Podcast Episode 36: Knights of the Federer Roundtable

Episode 36 is a very special edition of the Tennis Abstract Podcast. I’m joined (in person!) by my co-host Carl Bialik ,of the Thirty Love podcast, along with Federer super-fans and stats junkies Edo Salvati (of settesei.it) and Sulaiman Ijaz.

With this overwhelming amount of analytical enthusiasm gathered around a conference room table in Helsingør, Denmark, we delve into the GOAT debate, trying to take a balanced approach despite our likely Fed bias. We consider the value of weighting slam titles for draw difficulty, the importance of weeks at number one, the surface balance of Masters tournaments … even the doubles prowess of the men in the conversation. We also speculate about the eventual career tallies of Nadal and Djokovic, and what might tilt the debate in a new direction.

This was a really fun episode to record, so I hope you’ll enjoy it as much as we did.

(Note: this week’s episode is about 94 minutes long; in some browsers the audio player may display a different length. Sorry about that!)

Click to listen, subscribe on iTunes, or use our feed to get updates on your favorite podcast software.

Podcast Episode 35: Here Comes Aryna Sabalenka

Episode 35 of the Tennis Abstract Podcast, with Carl Bialik of the Thirty Love podcast, starts with a look at the newest star on the WTA tour, Aryna Sabalenka. The 20-year-old Belarussian won the Wuhan trophy last week, and already looks like one of the strongest hard-court players in the field. We also touch on the rise of Hawkeye line-calling competitor FoxTenn, and the ATP titles claimed a couple of players on the comeback trail, Bernard Tomic and Yoshihito Nishioka.

Thanks for listening!

(Note: this week’s episode is about 59 minutes long; in some browsers the audio player may display a different length. Sorry about that!)

Click to listen, subscribe on iTunes, or use our feed to get updates on your favorite podcast software.

Update: Episode index with links, thanks to FBITennis:

Sabalenka-mania 1:00
Australian Open preview based on WTA Elo 7:58
Is Osaka the next Serena? Is Sabalenka the next Maria? 16:25
Swinging around to swinging volleys 17:55
Performance byes 21:50
Fox “Force” 10 and challenges 25:15 And the payoff
The return of Bernard Tomic 39:45
Disappointing result for Fabio Fognini 46:10
The effect of injury on consistency 49:00
Nishioka’s first title 52:50

How Fast Was the Laver Cup Court?

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Italian translation at settesei.it

Laver Cup has redefined what a tennis event can be, and so far, the new definition seems to involve fast courts. Last year, we saw nine tiebreaks out of eighteen traditional sets, plus a pair of match tiebreaks that went to 11-9. This year’s edition wasn’t quite so extreme, with five tiebreaks out of sixteen traditional sets, but it still featured more tight sets than the typical tour event, in which tiebreaks occur less than once every five frames.

As usual, teasing out surface speed comes with its share of obstacles. Yes, there were lots of tiebreaks and yes, there were plenty of aces, but the player field featured more than its share of big servers. John Isner, Nick Kyrgios, and Roger Federer each contested two matches each year, and in Chicago, Kevin Anderson represented one-quarter of Team World’s singles contribution. No matter what the surface, we’d expect these guys to give us more serve-dominated matches than the tour-wide average.

Let’s turn to the results of my surface speed metric, which compares tournaments by using ace rate, adjusted for the serve and returning tendencies of the players at each event. The table below shows raw ace rate (“Ace%”) and the speed rating (“Speed”) for ten events from the last 52 weeks: The four 2018 grand slams, the fastest and slowest tour stops (Metz and Estoril, respectively), the two Laver Cups, and the two events that rate closest to the Laver Cups (Antalya and New York).

Year  Event            Surface   Ace%  Speed  
2018  Metz             Hard     10.6%   1.57  
2018  Antalya          Grass     9.9%   1.28  
2017  Laver Cup        Hard     17.0%   1.26  
2018  Australian Open  Hard     11.7%   1.17  
2018  Wimbledon        Grass    12.9%   1.16  
2018  Laver Cup        Hard     13.3%   1.09  
2018  New York         Hard     15.7%   1.09  
2018  US Open          Hard     10.8%   1.02  
2018  Roland Garros    Clay      7.7%   0.74  
2018  Estoril          Clay      5.2%   0.55

The speed rating metric ranges from about 0.5 for the slowest surfaces to 1.5 for the fastest, meaning that the stickiest clay results in about half as many aces as the same players would tally on a neutral surface, while the quickest grass or plexipave would give the same guys about half again as many aces as a neutral court would.

