1 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 48.6%: “Plzen to win”. Second comes “a draw” at 27.4%.
·Behind that distribution are the expected goals: 1.03 for Teplice, 1.54 for Plzen.
·The highest double chance value is 76.0% (X2 — draw or Plzen win).
·These values were computed from 1,036 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.
Teplice to win24.0%
Draw27.4%
Plzen to win48.6%
When the model has said 45–50% in the past, 2,070 of 4,392 predictions were correct (47.1%). Accuracy record →
⚽
Teplice
M. Cermak (assist: M. Radosta)
54'⚽TepliceJ. Auta (assist: M. Radosta)
58'⚽TepliceJan Fortelný (assist: L. Marecek)
68'⚽PlzenD. Višinský (assist: A. Memić)
88'PlzenDávid Krčík · red card
406
12
Fouls
19
3
Yellow cards
1
0
Red cards
1
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.
Both teams to score
53.6%
When the model has said 50–55% in the past, 3,613 of 7,010 predictions were correct (51.5%). Accuracy record →
Double chance
1X — Teplice win or draw51.4%
12 — any result other than a draw72.6%
X2 — draw or Plzen win76.0%
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 (27.4%).
First half
Actual: 3–4
Teplice lead at half-time15.7%
Level at half-time41.1%
Plzen lead at half-time43.2%
First-half double chance
1X — Teplice ahead or level56.8%
12 — not level at half-time58.9%
X2 — level or Plzen ahead84.3%
These values are not a fraction of the full-match prediction; they come from a separate model trained on the first-half scores of 1036 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
Teplice
at least 12Actual: 12
Plzen
at least 12Actual: 19
Corners
Teplice
at least 3Actual: 4
Plzen
at least 4Actual: 1
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 (53.6%). 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 Teplice score1.03
Attack: Teplice score below the league average (20% fewer).
Opponent's defence: Plzen concede 17% fewer than the league average, which pulls the expectation down.
Result: These two effects give an expectation of 1.03 goals (including home advantage).
How many goals Plzen score1.54
Attack: Plzen score above the league average (27% more).
Opponent's defence: Teplice's defence is close to the league average (0.98×), so it doesn't move the expectation much.
Result: These two effects give an expectation of 1.54 goals (including the away penalty).
Most likely scorelines
1–113.9%0–111.0%1–210.3%
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 1036 matches played in this league before kick-off; the team with fewer has 122 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.
