Tag Archive for: Betfair SP

Comparing Starting Price with Betfair SP

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Last week Geegeez added Betfair Starting Price (BSP) to numerous areas of the site, writes Dave Renham. For me as a researcher and writer this is fantastic news. As we know, most punters do not bet at Industry SP (ISP) anymore. Some still stick solely with traditional bookmakers, but to improve their bottom line they will use Best Odds Guaranteed (BOG) where available, as well as early or ante post prices. Some will use the Exchanges, primarily Betfair, with BSP one option to be utilised. Others will try and exploit both the bookmakers and the Exchanges to hopefully gain maximum advantage.

In my personal betting I use BSP for around 40% of all my horse racing win bets, so when researching ideas it is very useful for me to see the BSP profit and loss column.

For this article I am going to examine data from UK racing over the last two full years (2023 and 2024). In the overall findings I will be including all race codes, i.e. flat, all-weather (AW) and National Hunt (NH). For BSP profits/losses I will be using 2% commission which is what we, at Geegeez, are using in our calculations.

When we compare ISP to BSP there is no contest – BSP wins hands down. To give an example, if we look at horses priced between 5/1 (6.0) and 6/1 (7.0) combining all race codes in the UK over the designated time frame we see the following:

 

 

To BSP a profit of £226.24 to £1 level stakes would have been achieved compared with an £1826 loss if backing to Industry SP. That is some eye-watering difference. Just imagine if we were using £20 stakes and not £1 ones!

Before delving into BSP in more detail I do want to talk very quickly about Best Odds Guaranteed (BOG). This option is still available with 12 main bookmakers on most UK races each day. Essentially this option is a no brainer for those betting with standard bookies. When using BOG, it gives punters the chance to take an early price, but if the starting price (SP) is higher, we get paid out at the higher odds. I am in the process of doing some initial research into potential BOG strategies and at this early stage it seems there is a sweet spot in terms of price – or at least the early price. Early prices around the 5/1 (6.0) to 7/1 (8.0) mark seem to offer the best value long term for BOG bettors. I will need to dig much deeper, but I am fairly confident I am in the right early price ballpark to utilise BOG to its max.

There can be issues though with BOG betting such as limits on stakes and occasionally the BOG option will not be available – normally for those people that are winning consistently using it. Working out potential BOG profit and loss figures based on past prices is not always clearcut because of these aforementioned issues. However, I do hope to be sharing some research on this at some point in the future.

Back to main focus of this piece. Earlier I mentioned that the calculations in terms of Betfair commission across the Geegeez site is 2%. For those who currently 5% and are regular bettors on the machine, then log in to your Betfair account and choose the 'Basic' plan on this page. Once this is done, you'll pay 2% only on net winning Exchange bets.

Paying 2% commission on winning bets rather than 5% commission is clearly preferably but I want to illustrate this numerically by using real data to see what a difference it can make long term. Let me compare the BSP profits (to £1 level stakes) of all horses that had an Industry Starting Price of 13/2 in terms of 2% commission versus 5% commission.

 

 

Over this two-year period the difference would have been £116.89. To £20 stakes the difference would be a very significant £2337.80. In the table below I will share some other ISPs in terms of this 2% v 5% difference:

 

 

A palpable difference across the board and, for 8/1 shots, as with the 13/2 shots, a loss with 5% commission has been turned into a healthy profit when applying a 2% commission.

My next piece of digging is in connection with the ISP and the average BSP price for that specific price – comparing the difference between the two. The first graph compares a selection of ISPs under 10/1 (11.0) with their BSP average counterparts. The graph uses decimal odds for ease of comparison:

 

 

Hence an Even money shot at ISP (2.0) has paid 2.14 on average at BSP (before commission); a 9/1 (10.0) shot has averaged at 12.61. It is just another indication of why ISP on its own is outdated for any serious punter.

Let me now look at a selection of some bigger ISP prices ranging from 11.0 (10/1) to 41.0 (40/1):

 

 

As the ISP prices goes to 20/1 (21.0) or bigger the gap to BSP starts to increase considerably. Once we get to 40/1 (41.0) the BSP average is moving closer to double that of ISP. I have always been a fan of backing big-priced outsiders because if I can find a horse with a percentage win chance akin to its likely ISP then I have excellent value.