Last year’s Laver Cup, despite a whopping 17% ace rate, was barely among the top ten fastest courts out of the 67 tour stops I was able to rate. The surface in Chicago was on the edge of the top third, behind the speedy clay of Quito and considerably slower than the Australian Open.

These conclusions come with the usual share of caveats. First, surface speed is about more than ace rate. I’ve stuck with my ace-based metric because it’s one of the few stats we have for every tour-level event, and because despite its simplicity, it tracks closely with intuition, other forms of measurement, and player comments. Second, we’re not exactly overloaded with observations from either edition of the Laver Cup. Last year’s event featured nine singles matches, and this year there were eight. It’s even worse than that, because third sets are swapped out for match tiebreaks, leaving us even less data. That said, while we don’t have many matches to work with, we know a lot about the players involved, which isn’t as true of, say, Newport or Shenzhen, where a larger number of matches are contested by players who don’t make many appearances on tour.

The two Laver Cup surfaces rate as speedy, but not out of line with other indoor hard courts on the ATP tour. There will be tiebreaks and plenty of aces wherever Isner and Anderson go, no matter what the conditions.

Podcast Episode 34: Laver Cup and the Changing Tennis Landscape

Episode 34 of the Tennis Abstract Podcast, with Carl Bialik of the Thirty Love podcast, breaks down the second edition of the Laver Cup, with a look at the structure of the event, how it generates its appeal from an unusual format, and whether it can survive without Roger Federer. We also check in on the WTA Asian swing, and the ups and downs of top players that have made this season so difficult to predict.

Thanks for listening!

(Note: this week’s episode is about 59 minutes long; in some browsers the audio player may display a different length. Sorry about that!)

Click to listen, subscribe on iTunes, or use our feed to get updates on your favorite podcast software.

Update: Episode index with links, thanks to FBITennis:

Laver Cup 2018 0:50
Sock as the Best Doubles Player 6:52
A Laver (King/Gibson) Cup for Women?  Or Mixed? 15:30
Can Laver Cup survive celebrity retirements? 26:30
Will Laver Cup enthusiasm reach other formats? 36:20
WTA Guangzhou, Seoul and Tokyo 39:25
The two sweet Carolines (Wozniacki and Garcia) 43:55
Are we seeing mediocrity, or stronger parity in the WTA? 47:10
Probability an existing WTA GS winner wins at least 7 of them 51:20
Surprise stat fact about Caroline Garcia 55:05

Tracking European Dominance With Fictional Laver Cups

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Italian translation at settesei.it

No matter what happens this weekend in Chicago, tennis fans can safely say that Europe holds the edge over the rest of the world in the men’s game these days. According to my forecast, Europe has a healthy advantage in the second edition of the Laver Cup, and that’s with Rafael Nadal, the top-ranked singles player (and an excellent doubles player!) skipping the event.

It hasn’t always been this way. Back in 1999, a pair of Americans, Pete Sampras and Andre Agassi, held sway, and an Australian, Patrick Rafter, was also in better form than anyone Europe could have sent out in a proto-Laver Cup. Earlier in the 90s, Sampras and Agassi fought it out at the top of the rankings with even more Americans, such as Jim Courier and Michael Chang. Europeans have almost always been present near the top of the ranking table, but the rest of the world has often held its own.

Imaginary clashes

The Laver Cup format provides a plausible way to measure regions against each other. Comparisons like this are virtually impossible to quantify, because there’s no consensus on what it means for one region to dominate another. Laver Cup gives us a compromise. Singles is more valuable than doubles, but doubles plays a part. Depth–at least to the extent of six guys–is required, but the top three players can have a greater impact on the result.

