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Old 10-29-2018, 05:25 PM   #25
steveb
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Join Date: Jan 2008
Location: Melbourne Australia
Posts: 918
Quote:
Originally Posted by ARAZI91 View Post
Interesting Steve , had a quick shifty at my data for the UK and looked at all UK Flat Turf tracks. I limited it to Handicaps (tighter range of ability) and bucketed them by distance ranges eg 5f & less than 6f (we have some odd distances at some tracks - eg Newbury 5f 34yards)- I also limited it to >= 8 runner races and used 3yo and upwards.

These are average time margins of 2nd place finishers , medians would be lower due to frequency of tighter finishes but seems to show margins increase(at least here) as distances increase , possibly due to the relatively slower early pace. Obviously this covers a wide range of different type tracks (galloping to sharp/tight) and goings (firm to heavy)
The Official BHA Handicappers here use a lengths per second scale ranging from 6 per second on Firm to Good , 5.5 Good To Soft and 5 Soft or Heavy although having studied their published times online i have found them to vary , sometimes considerably in the scheme of things from as low as 0.14 to 0.25.

that surprises me immensely.
are the times official from the lynx system or whatever they use over there?

or have you converted back from the margins?
i have done a zillion countires(not uk or usa though!)and it is always the same.



as far as the conversions go they all suffer the same disease.
take a perfectly accurate time and convert it into an inaccurate margin.
sydney does a constant .17
hong kong does a constant .16
adelaide can be anything that i have not been able to figure.....varies .15 to .19....probably depends on how many cans the judge drunk!
other joints, especially other parts of australia, can be any bloody where.
thus it is obvious that a margin of 6 lengths here, may mean one of 5 or 7 there.


anywhere where times and margins are supplied, then you can just use regression to figure the conversion factor, and although it is never exact you can see what it is.
and the fact that it is never exact demonstrates how they turn accurate into inaccurate!
i do that whenever i add data because it's a great way of finding errors.
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