Creating a Tennis Trading strategy

02/04/2015 | By | Reply More

I’ve had a lot of people ask me about creating a Tennis trading strategy recently, so I thought I’d post an updated version of old article from January 2014 which a lot of people have found useful in the past.

For this article, my plan was to detail how to create and use an effective ‘script’ to trade a tennis match, by means of laying player’s service games and laying the player a break up in a set.

It is my belief that having a script is highly useful for several reasons:-

1 – It ensures you have all statistical information to hand prior to and during the match.

2 – It ensures that you don’t make impulsive decisions without any logical reason.

When creating a script my first job is to assess the projected holds of both players.

For this article, I used a hypothetical match between Victoria Azarenka and the now-retired Li Na on hard court at the Australian Open in January 2014. Both players were similarly ranked and there wasn’t a huge ability difference. For the purpose of simplicity, I’m going to assume that both players were equally fit and there were no match-up issues.

Projected holds for this match up, based on my model, were as follows:-

Azarenka 56.6%

Li 51.6%

These projected holds have also taken into account a surface adjustment. In the 2013, the average surface hold of the Australian Open was 61.5%, and when including 2012 data, was also 61.5%. This is below the current WTA hard court average of 63.1% so it can be assumed conditions were a little slow in Melbourne.

Both players have much lower projected holds than the WTA hard court average, so from this data we can draw the conclusion that there will be more breaks than average in this match. Interestingly, in the 2013 final, that was indeed the case – there were 16 breaks in 29 service games (just 44.83% of service games were held).

It’s also worth noting that Li has much better break point stats. She saved 60.4% to Azarenka’s 58.4%, and converted 52.6% to Azarenka’s 50.5% in 2013 (across all surfaces). This is borne out by her superior break point ‘clutch score’ of 7.1, compared to Azarenka’s 1.5. A break point clutch score is the difference between expectation and reality for a player’s break point stats, compared to service and return points won. A score of over 3.0 is considered pretty strong, and would indicate a ‘clutch’ player – someone who is strong at key points. Clearly this is definitely worth noting and taking into account when compiling a trading script.

This data would give a starting price of around 1.80 on Azarenka, which isn’t too dissimilar to her starting price of 1.71 in both the Australian Open Final, and at the recent WTA Tour Championships in Istanbul.

It’s also reasonable to assume that as Azarenka lost the match in Istanbul, her price would lengthen a little for a match-up in the near future, so the 1.80 on her looks pretty accurate. For the purposes of this article, I’m going to assume that’s the case.

So as it stands, we have the following information:-

· Starting prices are correct.

· Both players are expected to hold serve much less than average, especially Li.

· Li should save break points more than average.

All this information is available for every match in the TennisRatings daily ATP/WTA spreadsheets.

On that basis, we can start to formulate a trading plan…

With both players expected to hold serve much less than average, a good starting point would be to lay both servers for their individual service games when the first set is on serve. At the end of each service game we hedge our position, taking a profit if there is a service break, or a loss if there is a service hold. Essentially this is a short term trade.

In normal circumstances, because her projected hold is very low, it would be worth looking at laying Li’s serve for a higher stake than Azarenka’s, but in this match-up her break point clutch score needs to be considered. It would also make me consider taking a more conservative approach to her service games. One way of doing this would be to take some liability out at a scoreline such as 0-30 or 15-40, and definitely 0-40.

Several approaches can be considered here:-

· You could clear all liability at one of these scorelines, leaving all potential profit on Azarenka and a scratch position on Li, guaranteeing profit (higher profit if Azarenka still breaks).

· You could leave some liability on Li and more potential profit on Azarenka, knowing that if Li does save break points to hold, you could guarantee a pretty much scratch trade.

Because the markets on the exchanges generally base themselves on the tour surface hold average when moving to a service hold or break, finding players – especially those that the market may not necessarily expect – who should struggle to hold serve is a valuable asset.

A further, more detailed approach, would be to use Rolling Projected Holds, also available via ATP/WTA daily spreadsheets.

My research found that there was a very strong relationship between a player’s previous service game scoreline (e.g. hold to 0) and their next service game scoreline. I don’t want to go too much into the percentages as they vary from match to match according to a player’s base projected hold but I will say that projected holds can vary by as much as 10% either way based on previous service game scorelines.

Once there is a break of serve, prices will start to deviate strongly from the starting price. This has a more pronounced effect in ATP matches due to the men holding serve more (hence a break is a rarer commodity) but still has a strong influence in WTA matches. It’s very difficult to give a price guide to how much this will change because time decay (games elapsed) is a strong factor – for example the price will decrease sharper if the break comes to give a player a *5-3 lead as opposed to a *2-1 lead, for example.

The next step at this point would be to assess whether there is any viability in laying the player a break up in the set. At this point, unless the player who is a break up was a fairly strong underdog to win the match before it started, the player a break up will be trading odds-on (1.xx price). Laying players at 1.xx means that we generate more potential profit than our potential liability, so it’s generally preferred to laying players at prices odds against, although I don’t mind laying players between 2.00 and 2.60 for individual service games.

The way I feel is best to assess whether the player a break up can be laid is to see the break lead defence and break recovery stats which I compile monthly. These stats are also included in the daily ATP/WTA spreadsheets for each match. When I use these statistics, I mean the set went back on serve from those points (it does not take into account what happened after the set went back on serve).

In this match-up, the following 12 month break-back stats apply:-

· Azarenka gave up a break lead 38.46% in 2013, and recovered a break deficit 62.50%.

· Li gave up a break lead 42.86% in 2013, and recovered a break deficit 66.67%.

From this we can see that there isn’t much between the two players in this area. Li gave up a break lead slightly more, but compensated that by recovering more break deficits.

If Azarenka was a break up, my approach would be to assess the combined score for the scenario (Azarenka break lead loss % + Li break deficit recovery %), which would be 105.13.

If Li was a break up, my approach would be to assess the combined score for the scenario (Li break lead loss % + Azarenka break deficit recovery %), which would be 105.36.

These stats are almost exactly the same, and are significantly higher than the WTA combined score mean, so it’s viable to lay either player a break up in this match, as a medium term trade. By this I mean that I will look at keeping my position until either the player a break up gets broken (I can then hedge for profit) or the end of the set is reached (I can then hedge for a loss).

So far in the article we’ve looked at how you can use statistics to gain a very workable edge in the tennis trading markets, using basic projected holds when the match is on serve, and break lead/deficit stats when a player is a break up in the set.

Hopefully by now you have a good idea of how to create a tennis trading script based on statistics, and naturally, these are just several angles that you can use to create statistically viable entry points, and of course, many other potential avenues with positive expectation exist. However, these angles do illustrate the benefit of having a statistical trading script prior to a match which you can use when the match develops in certain directions, so you can take the approach of ‘if x happens, I’ll enter/exit with y trade’, which allows traders to execute trades on a non-emotional, non-impulsive, yet statistically viable basis – a much better approach than subjective entries with no particular reasoning.

Many Thanks to Dan Weston who was the guest poster for this article, visit Dan’s excellent Tennis ratings site for lots of useful Tennis stats.