Using (surface-neutral) singles Elo ratings and year-end ATP doubles rankings, I built six-player Team Europe and Team World rosters for each season going back to 1983. I followed the logic I set out in yesterday’s post about the value of a doubles specialist, so each team consists of the five best available singles players plus the highest-ranked doubles player. If the best doubles option was already on the singles list, I took the next player on the list. I required that each singles player have a minimum of 20 victories that season, so as to filter out the most substantial injury problems (for instance, Andy Murray didn’t make it onto the hypothetical 2018 Europe squad), but otherwise, I assumed everyone was healthy and willing to participate.

As an example, let’s look at the fictional 1983 competition. The World team consisted of John McEnroe, Jimmy Connors, Jimmy Arias, Guillermo Vilas, Jose Luis Clerc, and Peter Fleming, while the Europe squad was made up of Mats Wilander, Ivan Lendl, Jose Higueras, Anders Jarryd, Yannick Noah, and Pavel Slozil. (Lendl didn’t play under the USA flag until 1992, at which time the imaginary Team World, then captained by Rod Laver himself, snapped him up.) These sides made for one of the tightest hypothetical scenarios, with Team World winning 55% of simulations.

World’s fortunes soon turned. They were more heavily favored in the 1984 competition, but fell to underdog status for nine years after that. The graph shows each team’s probability of winning the Laver Cup every year, from 1983 to the present:

Laver Cup forecasts

Keep in mind, the figures for 2017 and 2018 assume that the best available players all show up. Yesterday I gave Europe a 67.6% chance of winning with this week’s actual rosters; add Nadal and move off hard courts to a neutral surface, and Europe’s chances improve to 75%, even with Juan Martin del Potro and Kei Nishikori available for Team World.

The gap between Europe and the rest of the world peaked in 2012, when the Big Four plus David Ferrer all had higher singles Elo ratings than any non-European player. It’s even worse than that: All the Europeans had Elo ratings about 2200, and among potential World team members, only Delpo rated above 2000. Plug those numbers into a Laver Cup forecast, and the hypothetical European side has an 87.5% chance of winning.

The 1987 competition–only three years after the World team would have been favored–looks nearly as lopsided. McEnroe and Connors were still leading the World side, but their levels had dropped while Lendl’s had risen. Add Stefan Edberg and Boris Becker to the mix, and it’s an 86.3% edge for the Europeans. Team World had a nice run in the 1990s, but at no point did their probability of winning a Laver Cup-style competition exceed 75%.

Europe’s power has eroded somewhat since 2012, but it’s difficult to imagine the event tilting fully in World’s favor anytime soon. Four of the five top ATPers under the age of 23 hail from the continent. There’s more hope in the teenage ranks, with Denis Shapovalov and Alex de Minaur (both potential World members) the only under-20s in the top 100, but even there, Europe’s depth wins out. Of the top ten teenagers in the ATP rankings, six are European.

Based on my hypothetical rosters, Team Europe would have been favored in 24 of the last 36 Laver Cups, and they would have won 23 of the 36. The format of the event introduces enough randomness that World is bound to win one of these years. But it will probably take a lot longer before tennis’s current top continent loses its position, even to the combined forces of the rest of the world.

Forecasting the 2018 Laver Cup

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Italian translation at settesei.it

It’s that time of year again: group selfies in suits, dodgy Davis Cup excuses, and a reminder that it takes more than six continents just to equal Europe. That’s right, it’s Laver Cup.

Last year, I worked out a forecast of the event, walking through a variety of ways in which captains Bjorn Borg and John McEnroe could use their rosters and ultimately predicting a 16-8 win for Team Europe. As it happened, both captains intelligently deployed their stars, and the result was 15-9. This year, the competitors are a little different and the home court has moved from Prague to Chicago, but the format remains the same.

Let’s start with a look at the rosters. I’ve included two additional players for reference: Juan Martin del Potro, scheduled to play for Team World, but withdrew; and Pierre Hugues Herbert, the doubles specialist Borg hasn’t realized he needs. Each player is shown alongside his surface-weighted singles Elo rating and surface-weighted doubles “D-Lo” rating:

EUROPE                       Singles Elo  Doubles D-Lo  
Novak Djokovic                      2137          1667  
Roger Federer*                      2097          1700  
Alexander Zverev                    1971          1690  
David Goffin                        1960          1582  
Grigor Dimitrov                     1928          1719  
Kyle Edmund                         1780          1542  
                                                        
WORLD                        Singles Elo  Doubles D-Lo  
Kevin Anderson                      1914          1692  
Nick Kyrgios                        1910          1668  
John Isner                          1887          1800  
Diego Sebastian Schwartzman         1814          1540  
Frances Tiafoe                      1772          1544  
Jack Sock                           1724          1925  
                                                        
ALSO                                                    
Juan Martin Del Potro               2062          1678  
Pierre Hugues Herbert               1691          1890

* Federer has played very little tour-level doubles for a long time. Last year I estimated his D-Lo at 1650; he played rather well last year, so I’ll bump him up to 1700 this time around.

