Jupiler Pro League · Belgium · Regular Season - 2

Union St. Gilloise–Zulte Waregem

0–0

HT 0–0

Kick-off: Saturday, 15 August 2026 at 14:00
Status: Match Finished
Venue: Stade Joseph Marien, Brussels

What the model said, and what happened

Ended level — we gave the draw 22%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

Match statistics

Match statistics
Union St. Gilloise		Zulte Waregem
9	Shots	11
3	Shots on target	4
7	Shots inside the box	9
4	Goalkeeper saves	3
9	Corners	3
4	Offsides	0
68%	Possession	32%
546	Passes	254
469	Accurate passes

What we expected, and what happened

Expected goals before kick-off: Union St. Gilloise 1.94 · Zulte Waregem 0.71. On the pitch: 0-0.
Shots Union St. Gilloise 9 · Zulte Waregem 11; on target 3 and 4.
Union St. Gilloise kept the ball more (68%).

Referee

Lothar D'hondt, Belgium→

4.41

yellows per match

0.24

reds per match

matches of data

Model prediction

Why this prediction?

The model puts the most likely outcome at 67.0%: “Union St. Gilloise to win”. Second comes “a draw” at 21.6%.
Behind that distribution are the expected goals: 1.94 for Union St. Gilloise, 0.71 for Zulte Waregem.
The highest double chance value is 88.6% (1X — Union St. Gilloise win or draw).
These values were computed from 1,136 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.

Union St. Gilloise to win67.0%

Draw21.6%

Zulte Waregem to win11.4%

When the model has said 65–70% in the past, 1,092 of 1,602 predictions were correct (68.2%). Accuracy record →

14	Fouls	13

2	Yellow cards	0

0	Red cards	0

First half

Actual: 0–0

Union St. Gilloise lead at half-time54.9%

Level at half-time36.0%

Zulte Waregem lead at half-time9.1%

First-half double chance

1X — Union St. Gilloise ahead or level90.9%

12 — not level at half-time64.0%

X2 — level or Zulte Waregem ahead45.1%

These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 1136 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

Union St. Gilloise: at least 11Actual: 14
Zulte Waregem: at least 10Actual: 13

Corners

Union St. Gilloise: at least 5Actual: 9
Zulte Waregem: 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.

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 Union St. Gilloise score1.94

Attack: Union St. Gilloise score above the league average (18% more).

Opponent's defence: Zulte Waregem's defence is close to the league average (1.04×), so it doesn't move the expectation much.

Result: These two effects give an expectation of 1.94 goals (including home advantage).

How many goals Zulte Waregem score0.71

Attack: Zulte Waregem score close to the league average.

Opponent's defence: Union St. Gilloise concede 39% below the league average — a defence that seriously brakes even a strong attack.

Result: These two effects give an expectation of 0.71 goals (including the away penalty).

Most likely scorelines

2–013.8%1–013.1%1–110.9%

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.

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.