Jan 16, 2015
Jan 16, 2015

Court speed and tennis betting

Court speed and tennis betting
Court speed is an important metric that tennis bettors should factor into their pre-match tennis betting analysis. See how the relationship between court speed and player characteristics, should impact your tennis betting.

Past Court speed and tennis betting research

Previously - in this article - we looked at court speed and the impact that fast and slow courts have on handicap betting. We used respective surface mean service hold percentage data to determine the fastest and slowest courts on the ATP Tour (See below). We also established that fast and slow courts have different characteristics, which favour either big servers (fast) or strong returners (slow). 

Fast CourtSlow Court
Munich Umag
Gstaad Newport
Atlanta Monte Carlo
Shanghai Miami
Madrid Dusseldorf
Marseille Kuala Lumpur
Sao Paulo Nice
Beijing Moscow
Brisbane Hamburg
Vina Del Mar Eastbourne

How to determine a 'big server' in tennis

However, this article looks at court speed from a different perspective. With top servers holding around 90% of the time on average, playing on fast surfaces should further boost this figure.

Most bettors perceive 'big-servers' on an entirely subjective basis.  However, there is a very useful metric bettors can use to highlight the 'big servers':

Service Hold % - Break Opponent %

When using this formula, the players with the biggest difference percentage are classed as the 'big servers' – their style will almost be entirely serve-dominated. The data below highlights the top ten ATP 'big servers' during 2014:

PlayerHold %Break %Difference %
Karlovic 92.6 8.8 83.8
Isner 93.1 9.3 83.8
Groth 88.8 9.6 79.2
De Schepper 81.9 5.6 76.3
Raonic 90 16.3 73.7
Lopez 86.5 14.1 72.4
Johnson 84.4 14 70.4
Tomic 84.8 14.4 70.4
Querrey 86.3 16.6 69.9
Tsonga 87.3 18.2 69.1

Looking at the table above, we can see that three players held their serve 90% or higher - Ivo Karlovic, John Isner and Milos Raonic, and that of the trio, Raonic (who breaks opponents 16.3% of the time) has the superior return game by some distance.

Sam Groth and Kenny De Schepper joined Karlovic and Isner in breaking opponents less than 10% of the time and were also highly ranked as the most serve-orientated players on tour.

How to determine a 'returner' in tennis

Similarly, we can do the same for players stronger on return - the ‘grinders’.  These players will break opponents much more frequently but hold their serve much less than the 'big servers'.

The top ten ‘grinders’ on the ATP Tour for the 2014 season by this metric (from a reasonable sample size) were the following:

PlayerHold %Break %Difference %
Andujar 73.3 29 44.3
Monaco 73.4 28.8 44.6
Lorenzi 73 27.5 45.5
Fognini 72.9 27.3 45.6
Ferrer 78.9 33.1 45.8
Belocq 73.1 27.2 45.9
Ebden 64.3 18.1 46.2
Falla 69.2 22.3 46.9
Garcia-Lopez 73.6 25.9 47.7
Gabashvili 71.7 23.8 47.9

These ten players were grouped very closely and it’s of little surprise that the vast majority (only Matt Ebden and Alejandro Falla could be excused from this statement) of these players are stronger on clay than on hard surfaces.

Having established the players who are most serve and return orientated on the ATP Tour, we can then look at historical results to see if there was an edge betting on them on fast or slow surfaces in tournaments in 2014 – the courts mentioned earlier in the article.

To clarify, a hypothetical £100 stake was applied to all matches where at least one set was completed. All ATP Main Tour and Qualifier matches were included:

Player (Servers)MatchesWinsWin %P/LROI
Karlovic 5 2 40.0 151 30.2
Isner 13 10 76.9 110 8.5
Groth 6 4 66.7 254 42.3
De Schepper 3 1 33.3 -103 -34.3
Raonic 2 1 50.0 -66 -33.0
Lopez 12 7 58.3 302 25.2
Johnson 3 1 33.3 -131 -43.7
Tomic 5 3 60.0 136 27.2
Querrey 4 2 50.0 -44 -11.0
Tsonga 6 4 66.7 -117 -19.5
Overall 59 35 59.3 492 8.3

Player (ReturnersMatchesWinsWin %P/LROI
Andujar 9 6 66.7 89 9.9
Monaco 6 3 50.0 -176 -29.3
Lorenzi 3 0 0.0 -300 -100.0
Fognini 11 6 54.5 -207 -18.8
Ferrer 11 9 81.8 624 56.7
Berlocq 6 3 50.0 -163 -27.2
Ebden 4 1 25.0 -219 -54.8
Falla 1 0 0.0 -100 -100.0
Garcia-Lopez 8 5 62.5 927 115.9
Gabashvili 12 7 58.3 293 24.4
Overall 71 40 56.3 768 10.8

Courts speed analysis

While there were only 59 and 71 matches sampled for the two respective brackets, blind-backing both 'big servers' on fast surfaces and 'grinders' on slow surfaces produced very strong returns of 8.3% and 10.8% respectively.

Combined, profits of £1260 were generated from a stake of £13,000, giving a superb return on investment of 9.7%.

Several big servers in particular performed well in fast conditions last season - Ivo Karlovic managed to beat US Open Champion Marin Cilic (with a starting price of 4.651) in Shanghai, whilst John Isner took the title in Atlanta. 

Feliciano Lopez reached the semi-final of Shanghai (a magnificent achievement for a player outside the top 20 in a Masters-level event), whilst Milos Raonic reached the final of Brisbane last week (not included in the results). 

Results for the players stronger on return were very variable, but David Ferrer, Guillermo Garcia-Lopez and Teymuraz Gabashvili were three players who thrived on slow surfaces in 2014.

Ferrer got the better of his nemesis Rafael Nadal in the quarter-final of Monte Carlo, whilst Garcia-Lopez managed three wins (against Tomas Berdych, Alexandr Dolgopolov and Gael Monfils) when priced over 4.00 on slow courts.

The above data clearly indicates that there was an overall big edge backing 'big servers' in fast conditions and 'grinders' in slow conditions during 2014, and gives even more weight to the assertion that bettors need to strongly consider court conditions as part of their pre-match betting analysis.

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