Especially with Delpo on the sidelines, Europe looks to dominate the singles. The doubles leans in World’s favor, largely because Jack Sock is so good, especially in comparison with guys who have focused on singles.

Format review

Let’s do a quick refresher on the format. Laver Cup takes place over three days, each of which has three singles matches and one doubles match. Each player must play singles at least once, and no doubles pairing can repeat itself. Day 1 matches are worth one point each, day 2 matches are worth 2 points each, and day 3 matches are worth 3 points each. If there’s a 12-12 tie at the end of day 3, a single doubles set–in which a previously-used team may compete–will decide it all.

Given that format, the best way for the captains to use their rosters is to stick their three worst singles players on day 1 duty, then use their best three on both day 2 and day 3. For doubles, they should use their best doubles player every day, with the best partner on day 3, next best on day 2, and third best on day 1. As I’ve mentioned, Borg and McEnroe came close to this last year, although Borg didn’t use Rafael Nadal (his best doubles player) in day 3 doubles, and he generally overused Tomas Berdych. Both decisions are understandable, as Nadal may not have been physically able to play every possible match, and Berdych was in front of a Czech crowd.

Now that we know the captains will act in a reasonably savvy way, we can forecast the second edition with a little more confidence than the inaugural one.

The forecast

Nadal’s absence this year will hurt the Europe squad on both singles and doubles. Combined with a small step backward for Federer’s singles game, this year’s Laver Cup figures to be closer than last year. Recall that my forecast a year ago called for a 16-8 Europe victory, and the result was 15-9.

Assuming optimal usage, the 2018 forecast gives Europe a 67.6% chance of winning, with a most likely final score of 14-10. There’s a nearly one-in-ten shot that we’ll see a 12-12 tie, in which the superior doubles capabilities of Team World give them the edge, with a 70.7% probability of winning the tie-breaking set.

Were del Potro not so fragile, this could get even more interesting. Swap out Frances Tiafoe for the Tower of Tandil, and Europe’s chances fall to 56.8%, with a most likely final score of 13-11.

Nothing McEnroe could have done, short of going to medical school a few decades ago, could have put the Argentine on his team this week. But Borg has less of an excuse for failing to maximize the potential of his team. Unlike World, with its world-beating doubles specialist, Europe has a stunning singles roster that rarely takes to the doubles court. As we’ve seen, one doubles player can take the court three times, plus the potential 12-12 tie-breaking set. The specialist would need to play singles only once, on the low-leverage first day.

The obvious choice is Pierre Hugues Herbert, a top-five doubles player with the ability to play respectable singles as well. The Frenchman would be considerably more valuable than Kyle Edmund, who is a better singles player, but not good enough to be of much help to an already loaded side. (I made a similar point last year and illustrated it with Herbert’s partner, Nicolas Mahut. Since then, Herbert has taken the lead over his Mahut in both singles and doubles Elo ratings.)

When we sub in Herbert for Edmund, the simulation spits out the best result yet for Europe. Against the actual World team (that is, no Delpo), the hypothetical Europe squad would have a 74.6% chance of winning, with the likely final score between 14-10 and 15-9. Herbert and a mediocre partner would still be the underdogs in a tie-breaking final set against Sock and John Isner, but the presence of a legitimate doubles threat would narrow the odds to about 58/42.

We won’t get to see either Delpo or Herbert in Chicago this year, but we can expect a slightly more competitive Laver Cup than last year. Add in home court advantage, and the result is even less of a foregone conclusion. It’s no match for last week’s Davis Cup World Group play-offs, but I suspect it’ll make for more compelling viewing this weekend than the final rounds in Metz and St. Petersburg.

