Apr 20, 2020
Apr 20, 2020

The role of court speed in tennis betting

Which are the 'fastest' and 'slowest' tennis courts?

How to determine big servers and strong returners

Court speed influence on tennis betting

Betting performance of big servers and strong returners

The role of court speed in tennis betting

Court speed is an important metric that all tennis bettors should factor into their pre-match betting analysis. Dan Weston takes a look at the relationship between court speed and player performance and the impact this can have on tennis betting.

Which are the ‘fastest’ and ‘slowest’ tennis courts?

In the article Understanding court speeds in tennis, surface and mean service hold percentage data was utilised to determine the fastest and slowest courts on the ATP Tour, which are as follows:

Fastest courts

Slowest courts

Antalya

Barcelona

Atlanta

Bastad

Auckland

Budapest

Auckland

Budapest

Brisbane

Buenos Aires

Cincinnati

Estoril

Hertogenbosch

Hamburg

Madrid

Marrakech

Marseilles

Monte Carlo

New York (non-Grand Slam)

Munich

Paris (non-Grand Slam)

Rio de Janiero

Queens

Umag

Shanghai

Stuttgart

It was also established that fast and slow courts have different characteristics that favour big servers and strong returners respectively.

How to determine ‘big servers’ and ‘strong returners’

With this in mind, court speed can be analysed from a different perspective to assess which players are particularly adept at performing on fast and slow courts.

As mentioned, fast courts suit big servers – players who deploy a style which is most palpably serve-dominated. While establishing the players who fall into this category is an exercise that can be completed from an entirely subjective basis, there is a useful formula that bettors can use to highlight the big servers:

(Percentage of serves held) - (Percentage of breaks won against opponent)

When using this formula, the players with the largest difference between the two percentages can be classed as big servers. The table below highlights the top ten ATP big servers throughout 2019:

ATP top ten big servers in 2019

Player

Serves held (%)

Breaks won (%)

Difference

John Isner

94.1%

9.7%

84.4%

Reilly Opelka

90.9%

10.6%

80.3%

Milos Raonic

92.9%

14.1%

78.8%

Nick Krygios

88.1%

13.2%

74.9%

Sam Querrey

87.0%

16.1%

70.9%

Matteo Berretini

87.3%

17.8%

69.5%

Taylor Harry Fritz

84.2%

15.7%

68.5%

Jo-Wilfried Tsonga

86.4%

18.0%

68.4%

Stanislas Wawrinka

86.5%

18.7%

67.8%

Stefanos Tsitsipas

85.6%

19.6%

66.0%

As the table above illustrates, three players held their serve at least 90% of the time – John Isner, Milos Raonic and Reilly Opelka. Notably, all ten broke their opponents’ serve less than 20% of the time, underlining their serve-orientated style.

Conversely, those with the smallest difference between percentage of serves held and percentage of breaks won against their opponent can be considered strong returners. These players will break opponents much more frequently but hold their serve considerably less than the ten players above.

The table below highlights the top ten strongest returners during the 2019 ATP season:

ATP top ten strong returners in 2019

Player

Serves held (%)

Breaks won (%)

Difference

Diego Schwartzmann

75.3%

31.5%

43.8%

Yoshihito Nishioka

72.6%

26.6%

46.0%

Fabio Fognini

73.1%

26.6%

46.5%

David Goffin

78.4%

27.8%

50.6%

Kei Nishikori

79.7%

28.5%

51.2%

Filip Krajinovic

79.0%

27.3%

51.7%

Dusan Lajovic

75.6%

23.2%

52.4%

Nikoloz Basilashvili

76.0%

23.3%

52.7%

Albert Ramos-Vinolas

79.0%

25.1%

53.9%

Daniel Evans

80.3%

26.4%

53.9%

The differing trends among these ten players are evident. Only one (Daniel Evans) held more than 80% of his serves and all of them won at least 20% of breaks against their opponent.

