Elena Rybakina and the Value of Average

Also today: Ugo Humbert in the (Elo) top ten; South American Davis Cup hard courts

Elena Rybakina at the 2023 US Open. Credit: Hameltion

Never underestimate average. Establishing oneself on the top level of the pro tennis circuit is extraordinarily difficult; proving that any particular skill is average among one’s tour-level peers is even harder. Most players are better than the norm in some categories, worse in others. Anyone who can beat the middle of the pack in every department is virtually guaranteed to be a superstar.

Average is Elena Rybakina’s secret weapon. You probably didn’t know she needed one, because she has a very effective, very evident non-secret weapon: an unreadable bullet of a first serve. In the last year, over 43% of her first serves have gone unreturned. No one else on tour comes within three percentage points of that, and only five other women top 35%. On a good day, the serve can put a match out of reach nearly on its own. When she faced Aryna Sabalenka in Beijing last fall, 65% of her first serves didn’t come back. Most women barely manage to win that many first serve points, let alone decide them with one stroke.

I’ll come back to the serve in a moment, because it is so remarkable, and it would be strange to talk about Rybakina without discussing it. But what makes her a contender every week–not to mention a champion in Abu Dhabi yesterday–is the way that the rest of her game doesn’t hold her back. Among the other women who end points with more than 35% of their first serves, you’ll find a long list of weaknesses. Qinwen Zheng doesn’t put nearly enough of them in the box. Donna Vekic and Caroline Garcia struggle to break serve. Liudmila Samsonova doesn’t break much, either, and her mistakes come in excruciating, match-endangering bunches.

Lopsided player profiles make sense. Only a few people have the combination of natural gifts and discipline to develop a dominant serve. Tennis skills are correlated, but not perfectly so. Someone who serves like Vekic can often learn good-enough groundstrokes and secondary shots. But players with one standout skill are unlikely to be solid across the board. Just because someone is top ten in the world in one category, why would we expect them to rank in the top 100 by a different measure?

Rybakina has reached the top–or close, anyway–by coupling a world-class serve with a set of skills that lacks defects. (You can nitpick her footwork or technique, but none of that holds her back when it comes to winning enough points.) After we review the devastation wrought by her serve, we’ll see just how average she otherwise is, and why that wins her so many matches.

First serves first

I’ve already given you the headline number: Since this time last year, 43.4% of Rybakina’s first serves haven’t come back. That’s one percentage point better than Serena Williams’s career rate. Serena’s numbers are based on matches logged by the Match Charting Project, a non-random sample skewed toward high-profile contests against strong opponents, so I’m not ready to say outright that Rybakina is serving better than Serena. But I’m not not saying that–we’re within the margin of error.

Some back-of-the-envelope math shows what kind of gains a player can reap from the best first serve in the game. Rybakina makes about 60% of her first serves–lower than average, but probably worth the trade-off. (And improving–we’ll talk about that in a bit.) When the serve does come back, she wins about half of points, roughly typical for tour players. All told, 43% of her serve points are first-serve points won. Tack on about half of her second serve points–she wins 48% of those, better than average but not by a wide margin–and we end up with her win rate of 62.5% of serve points–fourth-best on tour.

Put another way: We combine one world-class number (unreturned first serves) with a below-average figure (first serves in), one average number (success rate when the serve come back), and one more that was slightly better than average (second-serve points won). The result is an overall success rate that trails only those of Iga Swiatek, Sabalenka, and Garcia. That, in case you ever doubted the value of an untouchable first serve, is the impact of one very good number.

The key to Rybakina’s first serve–apart from blinding speed–is its unreadability. She must lead the tour in fewest returner steps per ace, a stat I dreamed up while watching the Abu Dhabi semi-final on Saturday. Samsonova seemed to stand bolted to the ground, watching one serve after another dart past her. After one business-as-usual ace out wide, Samsonova even offered a little racket-clap of appreciation, an unusual gesture for such a routine occurrence.

In addition to the deceptiveness of a nearly identical toss and service motion, Rybakina is effective in every direction. There’s no way for an opponent to cheat to one side, hoping to get an edge on a delivery in that corner of the box. Here are Elena’s rates of unreturned first serves and total points won in each corner of the two service boxes:

Direction   Unret%  Won%  
Deuce-Wide     36%   69%  
Deuce-T        45%   75%  
Ad-T           37%   70%  
Ad-Wide        42%   74%

The average player ends points with their first serve between 20% and 25% of the time and wins 60% of their first serve points. Rybakina obliterates those numbers in every direction. If there’s a strategy to be exploited, it’s that returners ought to lean toward their forehand, because if the serve comes to their backhand, they don’t have a chance anyway.

The scariest thing for the rest of the tour is that the 24-year-old’s biggest weapon may be getting even bigger. Her 43.4% rate of unreturned first serves in the last 52 weeks compares favorably to a career clip of 38.2%. Against Samsonova on Saturday, over 41% of all serves didn’t come back, better than Rybakina managed in any of their four previous meetings.