The Effect of the US Open Serve Clock

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Italian translation at settesei.it

This year’s US Open was the first grand slam to use a countdown clock before each serve. The time between points was set at 25 seconds, up from the official grand slam time limit of 20 seconds, partly to acknowledge the reality that 20 seconds was never going to happen, and to compromise with the ATP and WTA, whose limits have long been 25 seconds. The clock was tested at several North American events this summer, and I’ve already measured the effect of the clock on match times: once at The Economist’s Game Theory blog, and a second time here at Heavy Topspin.

In those two articles, I found that the serve clock seemed to make the sport slower. Using the limited data at hand–the number of points in each match and its overall time–it turned out that at every event using the clock in 2018, matches were slower by between 0.3 and 2.0 seconds per point. That doesn’t sound like much, but it adds up to a few minutes per match, and this is an innovation that was designed to hurry up play, not hold it back.

The US Open gives us a larger set of matches to study as well as more detailed data to work with. Before we attempt a less ham-handed approach to the problem, let’s see how the matches in New York measured up by the simple standard of seconds per point. Here is that calculation for all main draw singles matches in 2017 (without the clock, and a nominal 20-second time limit) and 2018 (with a 25-second clock):

Draw   2017  2018  
Men    40.0  43.4  
Women  40.7  42.3

Those are some awfully slow matches. Of the other summer events I analyzed, only the 2018 men’s draw in Washington exceeded 42 seconds per point.

However, the excessive heat probably played a part in some of the glacial play. The US Open heat policy certainly slowed down matches, as it allowed for a 10-minute break after the first two sets of women’s matches and the first three sets of men’s matches when the conditions were particularly bad. Those breaks are included in the official match times, so we need to account for them somehow.

Let’s skip some extra work and avoid the heat policy entirely by comparing only straight-set matches from 2017 and 2018, none of which were eligible for a heat break. That still leaves us with half of the original data points:

Draw   2017 Straight-Sets  2018 Straight-Sets  
Men                  39.2                43.4  
Women                39.8                41.3

That was not what I expected. The straight-set matches this year were almost the same speed as the longer ones, even without the possibility of a 10-minute heat break. Maybe players don’t dally as much during straight-set matches because so many of them are lopsided. Or perhaps the mix of players is a bit different. Whatever the reason, this apples-to-apples comparison shows that this year’s apples were quite a bit slower than last year’s.

Again, with better data

The heat policy issue illustrated the problem with using overall match time: It includes set breaks, changeovers, challenges, lets, and every other random type of delay you can imagine. In the long run, all the delays will even out, but in the long run, we’ll all be dead. So far, we’ve seen only a few hundred matches on each tour using the serve clock.

The US Open Slamtracker includes timestamps for the beginning of every point of most singles matches. That’s still not perfect–it doesn’t tell us when points end, for one thing–but with a bit of care and handling, it’s something we can work with. First, I took the Slamtracker data and identified every first-serve point that didn’t end the service game. I filtered out second serves because players use such wildly differing times between first and second serves, and that’s not something addressed by the serve clock. And I filtered out game-ending points because the pause after those points would be longer, involving switching servers and often changing sides.

That left about 16,000 points, a healthy amount of data to work with. From there, I tried to figure out how time was spent actually playing tennis. You know, serving, returning, hitting a bunch of slices, that sort of thing. It turns out that each additional shot adds roughly two seconds to the time between the start of that point and the start of the next. A portion of that might be additional fatigue, resulting in a longer between-points break, but I’ll give the players the benefit of the doubt and assume it’s all time spent playing tennis. I’ll also be generous and say that the first shot–the length of an ace or unreturned serve–is five seconds, to allow for some of the more elaborate service motions.

Put it all together, and we have 16,000 points for which we can estimate the length of the break after the point. If the timestamps for point 1 and point 2 are 35 seconds apart and point 1 was a five-stroke rally–5 seconds for the first shot, 8 seconds for the ensuing shots, for a total of 13 seconds–we can conclude that it took 22 seconds for the server to towel off, choose between various amounts of tennis-ball fuzz, and get ready to serve again.

One last step, again in the spirit of generosity: I eliminated the longest 5% of between-point breaks in each match. Some of those are probably challenges, or let serves, or other disruptions not reflected in the data. I’ve probably filtered out some legimate cases in which the server was really, really slow, but I want to do what I can to give us results that are uncontaminated by too many external issues.

