How to Use the Post Position Statistics | Galoppanalyse.no
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How to Use the Post Position Statistics

June 30, 2021

What Does the Post Position Statistics Visualize?

Track statistics is the first tool we have equipped you with. It can be found under the TOOLS tab in the menu.

The post position statistics provide a simple, visual presentation. The colors indicate what you can statistically expect of lengths lost due to wide trips, while the height of the bars is based either on the number of wins, or win percentage, depending on which version of the statistics you look at. In both versions, you will find both win rate and total wins in the tooltip, which you’ll get by hovering over or by pressing one of the gate positions.

A more detailed explanation of the colors and what they indicate is probably in order.

Specifically, there is a scale at the back that colors inside trips (rail trips) completely green – and vice versa, very wide trips completely red. What you see is at all times the average of these calculations – based on the filter settings you have selected. In other words, the filters determine what data is used to calculate.  

The data to determine ground loss is something we have collected ourselves, through careful video analysis of every race ran in Scandinavia and Meydan. We follow each horse through every turn, and estimate an average distance to the rail for each one of them (horses do not keep straight lines!).  

The data set that this particular visualization is based upon is only updated from time to time. It currently shows data from 2017, 2018, 2019 and 2020.

Example of post position statistics sorted by number of victories:

Here you can see the number of wins, and the average lengths lost by wide trips over all courses, distances and surfaces taken as a whole. This looks even worse than it really is, because it does not take into account that there are many more starters on post position 1-6, than it is from the wider gates, simply because it is relatively rare with full fields. Specially in Scandinavia. We therefore strongly recommend to always be using the visualization based on win percentage as well.

How to use the visualizations?

In order not to be fooled by the statistics, it is important to be aware that a raw count of the number of victories from each gate will be skewed, as there are many more starters in total from the lower post positions, than the higher ones. Simply because the average field size in Scandinavia is no more than 7-8 horses.

Therefore, we often prefer to use a statistic based on the winning percentage, rather than the raw count of number of victories.

If you begin with identical filters as in the picture above, the same statistics will, sorted by win percentage, look like this:

Example of the same statistic, sorted by win percentage:

This shows the win percentage and average lengths lost due to wide trips on all courses, distances and surfaces, as a whole. We see that the same tendencies are still very clear, but not as extreme as in example 1. This view is in our view a fairer representation of what is really going on.

The filters can be customized, so that you can see the statistics you’re interested in. You can filter on tracks, surface, distances and years. The visualization will aggregate on the filters you have activated at any given time.

It’s important to always keep in mind the amount of data left to do calculations with, after you have customized your filters. Some distances are seldom run and will therefore have less data, and in these kind of cases there will be a lot of noise and randomness in what you see. Don’t be fooled.

Combine these statistics with common sense!

The more data a specific visualization is based upon, the more confident can you be in that the trends you’re noticing represents true tendencies. 

Pro tip! At the very top of each column, you’ll see written in gray how many data points each calculation is based on.    

A Recent Example of a Good Bet Identified With Use of Post Position Statistics

Let me show you a recent example of a good use of the post position statistics.

We are heading back to the lunchtime event on June 2, 2021 at Bro Park, just a few days after we first made and published this visualization tool.

We were set for a 1000 m dirt race at Bro Park, and it was not so easy to find horses to like. There could be room for some bombs to hit. A good habit when you start to handicap a race, is of course to check the post position statistics for the relevant track, distance and surface first. It’s hard to remember everything in your head.

To find the relevant statistics for the 1000 m dirt track on Bro Park, you must select the following settings:

BANE = BRO PARK

UNDERLAG = DIRT

DISTANSE = 1000

ÅR = ALL

Notice that this would be in Norwegian. Bane = Track, Underlag = Surface, Distanse = Distance and År = Years. The rest should be pretty self explaining.
When you do this you get the view we see above, where we have the statistics sorted by the number of victories on one side, and the statistics sorted by win percentage on the other.

They show exactly the same tendency, that it seems to be an exceptionally big advantage to start from gate 1 on this very distance, 1000 m dirt track on Bro Park.

Here you also see that the number of data observations is quite limited, so you’ll have to use your best judgment to assess whether these trends are mere coincidences, or if they represent a real tendency. Only 11 observations are of course not enough to be sure, but still, 5 out of 11 victories is such a striking tendency that it is tempting to think that it can not all be completely random.

If you have watched some races throughout your life and like to think you know your ponies, you easily start to create some hypotheses. It’s tempting to think that what’s really going on here, is that whomever manages to get to the front at this particular distance will have very good chances to prevail.

After creating this hypothesis from analysing the post position statistics, we took another look at the past performances.

Samara Bay was not a horse we gave much chance at first glance. She had definitely not shown any performance figures that were competitive in this company earlier, but she was lightly raced. We barely remembered that she had shown at least a glimpse of “speed” at some occasions, and since we did not like anyone else in this very much either, we decided to include her on our pick 4 based only this suspicion made up from the insights provided by the statistics. As visualized in the pictures below you see Samara Bay jumping straight to the front, and defending that lead rather easily to a secure victory. The win odds were 18-1.

This is just one example, of course, and quite the  anecdotal evidence – but the idea was just to illustrate how the post positions statistics could assist in generating ideas.

This is “The Art of Handicapping”, after all!

Had Samara Bay been 3-1, one could of course not justify to speculate in this matter on such a thin data selection,  but when a horse is 18-1, well then it’s okay to grant one self a little extra “creative license”. It’s about percentages, after all.

Pro tip no. 2! It was Archers Ignite who became second in this race. He started in gate 3 which was zero-from-ten at the time. That stat for gate 3 is sure to be a bit random, after all only one win would change our impression, but it still undeniably looked from what we knew about gate 1 like Archers Ignite had it all to do, when tasked with catching up with a leader from the inner lane. That’s the kind of things you could make notes on, so that you would maybe upgrade Archer’s Ignites performance when he’s entering a start field yet again. In this particular case, that would have been a correct thing to do, as Archer’s Ignite has won both of his two races since, and that in very good style. 

We feel generous, so here are:

Pro tip no. 3! Distance from the starting gate to the first turn is a big factor when it comes to how advantageous or disadvantageous a particular post position could be. The shorter the distance to the turn, the more difficult it will be to avoid wide trips with a high gate number. It is simply less time to secure a good position. 

Now all that remains is just to wish you a good time with the statistics

– and if you stumble across such clear tendencies as in this one example, it should be an excellent topic of discussion on our forum !

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