My next comparison is with average BSP prices for handicaps versus non-handicaps at various ISPs. I wonder how many of us have assumed the average prices would be basically identical – well, within a hundredth of a point or two over two years’ worth of day at least. This is indeed the case for an ISP of Evens (2.0) where the difference is 0.02 of a point (2.13 versus 2.15), but as the prices get bigger, the gaps between the two start to increase. Once again, I’ll share two graphs, the first focusing on an ISP of 9/1 (10.0) or less:

 

 

The average non-handicap BSP is higher across the board than the handicap one with the difference between the two gradually increasing as the prices get higher.

Now I would like to examine the bigger prices:

 

 

With the bigger prices we see a similar pattern with the non-handicap BSP averages higher than the handicap ones and the gaps between the two once again increase as the ISPs get bigger. Looking at the ISP 40/1 (41.0) comparison we can see the gap between the two prices is close to 10 points (77.34 versus 67.87).

I believe the reason we have these differences, and such differences are more pertinent to these bigger prices, is due to the shape of some non-handicap markets. I am talking primarily about non-handicap markets with a very short-priced favourite. Here is an example of such a race. It was the 6.30 at Southwell on 8th October 2024. It was a 5 runner 2yo novice race (non-handicap). Here is the result with the relevant ISPs and BSPs:

 

 

With a very short odds favourite in Shah at 2/13 (1.15) if we look at all the other BSP prices they are bigger than their non-handicap average price. The table below helps to illustrate this further:

 

 

Not only was the BSP comfortably above the average for all four of these runners, in the case of the two biggest priced runners, Something Splendid and Divot, the difference was huge (80 v 47.36 and 328 v 142.53). Of course, such huge outsiders in a race with a super-hot jolly win very rarely but when they do the BSP rewards handsomely.

In my two-year research time frame, there have been 64 races with a favourite priced 2/13 or shorter and 61 of those were non-handicap races. Therefore, having this type of market shape for handicaps is extremely uncommon. Hence, these higher priced outliers in terms of BSP will occur much more in non-handicaps, helping to push the average BSP upwards. Now my guess is that this is not the only reason for the big differences between the average BSP prices of bigger priced runners in non-handicaps versus handicaps, but more on that later.

Continuing the bigger priced theme as well as comparing handicap results to non-handicap ones, let me look at some more BSP data comparing strike rates and BSP returns. In the table below I have split ISPs into three groups – prices from 33/1 to 50/1 (34.0 to 51.0), 66/1 to 80/1 (67.0 to 81.0) and 100/1+ (101.0+).

 

 

When looking at horses priced 34.0 to 51.01 the win strike rates imply a small edge to non-handicappers and the returns show a clear advantage to that cohort, too. Once we get to 67.0 to 80.0 though, the strike rates have flip-flopped with handicappers winning nearly twice as often (albeit still very rarely) and with a huge disparity in the ROIs of around 35p in the £ in favour of said handicappers. This disparity just gets bigger once we hit those 101.0 or bigger shots. Although these 101.0+ handicappers have won on average just one race in every 175 they have seen a return of over 60p in the £ to BSP. Non-handicappers in this price bracket have won on average one race in 833 losing 45p in the £.

There are two reasons for sharing this handicap / non-handicap BSP data for bigger price runners, and I would like to clarify that it is not to suggest that we back all 100/1+ handicappers! The first reason is to show that with bigger priced runners the type of race does make a difference, as does the ISP or the likely ISP, in terms of win chance, likely BSP and potential returns. Secondly, this table might help to explain an additional reason for something I was discussing earlier in relation to why the average price of outsiders on Betfair is bigger for non-handicappers than for handicappers.

At this juncture it should be noted that BSP does not beat ISP 100% of the time. However, a BSP ‘win’ does occur 97.5% of the time (and therefore ISP has ‘won’ 2.5% of the time). It is this 2.5% subset of runners I want to look at next.

Given that we know the Betfair market is about as efficient as a betting market can get, when the ISP is higher than its Betfair equivalent, the expectation would be that this industry price ought to be very close to its ‘true’ price.

4486 horses had an ISP higher than their BSP during the two years in review, and if we had backed them at ISP, a profit of £241.69 (ROI +5.4%) would have been achieved. To BSP these runners would have lost us £77.63 (ROI -1.7%).

