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Trap bias at Perry Barr: which traps actually win

··5 min read

Trap bias at Perry Barr measured on 2,262 races over 2 years: share of wins by trap against fair share, by distance and by grade, with the noise called noise.

trap biastrack geometryperry barr

Over the last 2 years at Perry Barr, 2,262 races, trap 3 has been a clear plus at +3.1 points against its fair share and trap 5 a clear minus at -2.5; the other traps sit inside noise. The track is 435 metres round with 80 metres to the first bend, measured from our own split times.

Share of wins by trap at Perry Barr against fair share
Share of wins by trap at Perry Barr against fair share

All distances

Trap Runs Wins Win rate Share of wins Fair share Bias Read
1 2,187 416 19.0% 18.4% 17.1% +1.3 noise
2 2,224 390 17.5% 17.2% 17.4% -0.1 noise
3 2,219 463 20.9% 20.5% 17.3% +3.1 clear
4 2,208 380 17.2% 16.8% 17.2% -0.4 noise
5 2,107 315 15.0% 13.9% 16.5% -2.5 clear
6 1,856 298 16.1% 13.2% 14.5% -1.3 noise

Trap 1 sits inside noise at +1.3 points. Trap 2 sits inside noise at -0.1 points. Trap 3 is a clear plus at Perry Barr: it wins 20.5% of races against a fair share of 17.3%, +3.1 points on 2,219 runs. Trap 4 sits inside noise at -0.4 points. Trap 5 is a clear minus: 13.9% of wins against a fair share of 16.5%, -2.5 points on 2,107 runs. Trap 6 sits inside noise at -1.3 points.

By distance

Only distances with at least 1,500 runs get their own chart; a bias that shows at one trip and not another is usually the run to the first bend at work.

480 metres, 1,637 races

Share of wins by trap at Perry Barr over 480 metres
Share of wins by trap at Perry Barr over 480 metres

Trap 1 sits inside noise at +1.5 points. Trap 2 sits inside noise at +0.2 points. Trap 3 is a clear plus at Perry Barr: it wins 21.6% of races against a fair share of 17.5%, +4.2 points on 1,606 runs. Trap 4 sits inside noise at +0.1 points. Trap 5 is a clear minus: 12.5% of wins against a fair share of 16.5%, -4.0 points on 1,517 runs. Trap 6 sits inside noise at -1.9 points.

275 metres, 586 races

Share of wins by trap at Perry Barr over 275 metres
Share of wins by trap at Perry Barr over 275 metres

No clear bias at 275 metres: every trap is inside noise on 586 races.

By grade

Grade letters grouped: A for graded races, D for sprints and dashes where the track uses them, S for stayers, and so on.

Grade Races T1 T2 T3 T4 T5 T6
A 1,438 +1.7 +0.4 +3.7* +0.1 -4.0* -1.8
D 554 +1.0 -1.0 +0.6 -2.4 +1.8 -0.0

Bias in points against fair share; * marks a clear bias.

The market and the fields

The Betfair favourite won 34.2% of 2,251 priced races here over the window. 79% of races went off with six runners; the rest had a vacant trap, which is why fair share is measured on runs and not assumed to be one sixth.

How to read this

Fair share is each trap's share of the runs, so a vacant trap 6 does not hand trap 5 a bias. A bias is called clear only when it is at least 1.5 points and at least 2.5 standard errors from fair on the runs behind it; anything smaller is a difference inside noise, and the page says so. The window is the last 2 years, refreshed whenever this page is rebuilt. The live version, with the going and our own accuracy at this track, is on the track page.

Questions this piece answers

Which trap wins most at Perry Barr?

Over the last 2 years trap 3 has the largest share of wins, 20.5% of 2,262 races. Against fair share the picture is: Trap 3 is a clear plus at Perry Barr: it wins 20.5% of races against a fair share of 17.3%, +3.1 points on 2,219 runs. Trap 5 is a clear minus: 13.9% of wins against a fair share of 16.5%, -2.5 points on 2,107 runs.

How is fair share worked out?

Each trap's fair share is its share of the runs, not one sixth. A trap that was vacant in many races has fewer runs and so a smaller fair share; comparing its wins with a sixth would invent a bias.

How often does the favourite win at Perry Barr?

The Betfair market favourite won 34.2% of 2,251 races with a settled price over the last 2 years.

T
The Edge AnalystGreyhound racing and statistical analysis

The analyst behind TrapMetrics: the person who built the rating model, runs it every morning, and writes up what it finds. About the writer

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