|
Player |
Win rate (%) |
Service points won (%) |
Return points won (%) |
Combined serve and return points won (%) |
2019 tiebreaks contested |
2019 tiebreaks won |
Tiebreaks won (%) |
|
Roberto Bautista-Agut |
65% |
66.7% |
38.7% |
105.4% |
23 |
8 |
34.8% |
|
David Goffin |
57% |
63.4% |
39.8% |
103.2% |
24 |
12 |
50.0% |
|
Grigor Dimitrov |
50% |
65.2% |
37.4% |
102.6% |
30 |
9 |
30.0% |
|
Hubert Hurkacz |
51% |
66.3% |
34.9% |
101.2% |
24 |
11 |
45.8% |
|
Ugo Humbert |
43% |
65.2% |
35.1% |
100.3% |
21 |
8 |
38.1% |
|
Fernando Verdasco |
48% |
63.8% |
36.5% |
100.3% |
19 |
8 |
42.1% |
|
John Millman |
41% |
63.6% |
36.3% |
99.9% |
26 |
11 |
42.3% |
|
Dusan Lajovic |
43% |
61.6% |
36.9% |
98.5% |
15 |
5 |
33.3% |
|
Federico Delbonis |
41% |
60.7% |
37.6% |
98.3% |
21 |
6 |
28.6% |
|
Steve Johnson |
40% |
64.7% |
33.6% |
98.3% |
20 |
7 |
35.0% |
|
Kyle Edmund |
39% |
63.8% |
34.2% |
98.0% |
12 |
1 |
8.3% |
With this year’s tennis season now underway, it is a good time to take an alternative look at how success and failure can emerge on the court. In the final article of a four-part series analysing variants in professional tennis, Dan Weston identifies which players could be under or overvalued by the betting market during the coming season.
The previous articles in this series looked at how to highlight players whose results were over or underperforming in comparison to their expected win-loss record. To conclude, this final piece will profile which players fit this bracket, with a view to demonstrating potential profitability from such an approach.
Ascertaining players undervalued by the market
As previously established, there is a noticeable relationship between a tennis player’s win percentage and combined service and return points won percentage, and a slightly weaker one between the latter and tiebreak success rate. These findings can be utilised to profile players who performed better than their actual results indicated across the 2019 season.
The players listed below suffered an inferior win percentage in 2019 than many players with poorer combined service and return points won percentages. They also had poorer tiebreak records than expected, based on their ability level implied from their service and return points won percentage:
Many of these players had around a 50% win rate last season despite recording a service and return points won percentage of above 100%, or a win rate of approximately 40% despite performing only marginally beneath the 100% benchmark.
In addition, not a single one of these players won greater than 50% of the tiebreaks they contested, despite recording stats in line or above those expected of an average professional.
Essentially, this group of players incurred poor results despite achieving at least decent stats. Notably, already in the 2020 season their results thus far have shown that the group have positively mean-reverted, prompting the market to undervalue them based on their 2019 results as opposed to underlying performance levels:
|
Player |
Matches |
Profit/Loss |
ROI |
|
Roberto Bautista-Agut |
12 |
4 |
0.33 |
|
David Goffin |
13 |
583 |
44.85 |
|
Grigor Dimitrov |
14 |
-79 |
-5.64 |
|
Hubert Hurkacz |
13 |
37 |
2.85 |
|
Ugo Humbert |
17 |
428 |
25.18 |
|
Fernando Verdasco |
8 |
-131 |
-16.38 |
|
John Millman |
10 |
236 |
23.60 |
|
Dusan Lajovic |
15 |
442 |
29.47 |
|
Federico Delbonis |
14 |
-284 |
-20.29 |
|
Steve Johnson |
19 |
-16 |
-0.84 |
|
Kyle Edmund |
13 |
61 |
4.69 |
|
Overall |
148 |
1281 |
8.66 |
Blind-backing this group in their matches this season would have returned 8.66% ROI to a level £100 stake based on Pinnacle’s closing prices – a considerable profit margin from the 148 matches in which they competed during the first two months of the year.
Who is overvalued by the market?
We can also look at the inverse indicators, to try and establish those which the market could be over-valuing and should (in theory) mean-revert downwards having obtained better results last year than their underlying performance levels would suggest:
Principally, the reverse is true for the players listed above – instead, they enjoyed a higher win percentage than their service and return points won percentage would ordinarily dictate, and all also produced better tiebreak records than expected.
Interestingly, blind-backing players from this group also produced a positive ROI, albeit not as high as those in the undervalued group:
|
Player |
Matches |
Profit/Loss |
ROI |
|
Stefanos Tsitsipas |
17 |
-102 |
-6.00 |
|
Stan Wawrinka |
11 |
266 |
24.18 |
|
Guido Pelia |
11 |
-230 |
-20.91 |
|
Felix Auger-Aliassime |
22 |
-93 |
-4.23 |
|
Marin Cilic |
11 |
51 |
4.64 |
|
Benoit Paire |
16 |
227 |
14.19 |
|
Christian Garin |
17 |
103 |
6.06 |
|
Fabio Fognini |
10 |
-187 |
-18.70 |
|
Radu Albot |
6 |
-600 |
-100.00 |
|
Egor Gerasimov |
14 |
401 |
28.64 |
|
Nick Kyrgios |
10 |
51 |
5.10 |
|
Lucas Pouille |
0 |
0 |
N/A |
|
Alexander Bublik |
15 |
406 |
27.07 |
|
Overall |
160 |
293 |
1.83 |
What has happened to the overperforming players?
Of the players from this group who have continued to perform well this year, Wawrinka’s underlying data has improved, while Paire has overperformed by around 5% on saving break points compared to his service points won percentage.
Bublik is in a similar position to the latter, although performing worse on return. Elsewhere, Egor Gerasimov is running 8-3 on tiebreaks this season with an absurd break point overperformance on return.
However, with the exception of Wawrinka, those continuing to perform superbly amongst this group still had variance on their side and will almost certainly mean-revert downwards in the near future.
Naturally, at the time of writing the current season is two months in, meanwhile the value may have eradicated on the undervalued players based on last season’s data. However, this type of research can be performed at any time during the season, enabling you to gain insight into the value of such an approach going forward.
You can read the first article in this series by Dan exploring whether the ATP top ten have ‘clutch’ ability here, the second studying the relationship between points won and win percentages in tennis here and the third looking at the influence of tiebreak points here.