Article - Impact of winning a 10-8+ final set in Grand Slams


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There can be no doubt that the performances of Gilles Simon this week were incredible and statistically defying – having left the court on crutches at the Kooyong Exhibition after turning his ankle, he has been abandoned by the market, yet somehow defeated Daniel Brands 16-14 in the final set of his first round match, before following this up with a 5-set win over Marin Cilic, coming back from 2-1 down to destroy the Croat in the final two sets.

The victory (and his comeback) against Cilic in particular was a shock to many, including myself, as there can be no doubt which player expended more energy in their first round match, as well as the obvious injury doubt over Simon as well.  

So what I decided to do for this article is to assess the effect of a long final set in a Grand Slam on a player’s subsequent match, with a view to seeing if there were any profitable betting or trading angles that we can exploit in the future.  Obviously this effect is unique to Grand Slams as they are unique to ATP/WTA matches in that they don’t have a final set tie-break (except for the US Open, which does).

For clarity, a long final set is considered to be any final set which is equal to or longer than 10-8 in scoreline.

From the table below, we can see that there were just 34 matches in the ATP/WTA combined where a player won the final set by a scoreline of 10-8 or more between 2010-2013, so the sample wasn't fantastic, but shows some interesting trends.

22 matches were in the ATP where I'd expect the effect of the long match to be bigger, given that the men play 5 sets.  Just 7 ATP players won their subsequent match, with 14 losing.  Fognini gave a walkover following an 11-9 final set win in the previous round.

In those 22 matches, should the player that won the previous round match by 10-8 or more in the final set have been backed with £100 level stakes, the loss incurred would have been £767 which generated a return of invesment of -36.52%.  Whilst the sample is small, there can be little doubt that this return is shocking.

However, when comparing favourites to underdogs, the contrast is stark.

When an ATP player won the final set of the previous round match by 10-8 or more, and was favourite in the next match, they actually won their subsequent match 6 out of 7 times, compared to just 1 win from 14 when the player started their next match as underdog.  That win was our friend Gilles Simon, illustrating just how much he bucked the statistical trend with his win over Cilic.

WTA players also incurred a loss when backing them for £100 level stakes in their subsequent match following a 10-8+ third set win, although the sample was tiny.  They won 5 of the 12 next round matches, and several underdogs (Wickmayer at 2.02 and Petrova at 3.24) won their next match.

Only three players were favourites in their next match in the WTA and they all emerged victorious (Makarova at 1.26, Paszek at 1.52 and McHale at 1.29).  

It's very interesting to see the negative impact on the underdogs compared to the favourites, with the underdogs obviously tending to be the lower-ranked player.  This goes along with my research for the impact of 5-set matches on lower ranked players, where they generated a horrific ROI for their next match following a 5-set victory.

Overall, the loss incurred when backing WTA players here was £267, generating an ROI of -22.25% - not as bad as the ATP, although it's not pretty.  When the two tours were combined, the loss was -£1034, and the ROI was -31.33%.  

A final area that I want to quickly look at is the underdogs in play.  3 of the 23 underdogs won the match, but a further 6 led in sets and eventually lost, so from this small sample it appears that laying these underdogs in-play could well be viable when leading by a set.  

Below is the table with the sample data:-

Tour Year Event Player Previous Match Opening Closing  Implied % W/L £100 stake Lost but
Final Set Score Price Price Change P&L lead in sets
Next Match Next Match
ATP 2010 Australian Del Potro 10-8 1.12 1.11 0.80 W 11
ATP 2012 Australian Isner 10-8 1.96 1.7 7.80 L -100 N
ATP 2013 Australian Roger-Vasselin 11-9 3.26 5.06 -10.91 L -100 Y
ATP 2013 Australian Kavcic 10-8 15.13 28.67 -3.12 L -100 N
ATP 2013 Australian Djokovic 12-10 1.19 1.23 -2.73 W 23
ATP 2014 Australian Simon 16-14 3.18 4.29 -8.14 W 329
ATP 2010 French Lacko 12-10 9.17 11.4 -2.13 L -100 Y
ATP 2010 French Ljubicic 10-8 1.75 2.38 -15.13 L -100 N
ATP 2011 French Garcia-Lopez 13-11 2.4 2.6 -3.21 L -100 Y
ATP 2011 French Fognini 11-9 gave walkover
ATP 2012 French Chardy 11-9 5.83 6.1 -0.76 L -100 N
ATP 2012 French Anderson 11-9 1.65 1.75 -3.46 W 75
ATP 2012 French Mathieu 18-16 1.9 2.22 -7.59 L -100 N
ATP 2013 French Pella 12-10 32.68 40.55 -0.59 L -100 N
ATP 2013 French Haas 10-8 2.05 1.82 6.16 W 82
ATP 2010 Wimbledon Isner 70-68 2.16 2.05 2.48 L -100 N *
ATP 2010 Wimbledon De Bakker 16-14 1.83 1.91 -2.29 W 91 *
ATP 2010 Wimbledon Tsonga 10-8 1.31 1.22 5.63 W 22
ATP 2012 Wimbledon Garcia-Lopez 10-8 15.21 17.75 -0.94 L -100 Y
ATP 2012 Wimbledon Klizan 11-9 5.49 5.64 -0.48 L -100 Y
ATP 2012 Wimbledon Cilic 17-15 4.35 5.16 -3.61 L -100 N
ATP 2013 Wimbledon Zemlja 11-9 9.14 9.82 -0.76 L -100 N
WTA 2010 Australian Wickmayer 10-8 2.05 2.02 0.72 W 102
WTA 2011 Australian Makarova 10-8 1.32 1.26 3.61 W 26
WTA 2011 Australian Schiavone 16-14 6.09 6.12 -0.08 L -100 Y
WTA 2012 Australian Arn 10-8 19.27 17.24 0.61 L -100 N
WTA 2013 Australian Cornet 10-8 8.29 10.9 -2.89 L -100 N
WTA 2013 Australian Mladenovic 11-9 4.73 6.28 -5.22 L -100 N
WTA 2013 Australian Muguruza 14-12 18.26 32.21 -2.37 L -100 N
WTA 2013 Australian Robson 11-9 2.71 2.88 -2.18 L -100 N
WTA 2010 French Petrova 10-8 3.43 3.24 1.71 W 224
WTA 2011 Wimbledon Paszek 11-9 1.79 1.52 9.92 W 52
WTA 2012 Wimbledon McHale 10-8 1.32 1.29 1.76 W 29
WTA 2012 Wimbledon Soler-Espinosa 10-8 4.47 5.68 -4.77 L -100 N

* Isner and De Bakker played each other in the subsequent round
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