It’s worth mentioning that the table below illustrates that only one player currently ranked 11-25 – Jerzy Janowicz – has reached the 6^th round (semi-final) of a Grand Slam and this gives further weight to the general consensus that Grand Slams strongly favour the top players.

The ATP service hold average for the previous 12 months is currently 78.5% at the time of writing, and in the table below showing the data for the players ranked 11-25, we can see there is a large discrepancy between the players, with six players holding serve 79.5% or below, and nine players holding serve 82.7% or above (no player held serve between 79.5% and 82.7%).

When taking into account service breaks of opponent, clearly the average is 21.5% (100-78.5) and there are five players who break their opponent’s serve less than 20% and hold over 82.7% – Milos Raonic (15.5%), John Isner (12.2%), Kevin Anderson (17.7%), Jerzy Janowicz (17.4%) and Philipp Kohlschreiber (19.8%).  Bearing this in mind, it is clear that these five players are the big servers ranked 11-25.

What the stats suggest on big servers

Between 2011 & 2013, these five players had the following Grand Slam records (when ranked within the top 40):

For clarity, only matches where at least one set is completed are included, and all prices used are Pinnacle closing prices.

Player	Matches	Wins	Best Win/Odds	Worst Defeat/Odds	Profit/Loss (based on level £100)
Milos Raonic	27	18	P. Kohlschreiber (1.677)	M. Berrer (1.181)	-£534 (-20.54% ROI)
John Isner	25	16	R. Stepanek (2.462)	A. Falla (1.135)	-£161 (-6.44% ROI)
Kevin Anderson	28	17	M. Raonic (2.337)	M. Baghdatis (1.404)	-£486 (-17.36% ROI)
Jerzy Janowicz	13	9	R. Stepanek (1.837)	M. Gonzalez (1.084)	£2 (0.08% ROI)
Philipp Kohlschreiber	25	16	J. Isner (4.603)	D. Istomin (1.274)	£215 (8.60% ROI)*

* Kohlschreiber’s two biggest wins were both against Isner (4.603 and 3.600) and without these matches against a fellow ‘big server’ his record would have showed a loss.  Furthermore, it can be seen that Raonic, Anderson and Kohlschreiber’s best wins were against one of these five players.

These figures illustrate how poorly big servers perform in Grand Slam events.  Only Phillip Kohlschreiber (notably the player with the best break of opponent percentage) recorded a win when priced over 2.50 between 2011 and 2013, and the combined records are as follows:

Player	Matches	Wins	Profit/Loss (based on level £100)
Combined Player Stats	118	76	-£964 (-8.17% ROI)

Why is this the case?  The table below provides some answers…

Player	Service Hold %	Opponent Break %	Match Win %	Sets per match*	Games per set*	Games per match*	7-5+ set per match %	5 Set Match %	Best Finish (Round)	Round Eliminated*
Raonic	91.3	15.5	18	3.52	10.17	35.78	30.53	10.71	4	2.80
Haas	83.4	23.7	9	3.57	10.36	37.00	36.00	21.43	5	2.80
Almagro	84.9	24.7	26	3.76	10.29	37.63	28.78	21.05	5	3.17
Isner	90	12.2	16	4.08	10.89	42.73	40.20	34.62	5	2.60
Youzhny	79.5	24.9	24	3.78	9.59	36.22	23.53	25.00	5	3.00
Fognini	72.6	30.5	3	3.43	9.71	33.39	33.33	0.00	3	1.75
Nishikori	78.7	29.2	16	3.48	9.10	31.65	17.50	13.04	5	3.29
Robredo	78.7	26.8	10	3.57	9.44	33.71	22.00	21.43	5	3.50
Simon	73.9	27	20	4.10	9.77	40.10	27.73	36.67	4	3.00
Anderson	85.6	17.7	17	3.64	9.90	36.07	27.45	17.86	4	2.55
Janowicz	82.9	17.4	9	3.58	10.14	36.33	27.91	15.38	6	3.25
Kohlschreiber	84.4	19.8	16	3.71	10.04	37.25	33.71	20.83	5	2.89
Dimitrov	83.7	21.4	3	3.80	9.84	37.40	21.05	33.33	3	2.00
Gulbis	82.7	25.8	3	3.50	10.24	35.83	33.33	14.29	3	1.75
Seppi	76.7	23.1	14	4.14	10.14	41.95	36.26	47.83	4	2.56
11-25 Mean	81.93	22.65	64.15	3.65	9.99	36.45	29.31	23.58	4.4	2.73
Big Servers Mean	86.84	16.52	63.33	3.72	10.25	37.75	32.48	20.00	4.8	2.82

* Stats based on the player average

The first area to look at is the amount of sets per match.  The data from this was inconclusive, with Isner playing more sets per match than all but two players (Gilles Simon and Andreas Seppi) but only Fabio Fognini, Kei Nishikori and Ernests Gulbis playing less sets per match than Milos Raonic.  When the five players were grouped together, they averaged 3.72 sets per match, marginally above the 3.65 set average for this 11-25 ranked bracket of players.

However, it can be seen that there is a very clear bias for big servers in the games per set area.  Only Kevin Anderson (9.90) was below the 11-25 mean of 9.99, with Isner’s games per set the highest at an incredible 10.89.  The five ‘big servers’ averaged 10.25 games per set on average, which is a fair bit above the 9.99 mean.

The effect of this is fairly obvious – as ‘big servers’ play more games per set, their sets are tighter. Tight sets mean that even smaller margins than usual decide the winner of a set (such as a tiebreak) and require more mental strength and concentration than straightforward sets.

We can see that Raonic, Kohlschreiber and especially Isner all play tighter sets (7-5 or bigger) more often than the 11-25 rank average of 29.31%.  Isner’s 40.20% is considerably higher than any other player.  The five ‘big servers’ grouped together have an average of 32.48%, 3.17% higher than the 11-25 rank average.

Looking at sets per match, the data somewhat surprisingly highlights that the ‘big servers’ do not play significantly more games per match than the 11-25 rank average.  The five players combined played 37.75 games per match, compared to the 11-25 rank average of 36.45 games per match.  Indeed, Raonic, Anderson and Janowicz actually played fewer games per match than the average.

Evidence shows big servers struggle in Grand Slams

On that basis it can be concluded that the tight nature of a ‘big servers’ match may hinder them from succeeding in Grand Slams, and because these players require more intense concentration and mental strength for longer than other types of player, the fatigue that this generates may affect them in the rounds following a victory.

There can be no doubt that Isner is an extreme example – he played the most games per set and the most games per match by a considerable distance in the 11-25 ranking bracket, as well as the tightest sets by some margin. The accumulated fatigue for Isner as well as the tight nature of his matches, explains why the giant American has failed to go further than a Grand Slam quarter-final.

Finally some other players are worth considering – it is clear from the stats that both Tommy Haas and Andreas Seppi have tendencies to play tight, and in the case of Seppi especially, long Grand Slam matches.

The opposite can definitely be said for Kei Nishikori (9.10 games per set and 31.65 games per match), Tommy Robredo and Fabio Fognini.  It can be no coincidence that these three players broke their opponents more than any other analysed.

As with any form of betting, detailed analysis of a player and their historical tendencies are vital to achieve success.  Men’s Grand Slam tennis tournaments are a much different betting proposition to normal ATP events and must be treated as such.