{"id":2591,"date":"2018-04-25T14:15:33","date_gmt":"2018-04-25T14:15:33","guid":{"rendered":"http:\/\/www.tennisabstract.com\/blog\/?p=2591"},"modified":"2018-04-25T14:15:33","modified_gmt":"2018-04-25T14:15:33","slug":"translating-atp-statistics-across-main-tour-and-challenger-levels","status":"publish","type":"post","link":"https:\/\/www.tennisabstract.com\/blog\/2018\/04\/25\/translating-atp-statistics-across-main-tour-and-challenger-levels\/","title":{"rendered":"Translating ATP Statistics Across Main Tour and Challenger Levels"},"content":{"rendered":"

Italian translation at settesei.it<\/em><\/a><\/p>\n

What is the gap between the top-level ATP Tour and the lower-level ATP Challenger Tour? Some players pile up trophies in the minor leagues yet have a hard time converting that success to match wins on the big tour, while others struggle with the week-to-week grind of the challengers but excel when given opportunities on the larger stage.<\/p>\n

Let’s take a look at a method that measures the difference between the skill level on the two tours. Once we can translate stats between levels, we can identify those players who are much better or worse than expected when they have the chance to compete against the best.<\/p>\n

The algorithm I’ll use is almost identical to the one baseball analysts have used for decades to determine league equivalencies<\/a>. For instance, we might find that a batting average of .300 in Triple-A (the highest minor league) is equivalent to .280 in the majors, meaning that, if a player is batting .300 in Triple-A, we’ll expect him to bat .280 in the majors. In tennis terms, it may be that a 10% ace rate in challengers is equivalent to a 8% ace rate on the main tour. Not every player will exhibit that precise drop in performance–some may even appear to get a little better–but on average, a league equivalency tells us what to expect when a player changes levels.<\/p>\n

Here is the algorithm for league equivalencies, as applied to men’s tennis:<\/p>\n

    \n
  1. Pick a stat to focus on. I’ll use Total Points Won (TPW) here.<\/li>\n
  2. Neutralize that stat as much as possible. In baseball, that means controlling for the difference in parks; in tennis, it means controlling for competition. For the following, I’ve adjusted for each player’s quality of competition using a method I described about a year ago<\/a>. Most players’ numbers are about the same after the adjustment, but a particularly easy or tough schedule means a bigger shift. For instance, Denis Shapovalov<\/a> posted a TPW of 49.8% on the big tour last season, but because he played such high-quality competition, the adjustment bumps him up to 52.1%, 18th among tour regulars.<\/li>\n
  3. Identify players who competed at both levels, and find their adjusted stats at each level. Shapovalov played 18 tour-level matches and 30 challenger-level matches last year, with adjusted TPW numbers of 52.1% and 54.4%, respectively.<\/li>\n
  4. Calculate the ratio for each player. For Shapovalov last year, it was 1.044 (54.4 \/ 52.1).<\/li>\n
  5. Finally, take a weighted average of every player’s ratio. The weight is determined by the minimum number of matches played at either level, so for Shapovalov, it’s 18. Using the minimum means that a player like Gleb Sakharov<\/a> (1 ATP match, 37 challenger matches) can be included in the calculation, but has very little effect on the end result.<\/li>\n<\/ol>\n

    Here are the results for the last six full seasons. Each ratio is the relationship between challenger-level TPW and tour-level TPW:<\/p>\n