Enough methodology, here are the results. The table shows the number of between-point pauses that were under 20 seconds, under 25 seconds, over 25 seconds, and over 30 seconds. Remember that these times, and the resulting rates, are built on a series of player- and official-friendly assumptions. I’m fairly confident that if we took a stopwatch to 16,000 points and audited the process in person, we would be much more likely to come up with equal or longer times between points than shorter ones.

Time Between Points   2017   2018  Change (%)  
Under 20s            86.5%  78.6%       -9.2%  
Under 25s            97.0%  95.1%       -2.0%  
Over 25s              3.0%   4.9%       63.1%  
Over 30s              0.4%   0.8%       91.0%

The number of excessively long breaks was not very high–less than one point in 20 this year–but the figures skyrocketed in comparison with last year. We could attribute this to the rule change from 20 seconds between points in 2017 to 25 this year, but as we’ve seen, matches with the 20 second limit last year were about as fast (on a match-time per point basis) as those with the 25 second time limit. So I think that’s a non-starter.

The heat, of course, remains a factor, even when heat policy breaks are taken out of the equation. Hotter, more humid conditions will tire players out more quickly, and that will show up in the amount of time they spend recovering between points. Maybe that accounts for the near-doubling of 30-second-or-longer pauses since last year.

Still, there are plenty of questions left to be answered about the serve clock and the way umpires are using it. The rate of 30-second or longer breaks, 0.8%, sounds tiny, but across 16,000 points, it’s over 100 cases. My study was able to include only about half of the points in Slamtracker-covered matches, which itself represents perhaps three-quarters of singles rubbers. Thus, we could be talking about over 300 instances of a player taking more than 30 seconds before serving over the course of the tournament. (And remember, we excluded the longest 5% of between-point pauses.) The number of 25-second-or-longer breaks is even more damning: By the same reasoning, there may have been nearly 2,000 times when a player exceeded the 25-second limit. A few time violations were called, sure, but only a tiny fraction of these probable offenses.

As I noted in my previous article here, a big part of the problem stems from officials waiting until after the crowd has settled down to start the clock. Thus, in an exciting, well-attended match, the time limit effectively becomes 35 seconds or more. This may be what umpires are instructed to do, but it is a sure-fire way to slow matches down. There’s no reason not to start the clock immediately and pause it later for the rare instances when the crowd is making too much noise 25 seconds later.

The simple approach to evaluating the effect of the serve clock, outlined at the beginning of this article, continues to suggest that the serve clock has made matches slower. The more sophisticated tack, made possible by the more detailed data available for most grand slams, supports the same argument, and shows us just how often players are still able to take extra time between points. Let’s hope the serve clock is a work in progress, because changes are necessary if it’s going to contribute to a speedier sport.

Jack Sock, Doubles King Once Again

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Italian translation at settesei.it

A couple of years ago, I wrote an article introducing D-Lo, an Elo-like rating system for doubles, which crowned Jack Sock as the best doubles player on the men’s tour. Sock grabbed the top spot in October 2016 and hung on for about nine months, largely by not playing very much. A couple of first-round losses in Washington and Montreal last summer sent him tumbling, landing at 8th after the US Open and as low as 14th going into this year’s Australian Open.

Despite his preference for singles, Sock has rocketed back into the lead, first pairing with John Isner for the Indian Wells title, and then partnering Mike Bryan (replacing injured brother Bob) to win both Wimbledon and the US Open. With the exception of one week immediately after Indian Wells, Sock sits at the head of the D-Lo table for the first time in more than a year. Here are the current top ten, along with their ratings:

Rank  Player                 D-Lo  
1     Jack Sock              1949  
2     Bob Bryan              1930  
3     Mike Bryan             1917  
4     Pierre Hugues Herbert  1906  
5     Nicolas Mahut          1893  
6     Jamie Murray           1886  
7     Bruno Soares           1883  
8     Oliver Marach          1867  
9     Robert Farah           1863  
10    Nikola Mektic          1863

Yes, that’s the injured Bob Bryan in the second spot. More on that in a moment.

