MERITOCRACY SA RACING INTELLIGENCE
Track Stats

Per-track intelligence: draw bias and speed by distance and going. Use the filters to see how the starting stalls behave on different ground, and how winning times compare across goings at the same track and distance.

How this is calculated

The field-size problem. A raw draw number can't be compared across races: gate 8 is the widest in an 8-runner field but mid-pack in a 16-runner field. So we never judge draws by their number alone. Instead, for every historical race we rank the runners by their draw and split the field into three equal groups by relative position — the inside, middle and outside thirds. A "low" draw therefore means the same thing — bottom third of that field — whether 8 or 18 went to post. This is what makes results from different field sizes directly comparable.

Impact Value (IV). Within each third we compare how often it actually produced winners with how often it would if the draw made no difference at all — i.e. if winners were shared out purely in proportion to how many runners each third held (a third of the runners would take a third of the wins):
IV = (that third's share of all winners) ÷ (its share of all runners). An IV of 1.00 means that part of the draw won exactly its fair share — no bias. 1.30 means it won 30% more often than expected (a real edge); 0.80 means 20% fewer wins than expected (a disadvantage). The same calculation on top-3 finishes gives the Place IV.

Bias strength & the chart. The leaderboard ranks trips by bias strength — the gap between the best and worst third's win IV — so the most lopsided draws rise to the top. The bar chart breaks the same data down to each individual draw number; treat the highest draws cautiously, as fewer big fields means smaller samples there.

Worked example — Greyville 1000m Inside draws there win 13.9% of their starts — that is, of every runner drawn in the inside third, 13.9% went on to win. Divide that by the Win IV of 1.37 and you get ≈ 10.1%, the baseline a neutral draw would manage (and a hint that the average field is about ten runners, since roughly one winner emerges per ten starters). So inside draws win 37% more often than that baseline, while outside draws (7.5%, IV 0.74) win 26% fewer. The place line reads the same way: 35.9% of inside starters finish in the top three, and a Place IV of 1.18 means 18% more top-three finishes than a fair share.

Two things to keep in mind. First, the three win percentages are independent rates, not slices of one pie — each is "of the runners in this third, how many won" — so they won't add up to 100%; they sum to roughly three times the overall win rate. (What does add to 100% is the share of winners each third supplies, since every race has exactly one winner.) Second, the three groups don't each hold exactly a third of the runners when a field doesn't divide evenly by three (an 11-runner field splits roughly 4 / 4 / 3 by draw rank). Impact Value handles this — it divides by each third's actual share of runners, not an assumed 33% — which is why IV, rather than the raw win %, is the figure to trust when comparing the three groups.

Built from historical results from August 2020, counting every runner that took its place in the gates. Only track-and-distance-and-going combinations with enough races are shown, so a single freak meeting can't skew the picture. Polytrack races are identified by Standard going; all other goings are turf.

Inside draws favoured (+21% wins) · Outside -24%
Kenilworth · 1000m · All goings · based on 941 races (9680 runners)
Inside draws
11.8%wins
Win IV 1.21
34.9% placed · Place IV 1.19
Middle draws
10.4%wins
Win IV 1.07
29.8% placed · Place IV 1.02
Outside draws
7.4%wins
Win IV 0.76
24.2% placed · Place IV 0.83
How Impact Value is measured — share of runners vs share of winners
Runners
I 30.0% M 33.2% O 36.8%
Winners
I 36.4% M 35.6% O 28.0%
Inside Middle Outside
Inside draws supplied 36.4% of the winners from 30.0% of the runners — that ratio is the Win IV (1.21). A slice that grows from the top bar to the bottom won more than its share; one that shrinks won less.
Win rate by draw
1
2
3
4
5
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7
8
9
10
11
12
13
14
15
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18
Speed by going — Kenilworth 1000m
Going Races Par time Avg win time Vs good/overall
Heavy (Turf) 34 62.27s 62.30s +5.0% slower
Soft (Turf) 122 61.61s 61.68s +3.9% slower
Yielding (Turf) 101 60.60s 61.10s +2.2% slower
All goings 923 59.62s 59.97s +0.5% slower
Good (Turf) 666 59.32s 59.36s same
Pace over the years — Kenilworth 1000m (All goings)
How to read this

Median winning time for each season at Kenilworth over 1000m on all goings, across the whole stored record. Taller, greener bars are faster seasons; shorter, warmer bars slower — so you can read how the track's pace has drifted from year to year. (The seasonal heatmap below answers a different question: it pools every year into the time of year.) Hover a bar for the numbers; faded bars are low-sample seasons with fewer than 5 timed races.

0.32s slower (0.5%) from 2014 to 2026 · 923 timed races
59.6
2014
59.7
2015
59.6
2016
59.8
2017
59.9
2018
59.8
2019
60.1
2020
60.0
2021
59.4
2022
59.4
2023
58.9
2024
59.5
2025
59.9
2026
Faster Slower Median winning time per season · taller = faster · faded = < 5 races
Going through the year — Kenilworth
How to read this

How often each going has been raced at Kenilworth by fortnight, pooled across all years — independent of the distance and going filters. Taller wet-ground (yielding / soft / heavy) blocks mark the rainy months, which is also why a single-going view below can be sparse out of season. Use By year to see one row per season.

JanFebMarAprMayJunJulAugSepOctNovDec
Going
Good / firm (turf) Yielding Soft Heavy
Seasonal speed — Kenilworth (All goings)
How to read this

Median winning time by fortnight of the year, pooled across every season since 2019. Each distance row is shaded on its own scale — cool = faster than that trip's typical, warm = slower — so you can read how the going-adjusted pace drifts through the calendar. Hover a cell for the hard numbers. Every distance is shown so seasonal patterns can be compared across trips: only the Going filter narrows this table — the Distance picker just highlights its row.

Distance JanFebMarAprMayJunJulAugSepOctNovDec
800m
900m
1000m
1100m
1200m
1400m
1500m
1600m
1700m
1800m
1950m
2000m
2200m
2400m
2500m
2800m
3200m
Faster Slower Shaded within each distance row · empty = too few races