    Year  Ratio  \n2017  1.086  \n2016  1.086  \n2015  1.098  \n2014  1.103  \n2013  1.100  \n2012  1.100<\/pre>\n
    The average of these yearly equivalency factors is roughly the difference between a 52.5% TPW at challengers and a 48.0% TPW on the main tour. The shift from 2012-15 to 2016-17 may reflect the injuries that have sidelined the elites. With fewer elite players on court, the gap between the two tours narrows.<\/p>\n
    Now that we know the difference between the levels, we can find the players who defy the usual patterns. Of the 100 players with the most “paired” matches–that is, with the most matches at both levels in the same years–here are the 20 with the lowest ratios. Low ratios mean less difference in performance between the two levels, so these guys are either overperforming at tour level or underperforming at challengers:<\/p>\n
    Player              ATP M  CH M  Min M  Ratio  \nMatthew Ebden          62   140     39  0.982  \nJared Donaldson        68    78     37  1.030  \nJack Sock              81    45     38  1.039  \nJames Duckworth        53   156     53  1.042  \nAndrey Rublev          56    79     42  1.047  \nVasek Pospisil         96    76     60  1.047  \nThiemo De Bakker       48    87     44  1.048  \nSamuel Groth           84   133     58  1.049  \nMichael Berrer         59   107     56  1.050  \nRuben Bemelmans        41   178     41  1.052  \nDustin Brown          120   173    111  1.055  \nBenoit Paire          295    53     53  1.059  \nPeter Gojowczyk        46   132     44  1.059  \nMichael Russell        58    78     58  1.061  \nMarius Copil           58   180     58  1.063  \nTaylor Harry Fritz     59    44     41  1.065  \nJordan Thompson        38    88     38  1.066  \nIllya Marchenko        56   116     37  1.066  \nTatsuma Ito            65   179     65  1.066  \nRyan Harrison         124    84     59  1.068<\/pre>\n
    The middle columns show the total number of ATP matches, challenger matches, and “paired” matches between 2012 and 2017 (“Min M”) for each player. (The last number gives an indication of just how much data was available for the single-player calculation.) Aside from a few big-serving North Americans near the top of this list, I don’t see a lot of obvious commonalities. There are some youngsters, some veterans, more big servers than not, but nothing obvious.<\/p>\n
    (Shapovalov doesn’t have enough paired matches to qualify, but his overall ratio is 1.035, good for third on this list.)<\/p>\n
    Here is the opposite list, the quintile of 20 players who have overperformed at challengers or underperformed on tour:<\/p>\n
    Player               ATP M  CH M  Min M  Ratio  \nFlorian Mayer          152    45     45  1.180  \nMikhail Youzhny         91    38     38  1.169  \nAljaz Bedene           144   121     80  1.160  \nFilippo Volandri        62   101     62  1.158  \nRobin Haase            194    71     71  1.157  \nTobias Kamke           102   144     73  1.155  \nAdrian Mannarino       234   115     86  1.155  \nFilip Krajinovic        36   167     36  1.148  \nAlbert Ramos           111    67     62  1.144  \nPaul Henri Mathieu     147    96     82  1.141  \nKenny De Schepper       77   196     77  1.140  \nFacundo Bagnis          45   197     45  1.136  \nPablo Cuevas           127    52     43  1.136  \nIvan Dodig              76    48     41  1.135  \nSantiago Giraldo       146    70     56  1.135  \nPaolo Lorenzi          204   191    124  1.135  \nThomaz Bellucci        162    44     44  1.134  \nAlbert Montanes        113   109     70  1.130  \nRogerio Dutra Silva     57   210     57  1.130  \nLukas Lacko            122   181    108  1.129<\/pre>\n
    There are more clay-courters here than on the first list, and the very top of the ranking includes veterans who have mastered the challenger level, even if they still struggle to maintain a foothold on the main tour. I’ve had to exclude one player who belongs on this list: Gilles Muller<\/a> broke my algorithm with his 45-9 challenger season in 2014. When I took him out of the 2014 calculations, the overall numbers changed very little, but it means no Muller here. Whatever his exact ratio, I can say that his tour-level performance hasn’t matched that 2014 run at challengers.<\/p>\n
    The bottoms of the two lists indicate that there isn’t that much variation between players. The middle 60% of players all have ratios between about 1.07 and 1.13, while the yearly averages hover around 1.09 and 1.10. Some players under consideration here have fewer than 50 “paired” matches over the six seasons, so a difference of a couple hundredths is far too little to draw any conclusions.<\/p>\n
    This algorithm, beyond suggesting what to expect from players when they move up from challengers to the main tour, could apply the same reasoning to other pairs of levels, such as ITF Futures and challengers, or women’s ITFs and the WTA tour. It could even compare narrower levels, such as ITF $10,000 events with ITF $15,000s, or ATP 250s with ATP 500s. The method is a staple of analytics in other sports, and it has a place in tennis, as well.<\/p>\n","protected":false},"excerpt":{"rendered":"
    Italian translation at settesei.it What is the gap between the top-level ATP Tour and the lower-level ATP Challenger Tour? Some players pile up trophies in the minor leagues yet have a hard time converting that success to match wins on the big tour, while others struggle with the week-to-week grind of the challengers but excel … Continue reading Translating ATP Statistics Across Main Tour and Challenger Levels<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","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":[16,96],"tags":[],"class_list":["post-2591","post","type-post","status-publish","format-standard","hentry","category-challengers","category-research"],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack-related-posts":[],"_links":{"self":[{"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/posts\/2591","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=2591"}],"version-history":[{"count":0,"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/posts\/2591\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/media?parent=2591"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/categories?post=2591"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tennisabstract.com\/blog\/wp-json\/wp\/v2\/tags?post=2591"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}