Of course, we don’t know the BSP or the ISP before the race starts, so you’d be forgiven for thinking this is a pointless piece of intel. However, for those punters who back late on Betfair, literally seconds before the ‘off’, knowing about this unusual state of affairs could offer a potential strategy.

The prices available very late on Betfair are going to be close to the eventual BSP, especially at the front end of the market. Technically, then, a strategy that may offer an edge would be to have both a Betfair live screen along with a couple of bookmaker live screens open on your computer, coupled with a live racing feed. If, a few seconds before the start of the race, the live Betfair price on a horse is lower than an available live bookmaker price, then back the horse with the bookmaker.

The chances are, regardless of the final ISP, that this will beat BSP with the price taken, or at least effectively beaten it after commission is considered. Not all of us have the time to watch live races on a daily basis and employ such a strategy but for those who do, I would be interested to see how this idea panned out over time.

Finally in this article, I want to examine the results when we use a BSP to ISP odds ratio. What I mean by that is if a horse has a BSP of 3.0 and the ISP was 3.0 the ratio would 1.0. If the BSP was 9.8 and the ISP was 7.0 the ratio would be 1.4 (9.8/7.0). I wanted to see if we could find anything useful out of looking at such ratios. To do this I have used ranges for the ratio and the table below shows my findings:

 

 

As expected, the strike rates tend to move in a positive direction as we move down the groups. In terms of returns, horses that have a BSP/ISP ratio of 1.01 to 1.24 have offered the best value. This again helps to illustrate how efficient the Betfair market is, especially at the front end of the market.

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That’s all for this week. Any price-based research has flaws because as I have stated earlier, we do not know pre-race what the ISP or BSP will be. However, this type of overview analysis is important to understand. For those who never or rarely bet on Betfair I hope this article is enlightening. For those who do, then there should be plenty of new information and stats to be aware of which have the potential to improve one’s bottom line.

 - DR

What to expect in 2024

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The new year is well upon us now and, on this fourth day of January, a few resolutions may remain intact. Chocolate, biscuits, cakes (and especially chocolate biscuit cakes) and beer are largely off the agenda for a bit here - yes, life is currently very dull - but, on a much more interesting note, below are some words around what is on the 2024 agenda for geegeez.co.uk...

 

Racecard Small Changes

We'll start with a 'not very rock n'roll' update: a collection of small changes to the racecards. Although small, most of them are things many users repeat countless times while navigating the software in search of interesting horses.

22nd January Update

These changes are now live and you can see them in action in the video below - there's a timeline below the video:

00:00 Intro
00:31 Save Racecard Filters (desktop & mobile)
02:45 Actual Race Distance in form blocks
04:16 Full Form UK/Ire filter
05:25 'By Time' Racecard view now has time order dropdown
06:40 Asterisked notes
09:10 Run Style added to Full Result
11:00 Removed 'abandoned' meeting non-runners from Tracker
11:35 Outro

 

Editorial Explainer

First up is a racecard menu filters 'memory' - currently, a user must select parameters from the racecard menu filters section each time they close and open the cards menu page. If you use the same filters all the time, you have to reinstate them each time. Faff. We'll sort that.

[Incidentally, if you sometimes see there are no races displaying on the menu page, just hit the 'reset' button top right]

 

Next, an asterisk on the form row when you have a note saved for any/all of meeting, race or runner - to notify you that it's there.

 

Also, we'll be displaying the specific race distance and any distance amendments when you hover over the 'Race Conditions' on any form row:

 

And, if you choose to view the racecard menu page 'by time' you can view the race dropdown ordered by time.

 

If run style is of interest to you, we're adding each horse's early pace position to the full results:

 

We'll get those small, but perfectly formed, changes live later this month.

 

Betfair Data

One of the projects for later in the year is to incorporate Betfair data - Betfair Starting Price (BSP) as well as in-running high and low prices. We actually have these data in our system but adding them appropriately to results and into the tools will take a while. But it's on our to do list.

For a lot of readers who have been restricted, some of the BSP results are likely to make eye-opening reading, certainly when compared to SP.