A quick refresher on the D-Lo system: It mostly works like a standard Elo algorithm, in that players gain points for winning matches and lose points for losing them, based on the quality of the opponent and the amount of prior information already baked into their ratings. A big upset earns more points than a victory over an equal, and for players with fewer prior matches, the effect of each match is greater. Thus, Sock got a few more points than Mike did for winning the 12 matches at the last two slams, because we knew relatively less about him before those tournaments.

D-Lo assumes that the quality of each team is equal to the average of the two players. If a team wins, each member of the partnership gains points, with one tweak: If the two players have different ratings, their ratings slightly move toward the average of the two. This is because it’s impossible to know how much each player contributes to a win. The system is designed so that, after a year or so of playing together, the two mens’ ratings will meet in the middle. It’s an imperfect system, but it does a reasonably good job of forecasting results, which means it usually provides a solid representation of each player’s skill level.

Back to the matter at hand: Doubles ratings have been particularly volatile this year, with five different men (Sock, Bob, Pierre Hugues Herbert, Mate Pavic, and Henri Kontinen) holding the #1 spot, and two more (Nicolas Mahut and John Peers) peaking at #2. This parity means that no player has a particularly high rating. Two years ago, Sock’s mark of 1949 would have been good for only fourth (behind himself, Herbert, and Mahut), and several players (the Bryans, Herbert, and Daniel Nestor among them) have peaked with ratings above 2000.

Take a look at how much the rank order has fluctuated since the beginning of 2018:

2018 D-Lo leaders

For clarity’s sake, I’ve left off Oliver Marach (whose rating tracks closely with that of his partner, Pavic, and whose season hasn’t lived up to its early promise) and Peers (ditto, with Kontinen). Herbert has reached the highest level of anyone this season, but a rough second half so far has left him behind the American trio of Jack, Bob, and Mike.

Back to the curious case of Bob Bryan. The Bryan brothers’ title at the Madrid Masters this year gave the twins their highest D-Lo ratings in nearly two years. “Standard” Elo doesn’t penalize players for absence, so Bob’s mark has remained at 1930 ever since. (I’ve added an injury/absence penalty in my singles Elo ratings, but haven’t done so for D-Lo. I suspect there is less of an effect, but still a measureable one, in doubles.) Mike’s rating has slipped because of some bad results apart from the pair of majors, and only Sock has caught up.

If Bob is healthy enough to play this fall, the twins are expected to pair up for the World Tour Finals, once again leaving the best doubles player in the world out of the field. In that case, Sock, down to 157th in the ATP singles race, could end up spending that week playing the new ATP Challenger event in Houston. Without their young compatriot in the way, the Bryans will be back in familiar territory, headed to London as the favorites for another year-end title.

Podcast Episode 33: Farewell, Davis Cup World Group Playoffs

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Episode 33 of the Tennis Abstract Podcast features guest host and frequent Heavy Topspin contributor Peter Wetz, who reports from last weekend’s Austria-Australia World Group playoff tie in Graz, which featured Dominic Thiem and podcast favorite Alex de Minaur, among others. We also try to give an explainer of the new Davis Cup format, but it’s possible we’ll leave you more confused than you were before.

Thanks for listening!

(Note: this week’s episode is about 61 minutes long; in some browsers the audio player may display a different length. Sorry about that!)

Click to listen, subscribe on iTunes, or use our feed to get updates on your favorite podcast software.

Update: Episode index with links, thanks to FBITennis:

What’s it like to go to a Davis Cup tie (Austria example)? 1:15
Gunter Bresnik’s coaching legacy 8:15
Dominic Thiem as clay court specialist 10:25
Mr. Sackmann’s One-Hander, and Results 14:20
One-Handed Backhands on Clay 15:40
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Alex De Minaur 19:20
Other World Group Playoffs Action 28:10
Prediction for 2018 World Cup Final 30:50
New Davis Cup Format/Reforms 36:15
How will the new DC format treat doubles 55:30

The US Open Surface Speed Puzzle

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Italian translation at settesei.it

Almost everyone agrees that the courts were slower at the US Open this year. The players thought so, the media concurred, and the tournament director confirmed that they had slightly changed the physical makeup of the surface in order to slow things down. Even clay-court wizard Dominic Thiem got within two points of the semi-finals, so clearly something changed.

