Championship · England · Regular Season - 2

Birmingham–Bristol City

2–2

HT 1–1

Kick-off: Saturday, 22 August 2026 at 11:30
Status: Match Finished
Venue: St. Andrew's @ Knighthead Park, Birmingham

What the model said, and what happened

Ended level — we gave the draw 28%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

33'Bristol CityS. Twine
42'BirminghamS. Tickle (own goal)
85'Bristol CityD. Ballard (assist: Rio Cardines)
90+5'BirminghamD. Gray (penalty)

Match statistics

Match statistics
Birmingham		Bristol City
4	Shots	11
1	Shots on target	3
2	Shots inside the box	10
2	Goalkeeper saves	0
5	Corners	2
1	Offsides	1
63%	Possession	37%
364	Passes	211
272	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Birmingham 1.52 · Bristol City 0.94. On the pitch: 2-2.
Shots Birmingham 4 · Bristol City 11; on target 1 and 3.
Birmingham kept the ball more (63%).

Unavailable players

Birmingham

L. Buchananout · Knee Injury
M. Leonardout · Achilles Tendon Injury
T. Gardner-Hickmanout · injury

Bristol City

A. Randellout · red-card suspension
C. Pringout · Ankle Injury
L. McNallyout · Knee Injury

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

Referee

Will Finnie, England→

2.80

yellows per match

0.00

reds per match

matches of data

5 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 50.3%: “Birmingham to win”. Second comes “a draw” at 27.7%.
Behind that distribution are the expected goals: 1.52 for Birmingham, 0.94 for Bristol City.
The highest double chance value is 77.9% (1X — Birmingham win or draw).
These values were computed from 2,220 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.

Birmingham to win50.3%

Draw27.7%

Bristol City to win22.1%

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

10	Fouls	7

1	Yellow cards	0

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 — Birmingham win or draw77.9%

12 — any result other than a draw72.3%

X2 — draw or Bristol City win49.7%

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 (27.7%).

First half

Actual: 1–1

Birmingham lead at half-time36.0%

Level at half-time41.5%

Bristol City lead at half-time22.5%

First-half double chance

1X — Birmingham ahead or level77.5%

12 — not level at half-time58.5%

X2 — level or Bristol City ahead64.0%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 2220 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

Birmingham: at least 11Actual: 10
Bristol City: at least 9Actual: 7

Corners

Birmingham: at least 5Actual: 5
Bristol City: at least 3Actual: 2

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 (48.0%). 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 Birmingham score1.52

Attack: Birmingham score close to the league average.

Opponent's defence: Bristol City's defence is close to the league average (1.07×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.52 goals (including home advantage).

How many goals Bristol City score0.94

Attack: Bristol City score close to the league average.

Opponent's defence: Birmingham concede 16% fewer than the league average, which pulls the expectation down.

Result: These two effects give an expectation of 0.94 goals (including the away penalty).

Most likely scorelines

1–114.0%1–012.2%2–110.2%

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 2220 matches played in this league before kick-off; the team with fewer has 139 matches. No data from after the match was used. The model's track record is published unfiltered.

Week 2 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.