{"id":1434,"date":"2013-11-19T11:38:12","date_gmt":"2013-11-19T16:38:12","guid":{"rendered":"http:\/\/heavytopspin.com\/?p=1434"},"modified":"2013-11-19T11:38:12","modified_gmt":"2013-11-19T16:38:12","slug":"the-speed-of-every-2013-surface","status":"publish","type":"post","link":"https:\/\/www.tennisabstract.com\/blog\/2013\/11\/19\/the-speed-of-every-2013-surface\/","title":{"rendered":"The Speed of Every 2013 Surface"},"content":{"rendered":"

Few debates get tennis fans as riled up as the general slowing–or homogenization<\/a>–of surface speeds. \u00a0While indoor tennis (to take a recent example) is a different animal than it was fifteen or twenty years ago, it’s tough to separate the effect of the court itself from the other changes in the game that have taken place in that time.<\/p>\n

Further, the “court effect” itself is multi-dimensional. \u00a0The surface makes a big difference, as grass will almost always play quicker than a hard court, which will usually<\/a> play faster than clay. \u00a0But as we’ve seen with the persistence of Sao Paulo as one of the fastest-playing events on tour<\/a>,\u00a0altitude is a major factor, as is weather, which can slow down a normally speedy tournament, as was the case with Hurricane Irene at the 2011 US Open<\/a>. \u00a0The choice of balls<\/a> can influence the speed of play as well.<\/p>\n

With all of these factors in play, what we often refer to as “surface speed” is really “court speed” or even “playing environment.” \u00a0It’s not just the surface. \u00a0That said, I’ll continue to use the terms interchangeably.<\/p>\n

Because of there is only limited data available, if we want to quantify surface differences, \u00a0we must use a proxy for court speed. \u00a0What has worked in the past<\/a> is ace rate–adjusted for the server and returner in each match. \u00a0On a fast court–a surface that doesn’t grip the ball; or one like grass with a low, less predictable bounce; or at a high altitude; or in particularly hot weather–a player who normally hits 5% of his service points for aces might see that number increase to 8%. \u00a0(Returners influence ace rate as well.<\/a> A field with Andy Murray<\/a> will allow fewer aces than a field with Juan Martin del Potro<\/a>, so I’ve controlled for that as well.)<\/p>\n

Aggregate these server- and returner-adjusted ace rates, and at the very least, we have an approximation of which courts on tour are most ace-friendly. \u00a0Since most of the characteristics of an ace-friendly court overlap with what we consider to be a fast court, we can use that number as an marker for surface speed.<\/p>\n

2013 Court Speed Numbers<\/strong><\/p>\n

For the second year in a row, the high-altitude\u00a0clay<\/em> of Sao Paulo was the fastest-playing surface on tour. \u00a0The altitude also appears to play a role in making Gstaad quicker than the typical clay.<\/p>\n

As for the slowing of indoor courts, the evidence is inconclusive. \u00a0The O2 Arena, site of the World Tour Finals, rated as slower than average in 2011 and 2012, on a level with some of the slowest hard courts on tour. \u00a0This year, it came out above average, and a three-year weighted average puts the O2 at the exact middle of the ATP court-speed range.<\/p>\n

Valencia and the Paris Masters played about as fast as they have in the past, while Marseille remained near the top of the rankings. If there is evidence for a mass slowing of indoor speeds, it comes from some unlikely sources: Both Moscow and San Jose were among the quickest surfaces on tour in 2010 and 2011, but have been right in the middle of the pack for the last two years.<\/p>\n

The table below shows the relative ace rate of every tournament for the last four years, along with a weighted averaged of the last three years. \u00a0The weighted average is the most useful number here, especially for the smaller 28- and 32-player events. \u00a0The limited extent of a 31-match tournament can amplify the anomalous performance of one player–as you can see from some of the bigger year-to-year movements. \u00a0But over the course of three years, individual outliers have less impact.<\/p>\n

The “Sf” column is each event’s surface: “C” for clay, “H” for hard, and “G” for grass. \u00a0The numbers are multipliers, so Sao Paulo’s three-year weighted average of 1.58 means that players at that event hit 58% more aces than they would have on a neutral court. \u00a0Monte Carlo’s 0.67 means 33% less than neutral.<\/p>\n