 

Ratings Model

This is one of those dreaded rabbit holes into which I vowed we'd never delve. Well, we have already sunk a good few hours into the project and we've made some promising progress; but there is  much still to do. I'm at the point now where, for the first time, I do believe we can produce a set of ratings that a) finds a lot of winners and b) highlights some value.

The process involves creating separate models for separate groups of races, and if/when we get as far as publication, we'll do it piecemeal. That is, once we're happy with, for instance, our all-weather sprint handicap model, we'll publish numbers for all-weather sprint handicaps. And so on.

There are loads of ratings out there, many of which are very good at finding winners - but due to the fact they're published so widely they are significantly loss-making. Our Peter May ratings get close to break even at Betfair SP with their top rated picks every year, sometimes turning a small profit and sometimes a small loss. And we might not be able to fare better than that.

My main point is that, unless we find something of utility, as opposed to the somewhat ornamental numbers produced by the fashionable houses, we'll not publish.

 

Query Tool

QT is a powerful means of analysing large chunks of racing data and, once that's done, of saving specific 'QT Angles' to your own account and being notified of qualifiers each day. It's been unchanged for a few years now, and we've aborted a few attempts at an upgrade; but I have so many things I want to add to QT - a majority of them from your feedback and suggestions - and, once we've re-engineered a QT 2.0 engine, it will be relatively straightforward to deploy that extra functionality.

This WILL happen in 2024, it's been too long.

 

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As you can see, apart from the small changes due for release this month, we've got a couple of pretty big 'how long is a piece of string' projects for later in the year. The Betfair element shouldn't be too onerous but I'd like to put some developer time into the modelling next. Very, very loose timeline would be aiming to get some flat rating models on stream for the start of the turf season; then perhaps pivoting to the Betfair and QT projects before reverting to the remaining race code ratings models.

There is a lot of scope for timelines to change, but these are the 2024 resolutions for geegeez. Let's hope they last longer than my personal attempts at self-improvement!

Matt

p.s. away from the bright lights of geegeez, there are a couple of other interesting projects on the go. One, a tote ticket builder, should hopefully be available very soon (I've been using it for a year!), and the other, TennisProfits.com, is a site for tennis traders that we're hoping to make more accessible for bettors, too. I'll share snippets on these from time to time as the year progresses. The tote ticket project especially is one that I think will be of great interest to many geegeez readers/racing punters.

‘Money Without Work’ 2: Wisdom of Crowds

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Part 1 of this series can be found here.

I have deliberately kept mathematical 'proof' and academic rigour of the theories of Wisdom Of Crowds and the related Efficient Market Hypothesis out of this article, writes Russell Clarke. Those who are interested can easily research further their efficacy online. For what it's worth, I believe both theories have limited real world applications, though their usefulness in sporting prediction markets is undeniable.

A brief definition of the Wisdom of the Crowd is that large groups of people are collectively smarter than individual experts at predicting outcomes. Explanations of the wisdom of the crowd are numerous but the Diversity Prediction Theorum attempts to mathematically quantify via the definition, “the squared error of the collective prediction equals the average squared error minus the prediction diversity”.

In layman’s terms, when group of predictors is large and diverse, the error is small. There are more complex layers to add to the wisdom of the crowd theories and explanations involving independence, bootstrapping and other exotically named theories, but for our purposes, we will omit the bells and whistles of academia. This is simply about, to misquote Jeremy Corbyn, “why the many are smarter than the few”. It is especially true when the crowd is diverse and independent, which is very much the situation in betting markets.

It has been demonstrated in numerous studies that the crowd is particularly accurate in the fields of quantity estimate, general world knowledge and spatial reasoning. If we look at quantity estimate, I saw a programme on this subject where office workers were asked to guess the number of sweets in a large jar. The estimates had a huge range and yet the average was just 4 sweets from being correct! More famously, at a 1906 Plymouth Fair, 800 people were asked to guess the weight of an ox and the average was within 1% of the actual weight. I know, I need to get out more…

Related to Wisdom Of Crowds is the Efficient Market Hypothesis. The EMH in its simplest form suggests that asset prices reflect all available information (and thus, by association, it is impossible to beat the market). The latter conclusion is a stretch of the theory, particularly in sports betting.