I’m not going to argue with that. But when I set out to measure the change and get a sense of who might have benefited, I kept finding odd results. Almost nothing I tried revealed any clear-cut slowing of the surface, and by some metrics, the courts in Flushing played faster this year. Maybe it was just the heat and humidity–though the numbers don’t make that clear, either.

My usual starting point is my own surface-speed stat, which compares the ace rate at each tournament while controlling for the mix of servers and returners. While the dearth of advanced stats means it is limited to some basic inputs, it usually matches up quite well with our intution and doesn’t differ too much from Court Pace Index (CPI), an infrequently-available metric based on direct physical measurements. Using my algorithm, the US Open surface was 5% faster than the average surface at an ATP event in the last 52 weeks, compared to last year, when it was 4% slower. Compared to courts at the average WTA tournament, New York was 5% slower this year, versus 19% slower in 2017. The slowest tour-level surfaces (for either gender) have about 50% fewer aces than average, and the fastest have about 50% more.

2017 wasn’t just a blip, either in real-life on in my metric. It was similar to 2016, which also rated as considerably slower than this year’s surfaces. We’re left with a discrepancy that may stem from using an algorithm that relies too much on aces: Perhaps players were overwhelmed by the heat and tried more than usual to keep rallies short, or they simply didn’t bother trying to put their racket on first serves as often.

The evidence is clearer that players were more aggressive this year than in 2017. The average rally length, excluding double faults, on courts covered by Slamtracker (179 of the 254 main draw singles matches) fell from 4.28 shots last year to 4.17 this year, a drop of 2.6%. That could be affected by the changing mix of players in the draw (as well as those selected to play on higher-profile courts) so I isolated the 27 players with at least two matches worth of data from both 2017 and 2018. Those 27 saw their rally length drop a tiny bit more, about 3% from last year to this year.

We have the beginnings of an explanation. If players were showing more aggression–perhaps because the heat encouraged them to adopt more first-strike tactics–that could cancel out the effect of a slower surface. We can drill down even further using the Aggression Score (AS) metric, which measures the rate of winners and unforced errors per shot. Across all matches, AS rose from 15.3% in 2017 to 16.1% this year, an increase of 5.7%. Using the 27 players with multiple matches from both years’ tournaments, the difference is more stark, rising by 8.7%.

It’s clear that we saw more aggressive tennis at the 2018 Open than the year before. If we take for granted that the courts played faster, the case is closed: Tactics, probably heat-induced, outweighed surface. But if we approached the problem without knowing what players, media, and tournament officials said, the same numbers would unequivocally point to an even simpler conclusion, that the courts played faster.

If tactics explain our discrepancy, one more place we might look is first serves. Maybe servers took more chances, increasing their ace rate at the expense of first-serve percentage. But the data doesn’t back us up: The overall first-serve percentage in Slamtracker matches fell by a mere 0.07%. Using year-to-year comparisons for our set of 27 players, the difference was larger, but still a measly 0.3%. If tactics are the answer, it must be on the return of serve, not the serve itself.

This is where the trail runs cold. Return tactics are tougher to quantify than serving strategy, and there’s a limit to how much we can do with the available data. We can tally return winners and induced forced errors (IFEs), points in which the returner ended things with a strong reply. If returners allowed more aces, it should be because they took a more aggressive approach, trading fewer opportunities for better odds of winning when they did make contact. Instead, the record shows that return winners and IFEs fell a whopping 7% from last year to this year. That number supports the theory of a slower surface, and it meets expectations for those players who adopted very conservative return positions, such as Rafael Nadal, whose return winner/IFE rate went down by 3%, and Thiem, whose rate decreased by 7%. But a slower surface and a lower return winner/IFE rate should add up to fewer aces, not more.

Compared to where we started, we have a lot more data but not many more answers. Some signs point to a faster surface, others to a slower; some indicate more aggressive tactics, others more conservative ones. regardless of what we know about the physical makeup of the courts, there are many factors that influence what we refer to as “surface speed.” The hot, humid conditions in Flushing this year surely help complicate things–perhaps a study that took into account the heat index for each individual match would shed more light on these questions. We could also be seeing players adapt to the conditions–whether the heat or the slower surface–in different ways. Everyone may agree about how the courts played this year, but it’s much more difficult to pin down exactly what that means.