Actual: 0–2

Derby lead at half-time38.0%

Level at half-time42.7%

Swansea lead at half-time19.3%

First-half double chance

1X — Derby ahead or level80.7%

12 — not level at half-time57.3%

X2 — level or Swansea ahead62.0%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 2233 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

Derby: at least 12Actual: 16
Swansea: at least 9Actual: 7

Corners

Derby: at least 4Actual: 5
Swansea: at least 3Actual: 6

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 (48.1%). 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 Derby score1.39

Attack: Derby score close to the league average.

Opponent's defence: Swansea's defence is close to the league average (0.95×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.39 goals (including home advantage).

How many goals Swansea score1.09

Attack: Swansea score close to the league average.

Opponent's defence: Derby's defence is close to the league average (0.97×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.09 goals (including the away penalty).

Most likely scorelines

1–114.7%1–010.4%2–19.5%

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 2233 matches played in this league before kick-off; the team with fewer has 94 matches. No data from after the match was used. The model's track record is published unfiltered.

Week 3 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: the bias is only pronounced in the opening week. In this week the model's overall accuracy does not separate from the rest of the season — that is, we found no measurable flaw. The one tendency across all opening weeks is that home wins are called slightly too often (said 43.0%, got 41.9%; n=583).

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.