Here I’m going to give you a blueprint to create and use a script to trade a tennis match using the data from the daily tennis trading notes, and the stats from the resource page.
Having a script prepared is extremely useful for a couple of very important reasons:
- It gives you all the statistical information in one place before and during the match.
- It makes sure that you don’t make any trades on impulse without any logical behind them.
As there is no sport on at the moment, I’m going to look at a hypothetical match between Elena Rybakina & Iga Swiatek on hard court at the Rogers Cup in Toronto.
| Rogers Cup – Toronto, PREMIER, CAN, Hard. | |||||||||||||
| Court Speed is 69.5% (3.9% above mean) – Fastish. |
Projected Hold % |
Break Opponent % | Implied probability | E.O.S. | WTA World Rank | WTA Surface Rank | BP Save | BP Win | 12-month TB Record | Pinnacle Opening Price | My Price |
TOT Surface Rating |
|
| 1 | Elena Rybakina | 76.40% | 33.30% | 54.42% | – | 17 | 20 | 63.5 | 46.1 | 7-4 | – | 1.84 | 108.2 |
| 2 | Iga Swiatek | 71.20% | 32.90% | 45.58% | – | 49 | 53 | 52.9 | 44.3 | 2-2 | – | 2.19 | 103 |
| WTA Hard Court Mean 65.6% | 55 | 45 | |||||||||||
When I create my sheet the first thing, I do is to look at the projected holds of both players.
Projected holds for this match are:
Rybakina 76.40%
Swiatek 71.20%
The current WTA Hard Court service hold mean is 65.6% and both girls here hold well over that. So we can assume this is going to be a serve dominated match-up, when we consider the court speed which is fast, we can see that breaks could possibly be at a premium in this match.
It’s also worth looking at and taking into account the break point stats on the sheet to get a picture of who is clutch or not. From this we can see Rybakina is much better at saving break points than Swiatek and could possibly be backed BP down.
Swiatek hasn’t a strong trend either way. Have a quick glance at the unique TOS rating as well, this is a numerical snapshot of a player’s stats over the last 12 months and will tell you who has been in the better form. As a general rule of thumb over 120 is world class, 115-119 is Top 10 level and 108-114 is solid Top 15 material.
Under 100 is usually a sign of a journeyman player. Obviously this depends on age as a number that is constantly growing could also point to a teenager on the come-up.
If we then have a glance at previous years results from this tournament. We can see Rybakina has never played here and Swiatek made her debut last year and won four matches including two in qualifying.
I then compare my models’ price with the opening Pinnacle price to judge if we have any value pre-match, as value pre-match also means value in-play as all in-play prices deviate off the starting price.
In this example we can see Rybakina holds and breaks more than her opponent and has a higher TOS rating so we can infer from the numbers that she should be priced up as favourite in this particular match-up.
So, from the information we have already we can see:
- Rybakina should open as favourite.
- Swiatek has experience of these courts and has 3rd round points to defend from last year.
- Both players are expected to hold serve more than average.
- Rybakina should save more break points than expectation.
- Rybakina has played at a higher standard over the last 12 months on the specific surface.
- Both players have an average return game.
The first thing that jumps out when considering the above points is that both players are expected to hold serve more than average and with Rybakina above average at saving break points, we can lay Swiatek when she is leading on the Rybakina serve at *15-40. This is a short-term single game trade where we have to be very aware of the game state.
Trade On Sports Tennis Gold Application
We can now use the Trade On Sports Tennis Gold Application to micro mine the data and look at specific scenarios within the match to put together a trading plan.
The first thing I look for is who is a quick starter, so we look at the set one win percentages of both players and we can use a benchmark of if you win the opening set around 65% of the time then that is very strong form.
Rybakina 69%
Swiatek 60%
Now we can mine this data even further to see who breaks the most FIRST in set one.
Rybakina 59%
Swiatek 59%
If we take a mean figure from the Top 100 WTA, we see the average player breaks first in set one 51.5% of the time, so both girls are above average in this respect.
Now we look at who loses the lead in set one more than expectation (WTA Top 100 mean 46.19%)
Rybakina 44%
Swiatek 31%
Iga is very strong at holding a lead in the opening set it seems. So, do we want to oppose her a break up?
Let’s have a look at the players set one recovery stats, the WTA Top 100 mean is currently 49.93%.
Rybakina 63%
Swiatek 45%
Rybakina is exceptional at set 1 break recovery but its not a perfect storm as Swiatek is strong at holding a set 1 lead, ideally in this scenario we want to be opposing a weak front runner with a player who has Rybakina level recovery stats. In this example though we use our eyes to see if Rybakina is making any inroads into the Swiatek serve, if she is then maybe we can take on the Pole when serving.
I also like to look at who chokes at the end of sets as the scoreboard pressure is turned up a notch. We have certain criteria that needs to be met at Trade On Sports to show us who is strong at taking a late lead when the match is still on serve or who likes to get themselves broken late in sets. When taking a late lead, the Top 100 WTA mean is currently 41.34% and being broken late the mean is 40.75%.
Taking A Late Lead (Tour mean 41.34%)
Rybakina 33%
Swiatek 40%
Being Broken Late (Tour mean 40.75%)
Rybakina 33%
Swiatek 60%
We also find another angle to consider here. Swiatek seems to get nervous when serving late on in set one, this quite possibly is due to the fact she’s still a teenager and her mental strength is still a work in progress. Personally, I’d be keener to lay her in this spot than earlier on in the set.
We also have serving for the set and serving to stay in the set stats and these are well worth a look at as some players are hopeless in this scenario, I’ve posted enough numbers so I think you get the drift.
Once the 1st set is done we can have a look at set two win percentages, we can also break them further down into set two win percentage when won set one and set two win percentage when lost set one.
Once more all the stats described above, early break, recovery etc are all available for set two & three. This micro mining of the data will help us to decipher if there is any value in laying the set one winner.
Sets Two & Three
So, for instance if we look at set two win when won set one figures, we see the WTA mean is 64.1% and Rybakina in this spot wins 68% of the time and Swiatek 61%.
Looking at the set two win when lost set one we see the mean is 39.2% and Rybakina clocks in with a 44% conversion rate with Swiatek just behind at 42%. From this we can deduce that both girls are fighters and the optimum spot for me is to lay Swiatek if she happens to have won set one.
If we reach a deciding set we then do the same analysis within set three to try and find patterns in a players game, all this would be impossible without the Trade On Sports Tennis Gold application as it really does give you all you need to map out a trading plan while watching a tennis match.
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