So, what are the implications of this theory when we look at, for example, horse racing? I have evidence that in recent times a real sea-change has occurred in the racing markets and this has been caused by the increasing wisdom of the crowd. It has gone largely unnoticed as it has been gradual and marginal. However, it has been incremental and, as a result, the marketplace today is very different from that of even a few years ago.

Let me rewind to a time when starting prices were produced by the on-course betting market. A few “good men and true” would form a huddle at the 'off' of each race and compare the prices they saw offered by the bookmakers. They came to an agreement or average and that was declared as the starting price. This SP was basically the result of supply and demand in the on-course marketplace (racecourse punters and the major bookmaking offices who sent cash to the course to reduce the prices of horses that they had large liabilities on). This method was later replaced by a similar method, but one which included more on-course bookmakers.

However, the methodology is not of major importance. The SP’s were still, in theory, a result of supply and demand mechanics within the racecourse crowd. The rise and rise of betting exchanges and, crucially, their use by virtually every racecourse bookmaker means that is no longer the case. Today, the SP’s are a reflection of the betting activity on the exchanges rather than the activity on a racecourse. Suddenly, the crowd is no longer a few hundred punters on a racecourse, it is tens of thousands on an exchange. The new crowd is better informed, more diverse and greater in number. The wisdom of the crowd has increased.

If we accept the aforementioned theories at face value, the best approximation of the chance of an outcome would, in horse racing, be the Betfair Starting Price (BSP) and, in football, the Asian Handicap closing lines. That is because those markets are the largest, deepest and smartest markets for those individual sports. The participants in those marketplaces are diverse, independent and largely devoid of any 'group think'.

In both of these markets there is virtually no margin to account for and so the final prices (once every participant has eventually 'voted') can be readily converted into a percentage chance of that outcome actually happening. A BSP of 2.0 represents a 50% chance, 3.0 represents a 33% chance, 5.0 represents a 20% chance etc. Similarly, Asian Handicap Lines can be converted into % chances for football betting. Numerous empirical studies have shown both to be almost wholly accurate.

I realise I have ‘banged on’ a bit here, but, the importance of this knowledge cannot be overstated. It demonstrates the futility of trying to beat the market when it is at its most accurate. In plain English, it is arrogant in the extreme to believe you know more than the market at the closing and you will eventually find out that it pays to be humble! If you bet at BSP (Betfair Starting Price), the commission is likely to ensure you are a long-term loser (although it is a more favourable strategy than betting with bookmakers at SP with their much higher margins than the exchange commission). If you accept that logic, then it is clear that you should be betting early, when the market has less participants and is therefore less accurate.

Another use for the EMH is if you want to accurately assess systems, strategies or the records of tipsters/experts. It is a quicker and faster way to assess than simply looking at a profit/loss account, which can be wildly erroneous. So, traditionally, even those that do their research, will look at a series of results and concentrate on factors such as profit/loss, strike-rate, longest losing run, taken from a set of past results. On the surface this seems logical and sensible. However, the downside is that you will almost certainly be dealing with an inadequate sample size (again, if you need the maths, then an online check) and even if you have thousands of results, a simple Monte Carlo simulation will demonstrate the huge variance in results you could experience moving forward (more of which anon).

Using our appreciation of the accuracy of the markets, we can gain a quicker and more accurate guide to how a strategy will perform in the future and in the longer-term. We can ignore profit/loss figures and instead concentrate on how the selections (winners and losers) perform against the market. There are a few criteria you could apply but a very simple method is demonstrated below:

Two figures you require are the price at which the selection is advised (or a morning price) and the eventual BSP. Then it becomes a simple comparison. If a horse is advised at 10/1 (11.0 digital odds) and the bsp is 7.0, then that would be assessed as +4 (11-7). Similarly, a horse advised at 8/1 (9.0) and the bsp is 9.0 would be assessed as 0 (9-9) and a horse advised at 12/1 (13.0) that has an eventual bsp of 18.0 would be -5 (13-18).

After as few as fifty bets you would get a good reading of the number of selections that are positive as opposed to negative, and, the running total would give an indication of the magnitude of the long-term profits/losses that are likely. The actual results and profits/loss are largely irrelevant as they may just reflect either a favourable or unfavourable run of winners/losers. You can be sure, however, that if you continue to beat the "closing line” you have unearthed a source of long-term profit.

- RC

Next week: Part 3: Bookmakers - Sharps and Softs