Tennis – Dominant Sets in ATP Masters Events
A popular form of trading is laying the player a break up – I’ve written a great deal about it before, and the positive aspects of this type of trade is that it’s easily quantifiable (using projected hold and break lead/deficit loss/recovery statistics) and that risk is much more limited than taking a position when the set is on serve.
The worst result for this type of trade is when the player you have opposed turns a single break lead into a double break lead, as the tick loss will naturally be higher.
On this basis, I endeavoured to assess whether there were certain conditions which created a scenario where a double break set was more likely. I quantified this as a 6-0, 6-1 or 6-2 set result, where a double (or in rare cases, triple) break set victory was guaranteed.
I looked at the ATP Masters 1000 events in 2014 to make a statistical comparison, and the results can be seen below:-
ATP Masters Tournaments | 2014 Data | 6-0 to 6-2 Sets | ||||||||
1st/2nd Round | 3rd Round + | 3rd Round + | ||||||||
Event | Surface | Completed Sets | Yes | No | % |
10 |
Yes | No | % | Overall % |
Madrid | Clay |
95 |
28 |
67 |
29.5 |
30 |
6 |
24 |
20.0 |
27.2 |
Toronto | Hard |
97 |
19 |
78 |
19.6 |
37 |
3 |
34 |
8.1 |
16.4 |
Shanghai | Hard |
95 |
18 |
77 |
18.9 |
35 |
10 |
25 |
28.6 |
21.5 |
Rome | Clay |
89 |
20 |
69 |
22.5 |
38 |
14 |
24 |
36.8 |
26.8 |
Cincinnati | Hard |
97 |
17 |
80 |
17.5 |
38 |
13 |
25 |
34.2 |
22.2 |
Paris | Indoor Hard |
74 |
19 |
55 |
25.7 |
35 |
6 |
29 |
17.1 |
22.9 |
Miami | Hard |
153 |
36 |
117 |
23.5 |
63 |
15 |
48 |
23.8 |
23.6 |
Monte Carlo | Clay |
95 |
36 |
59 |
37.9 |
33 |
14 |
19 |
42.4 |
39.1 |
Indian Wells | Hard |
152 |
40 |
112 |
26.3 |
78 |
20 |
58 |
25.6 |
26.1 |
Overall |
947 |
233 |
714 |
24.6 |
387 |
101 |
286 |
26.1 |
25.0 |
|
Hard/Indoor |
668 |
149 |
519 |
22.3 |
286 |
67 |
219 |
23.4 |
22.6 |
|
Clay |
279 |
84 |
195 |
30.1 |
101 |
34 |
67 |
33.7 |
31.1 |
Quite surprisingly, there were slightly fewer dominant set wins in the first and second round of tournaments. This, on the surface, is quite strange as it would be logical to assume that the ability differential between players was highest here. However, it also features players who tend to be weaker on serve, and frequent chokers, and this may be a contributory factor.
The main striking difference was the propensity for clay events to have much higher 6-0 to 6-2 set wins than hard or indoor hard court. 2014 Clay Masters 1000 events had 7.8% more dominant sets than those on hard or indoor hard in the first two rounds, and 10.3% in the later stages of events, which generated an 8.5% greater figure overall.
On this basis, laying players a break up on clay is a much riskier prospect than on hard courts, and this type of trade should be considered more carefully on the dirt.
This analysis is a superb example of useful data that can be generated in a short space of time – it took me around half an hour to compile the above table. Hopefully it will inspire a few readers to undertake some research for their own trading.
Category: Tennis, Trading strategies