Horse Racing Statistics: Understanding In-Running Data [GBettle]

horse racing statistics

You may have seen the horse racing statistics I share on twitter from time to time (most days)…

Foolish, but I assumed all would understand them fully…

But, obviously there’s not a lot of point in sharing if they aren’t interpreted right!

 

Gary Question

Here’s a quick guide on what the numbers and stats mean, and how they could be used to your benefit.

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Horse Racing Stats Breakdown:

Typically you’ll see two sets of data. Historical in-play pricing and the current ‘market-line’.

Before they’re explained, it’s worth noting that previous price data is exactly that. There’s no guarantee this will happen every single time, further runner analysis is a good idea before putting down any kind of bet. Also, readers should remember that the whole idea of trading is not to win every time, but to build profits over the consistent application of an edge. Recently there seems to be more users punting on a price move, and then calling it a trade if it worked out…

So, the horse racing statistics:

Ascot Racing Stats 1

Above, you can see the historical in-play statistical data for ‘Brandon Hill’. From top to bottom in time (Event Date and Time).

To next column along speaks for itself. ‘Menu Hint’ being the Country, Track and Date the race took place. Followed shortly after by the ‘Event Name’ including the race distance and type. Selection name goes without saying…

The part that some may be confused with are the last two columns. BSP stands for Betfair Starting Price and IPMN means In-Play Minimum, the lowest price at which the selection traded for more than £2.

If we were to create an example from the table above:

Brandon Hill raced in a 3 mile handicap chase on the 8th of December 16 where the starting price was 4.3 (10/3). Within the race Brandon Hill traded at a low of 1.01… because the selection won. Simple enough, right?

Second Statistics Screen:

The black set of statistics may be the screen that appears confusing, because some have assumed the list of numbers on the left are previous results, they’re not.

From top to bottom (below) you have the date at which the market data was captured, and on which race. Total Matched is the volume of money in GBP on the entire race at that time, Market line is the time at which the data was captured. In this example, it was 10:00:49 in the morning.

Below this, left to right is the selections Betfair ID. Not to be confused with anything else, the selections within the given race and prices that there is money available to match. Antony is available to back at 4.3 and lay at 4.4 if you take a peek…

Ascot Racing Stats 2

Now, lets take a look at how you could use these horse racing statistics to your benefit!

Whats the Use?

Depending on your betting experience, you may already have spotted a range uses for horse racing stats like this.

Like we said previously, past performance isn’t a guaranteed indication of the future. However, it’s hard to deny that this is a good way of identifying a horses appearance whilst running. Horses that ‘travel strongly’ often trade lower in-play. Others may run prominently or lead, either way the horses preferred running style and appearance shine through in the data.

Brandon Hill is a good example of this.

If you take a look at he previous runs, the selections statistics showed a price reduction of 50% or more in-running nearly every time. These kind of statistics are extremely useful for anyone that is looking to use a dobbing strategy whilst the race is in-play.

Given all of this information, how did Brandon Hill run on the day the stats were released?

Horse Racing Stats Timeform

Yup, that’s another one. Starting at 5.8 and trading at a low of 1.5.

Obviously dobbing isn’t the only strategy to use when looking at this data, there’s many ways to ‘skin a cat’ on the exchange.

Regardless of what you do, these statistics are free. Just make sure you follow the Twitter and Facebook feeds!

Either way, enjoy…

Horse Racing Stats EXAMPLE:

That may have gone over some readers heads, so here’s a little example of how you could do this – including the numbers.

If we run through a hypothetical trade on Brandon Hill on the 24th. We’ve seen the pretty impressive strike rate at which Brandon Hill trades in-running, using the historical horse racing statistics. So we decide to place a £20 trade, in the anticipation Brandon Hill will trade at 50% of the starting price, in-running.

A £20 back bet carries a return of £116 (of which £96 is profit) and a liability of £20.

Obviously 50% of 5.8 is 2.9, this is where we place our lay bet of £40.

If our selection should trade as low as 50%, we’re all green to the tune of £20. But if it should not, we lose £20. A 50/50 payout proposition.

Except of course, if Brandon Hill’s previous horse racing statistics are anything to go by – there’s far more than a 50/50 chance of both bets being matched.

Assuming commission was at 5%, we would have incurred a £1 charge on our winnings. This would need to be factored into your overall decision as to which selections you place this trade (knows as a DOB).

Thanks to GBettle for posting these stats up on twitter each morning.

Related: In-Play Trading Strategies

7 thoughts on “Horse Racing Statistics: Understanding In-Running Data [GBettle]

  1. Hello Caan…. Where can we find those data? If possible in a format that we can work out (csv, xlsx)….

    Great job you have here…. Best regards

      1. The daily stats are available from betfair but you have to crunch the numbers to get the summary stats as posted by Gary and myself

  2. Good post Caan. I really enjoy your blog but one question. Isn’t half of 5.8 actually 3.4? ( 5.8-1 divided by 2 = 2.4 then plus one to get Betfair odds = 3.4

    1. Hi Chris,

      Nope, it’s half of the odds, not the potential return/liability. Write down the numbers and potential incomes and you’ll see the difference. At 3.4 it would leave £20 profit on the rest of the field, but not the selected runner.

      Have a good week!

      Cheers
      Caan

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