Court speed influence on tennis betting

Having established the players who are the most serve and return-orientated on the ATP Tour, it can be assessed as to whether an edge emerged by betting on them when they were playing on the aforementioned fast and slow courts throughout 2019.

For the first part of this, a hypothetical €100 stake was placed on the top ten big servers for all of their ATP Main Tour and qualifying matches on the listed fast courts throughout last year. The results were as follows:

Betting performance of ATP top ten big servers on fast courts in 2019

Player

Matches played

Matches won

Win rate (%)

Profit / Loss

ROI

John Isner

10

5

50.00%

-€249

-24.90%

Reilly Opelka

14

9

64.29%

€172

12.29%

Milos Raonic

10

7

70.00%

€27

2.70%

Nick Krygios

8

3

37.50%

-€414

-51.75%

Sam Querrey

7

4

57.14%

-€154

-22.00%

Matteo Berrettini

17

12

70.59%

€403

23.71%

Taylor Harry Fritz

14

8

57.14%

-€42

-3.00%

Jo-Wilfried Tsonga

8

5

62.50%

€50

6.25%

Sanislas Wawrinka

13

9

69.23%

€74

5.69%

Stefanos Tsitsipas

21

16

76.19%

€1184

56.38%

Total

122

78

63.93%

€1051

8.61%

Despite the fact that four of the ten players produced a negative return on investment (ROI), the €100 bet on the 122 matches would have still produced an overall profit of €1051, resulting in an encouraging return on investment rate of 8.61%.

In terms of the player performances, six recorded an impressive win rate of above 60%, of which three returned a formidable 70% and above. Only one player amongst the ten (Nick Krygios) lost more matches than he won on fast courts last year.

Notably, three of the four players who produced negative ROIs did so despite achieving win rates of at least 50%, indicating that the assertion that big servers are strongly suited to faster courts has begun to proliferate the betting market and they were strong favourites for the matches they did win.

The equivalent stats for the ATP top ten strong returners on slow courts throughout last year are as follows:

Betting performance of ATP top ten strong returners on slow courts in 2019

Player

Matches played

Matches won

Win rate (%)

Profit / Loss

ROI

Diego Schwartzmann

10

6

60.00%

€75

7.50%

Yoshihito Nishioka

3

1

33.33%

-€134

-44.67%

Fabio Fognini

16

13

81.25%

€1039

64.94%

David Goffin

6

3

50.00%

-€203

-33.83%

Kei Nishikori

5

3

60.00%

-€95

-19.00%

Filip Krajinovic

10

7

70.00%

€24

2.40%

Dusan Lajovic

15

10

66.67%

€760

50.67%

Nikoloz Basilashvili

7

5

71.43%

€377

53.86%

Albert Ramos-Vinolas

13

9

69.23%

€315

24.23%

Daniel Evans

1

0

0.00%

-€100

-100%

Total

86

57

66.28%

€2058

23.93%

The betting performance of the strong returners was even better, generating a profit of €2058 from just 86 matches for a return on investment rate of 23.93%.

Again, four of the ten players produced a negative ROI, although notably on this occasion they were the four players who contested the least matches among the sample. All but three enjoyed a win rate of at least 60%, with Fabio Fognini recording the highest win rate from both groups of 81.25%.

Conclusions and things to consider

Overall, by wagering €100 on the 208 matches that the ATP’s most pertinent big servers and strong returners contested on fast and slow courts respectively last year, bettors would have received a total profit of €3109.

Of the 208 individual bets, 135 (or 64.90%) would have won to produce a superb return on investment rate of 14.95%. Amongst these, each player who participated in at least ten matches recorded a win rate – and therefore, a winning bet rate – of at least 50%.

The above data not only supports the findings that certain players are suited to specific court speeds, but more importantly offers weight to the assertion that bettors need to strongly consider court conditions as part of their pre-match betting analysis.

This particularly appears to be the case when a player deemed a strong returner is contesting a match on a court with a slower than average speed.

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