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 when given opportunities on the larger stage.
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.
The algorithm I’ll use is almost identical to the one baseball analysts have used for decades to determine league equivalencies. 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.
Here is the algorithm for league equivalencies, as applied to men’s tennis:
- Pick a stat to focus on. I’ll use Total Points Won (TPW) here.
- 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. 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 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.
- 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.
- Calculate the ratio for each player. For Shapovalov last year, it was 1.044 (54.4 / 52.1).
- 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 (1 ATP match, 37 challenger matches) can be included in the calculation, but has very little effect on the end result.
Here are the results for the last six full seasons. Each ratio is the relationship between challenger-level TPW and tour-level TPW:
Year Ratio 2017 1.086 2016 1.086 2015 1.098 2014 1.103 2013 1.100 2012 1.100
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.
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:
Player ATP M CH M Min M Ratio Matthew Ebden 62 140 39 0.982 Jared Donaldson 68 78 37 1.030 Jack Sock 81 45 38 1.039 James Duckworth 53 156 53 1.042 Andrey Rublev 56 79 42 1.047 Vasek Pospisil 96 76 60 1.047 Thiemo De Bakker 48 87 44 1.048 Samuel Groth 84 133 58 1.049 Michael Berrer 59 107 56 1.050 Ruben Bemelmans 41 178 41 1.052 Dustin Brown 120 173 111 1.055 Benoit Paire 295 53 53 1.059 Peter Gojowczyk 46 132 44 1.059 Michael Russell 58 78 58 1.061 Marius Copil 58 180 58 1.063 Taylor Harry Fritz 59 44 41 1.065 Jordan Thompson 38 88 38 1.066 Illya Marchenko 56 116 37 1.066 Tatsuma Ito 65 179 65 1.066 Ryan Harrison 124 84 59 1.068
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.
(Shapovalov doesn’t have enough paired matches to qualify, but his overall ratio is 1.035, good for third on this list.)
Here is the opposite list, the quintile of 20 players who have overperformed at challengers or underperformed on tour:
Player ATP M CH M Min M Ratio Florian Mayer 152 45 45 1.180 Mikhail Youzhny 91 38 38 1.169 Aljaz Bedene 144 121 80 1.160 Filippo Volandri 62 101 62 1.158 Robin Haase 194 71 71 1.157 Tobias Kamke 102 144 73 1.155 Adrian Mannarino 234 115 86 1.155 Filip Krajinovic 36 167 36 1.148 Albert Ramos 111 67 62 1.144 Paul Henri Mathieu 147 96 82 1.141 Kenny De Schepper 77 196 77 1.140 Facundo Bagnis 45 197 45 1.136 Pablo Cuevas 127 52 43 1.136 Ivan Dodig 76 48 41 1.135 Santiago Giraldo 146 70 56 1.135 Paolo Lorenzi 204 191 124 1.135 Thomaz Bellucci 162 44 44 1.134 Albert Montanes 113 109 70 1.130 Rogerio Dutra Silva 57 210 57 1.130 Lukas Lacko 122 181 108 1.129
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 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.
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.
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.