Event            Sf  10 A%  11 A%  12 A%  13 A%   3yr  \nSao Paulo        C    1.44   1.08   1.58   1.74  1.58  \nMarseille        H    1.09   1.24   1.41   1.26  1.30  \nHalle            G    1.20   1.39   1.26   1.20  1.25  \nWimbledon        G    1.36   1.18   1.24   1.25  1.24  \nShanghai         H    0.96   1.05   1.08   1.37  1.22  \nMontpellier      H    1.28          1.40   1.16  1.21  \nBrisbane         H    1.01   1.20   1.08   1.27  1.19  \nTokyo            H    1.35   0.98   1.17   1.26  1.18  \nGstaad           C    0.87   1.13   0.90   1.35  1.16  \nWinston-Salem    H           1.20   1.10   1.18  1.16  \n\nChennai          H    0.75   0.77   1.21   1.25  1.16  \nValencia         H    1.02   1.10   1.12   1.19  1.15  \nZagreb           H    1.09   1.16   1.20   1.11  1.15  \nWashington       H    0.96   0.93   1.34   1.10  1.15  \nVienna           H    1.42   1.22   1.01   1.19  1.14  \nSantiago         C    1.23   1.21   0.86   1.29  1.13  \nSydney           H    1.08   1.14   0.94   1.25  1.13  \nAtlanta          H    0.92   0.82   1.06   1.26  1.12  \nEastbourne       G    1.07   1.13   0.92   1.22  1.11  \nQueen's Club     G    1.07   1.13   1.09   1.12  1.11  \n\nParis            H    1.38   0.97   1.16   1.12  1.11  \nCincinnati       H    1.09   1.02   1.08   1.13  1.10  \ns-Hertogenbosch  G    1.13   1.08   1.03   1.15  1.10  \nAuckland         H    1.01   1.08   1.06   1.12  1.09  \nMemphis          H    1.08   1.12   0.95   1.09  1.05  \nStuttgart        C    1.09   1.05   1.04   1.06  1.05  \nBogota           H                         1.09  1.05  \nRotterdam        H    0.88   1.21   0.83   1.12  1.04  \nStockholm        H    0.93   0.96   1.15   0.99  1.04  \nBasel            H    0.98   1.05   1.16   0.96  1.04  \n\nBangkok          H    1.20   1.12   0.73   1.19  1.03  \nAustralian Open  H    0.98   1.10   0.92   1.08  1.03  \nUS Open          H    1.14   0.93   1.06   1.04  1.03  \nSan Jose         H    1.21   1.23   0.96   0.99  1.02  \nMoscow           H    1.28   1.12   1.01   0.99  1.02  \nDubai            H    1.13   1.07   1.14   0.92  1.02  \nDoha             H    0.88   1.29   0.90   0.98  1.00  \nTour Finals      H    1.07   0.93   0.87   1.11  1.00  \nBeijing          H    1.01   1.01   1.06   0.94  0.99  \nCanada           H    0.99   1.02   1.04   0.95  0.99  \n\nMadrid           C    0.76   0.86   1.19   0.89  0.98  \nKitzbuhel        C           1.12   0.70   1.12  0.98  \nMetz             H    1.14   0.96   1.07   0.90  0.97  \nDusseldorf       C                         0.92  0.96  \nMunich           C    0.77   0.82   0.91   0.97  0.92  \nSt. Petersburg   H    1.02   0.84   0.86   0.99  0.92  \nAcapulco         C    0.88   0.89   1.06   0.84  0.92  \nDelray Beach     H    0.98   1.07   0.92   0.85  0.91  \nNewport          G    1.46   0.72   1.04   0.89  0.91  \nKuala Lumpur     H    0.96   0.97   0.81   0.94  0.90  \n\nMiami            H    0.91   0.98   0.86   0.89  0.89  \nUmag             C    0.56   0.74   0.67   1.04  0.87  \nHamburg          C    1.04   0.85   0.75   0.92  0.85  \nBuenos Aires     C    0.84   0.86   0.93   0.74  0.82  \nIndian Wells     H    0.92   0.90   0.86   0.77  0.82  \nRoland Garros    C    0.82   0.86   0.81   0.78  0.81  \nBarcelona        C    0.73   0.65   0.91   0.78  0.80  \nCasablanca       C    0.82   0.91   0.77   0.75  0.79  \nEstoril          C    0.62   0.73   0.79   0.71  0.74  \n\nHouston          C    0.85   0.71   0.71   0.77  0.74  \nBucharest        C    0.61   1.08   0.62   0.68  0.73  \nRome             C    0.78   0.67   0.64   0.81  0.73  \nNice             C    0.88   0.84   0.79   0.64  0.72  \nBastad           C    0.93   0.74   0.86   0.58  0.70  \nMonte Carlo      C    0.63   0.60   0.71   0.67  0.67<\/pre>\n","protected":false},"excerpt":{"rendered":"
Few debates get tennis fans as riled up as the general slowing–or homogenization–of surface speeds. \u00a0While indoor tennis (to take a recent example) is a different animal than it was fifteen or twenty years ago, it’s tough to separate the effect of the court itself from the other changes in the game that have taken … Continue reading The Speed of Every 2013 Surface<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[109],"tags":[],"class_list":["post-1434","post","type-post","status-publish","format-standard","hentry","category-surface-speed"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/posts\/1434","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/comments?post=1434"}],"version-history":[{"count":0,"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/posts\/1434\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/media?parent=1434"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/categories?post=1434"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/tags?post=1434"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}