She may be getting savvier, too. One of the dangers of a game built around a single weapon is that certain players might be able to neutralize it. Daria Kasatkina, Elena’s opponent in yesterday’s final, is just such an opponent, a resourceful defender and a first-class mover. When the two women played a three-and-a-half-hour epic in Montreal last summer, Kasatkina put three-quarters of first serves back in play, something that few women on tour could manage and one of the main reasons the match stretched so long. Rybakina survived, but she was broken ten times.

Yesterday, Kasatkina was as pesky as ever, getting almost as many balls back as she did in Montreal. But Rybakina took fewer chances with her first strike, perhaps as much to counter the wind as to adjust for her opponent. Whatever the reason, Elena made three-quarters of her first serves. She had never landed more than 61% against Kasatkina.

The Abu Dhabi final was an exaggerated example of a longer-term trend. Somehow, Rybakina is making way more first serves than ever before, sacrificing no aces and only a fraction of first-serve points won. The overall results speak for themselves:

Year    1stIn%  1st W%   Ace%   SPW%  
2024     66.8%   70.9%  10.3%  64.8%  
2023     56.8%   73.6%  10.5%  62.8%  
Career   57.8%   71.1%   8.4%  62.0%

It’s not a perfect comparison, because the entire 2024 season so far has been on hard courts. Her season stats will probably come down. But a ten-percentage-point increase in first serves in? Nobody does that. Kasatkina won just five games yesterday, and she won’t be the last opponent to discover that whatever edge she once had against Rybakina is gone.

Average ballast

As Ivo Karlovic can tell you, the best service in the world can take you only so far. Some first serves will go astray, some serves will come back, and then there’s the whole return game to contend with. Women’s tennis rarely features characters quite as one-sided as Ivo, but Vekic and Garcia illustrate the point, struggling to string together victories because their serves alone are not enough.

Here’s a quick overview of how the rest of Rybakina’s game stacks up against the average top-50 player over the last 52 weeks:

Stat     Top-50  Elena  
2nd W%    46.7%  48.4%  
DF%        5.2%   3.9%  
RPW       44.4%  44.2%  
Break%    35.5%  36.9%  
BPConv%   46.6%  43.5%

She’s somewhat better than average behind her second serve, as you’d expect from someone with such a dominant first serve. It’s aided by fewer double faults than the norm. On return, we have two separate stories. Taking all return points as a whole, Rybakina is almost exactly average, matching the likes of Barbora Krejcikova and Marta Kostyuk. The only category where she trails the majority of the pack is in break point conversions–and by extension, breaks of serve.

The discrepancy between Rybakina’s results on break points and on return points in general may just be a temporary blip. Most players win more break points than their typical return performance, because break points are more likely to arise against weaker servers. That hasn’t been the case for Elena in the last 52 weeks, and it wasn’t in 2022, either, when she won 41.9% of return points that year but converted only 40.5% of break opportunities.

Match Charting Project data indicates that she is slightly more effective returning in the deuce court than the ad court; since most break points are in the ad court, that could explain a bit of the gap. Charting data also suggests she is a bit more conservative on break point, scoring fewer winners and forced errors than her normal rate, though not fewer than the typical tour player. It may be that Rybakina will always modestly underperform on break opportunities, but it would be unusual for a player to sustain such a large gap.

In any case, she hasn’t struggled in that department in 2024. In 13 matches, she has won 46.9% of return points overall and 47.3% of break points. It’s dangerous to extrapolate too much from a small sample, especially on her preferred surface, but it may be that Rybakina’s single weak point is already back to the top-50 norm of her overall return performance.

The value of all this average is this: What Rybakina takes with her first serve, she doesn’t give back with the rest of her game. We’ve already seen how a standout rate of unreturned first serves–plus a bunch of average-level support from her second serve and ground game–translates into elite overall results on serve. A tour-average return game generates about four breaks per match. Elena has been closer to 3.5, but either way, that’s more than enough when coupled with such a steady performance on the other side of the ball.

I can’t help but think of Rybakina’s “other” skills as analogous to the supporting cast in team sports. Her first serve is an all-star quarterback or big-hitting shortstop; the rest of her game is equivalent to the roster around them. In baseball, a league-average player is worth eight figures a year. Though Elena’s return, for instance, doesn’t cash in to quite the same degree, it is critical in the same way. A superstar baseball player can easily end up on a losing team, just as Caroline Garcia can drop out of the top 50 despite her serve. Rybakina is at no risk of that.

A final striking attribute of Rybakina’s game is that her array of tour-average skills can neutralize such a range of opponents. Her weekend in Abu Dhabi was a perfect illustration, as she overcame Samsonova and Kasatkina, two very different opponents, each of whom has bedeviled her in the past. Elena is more aggressive than the average player, but she is considerably more careful than Samsonova; her Rally Aggression Score is equivalent to Swiatek’s. She was able to take advantage of the Russian’s rough patches without losing her own rhythm or coughing up too many errors of her own.

Against Kasatkina, she posted the most unexpected “average” stat of all. In a matchup of power against defense, defense should improve its odds as the rallies get longer. On Sunday, the two women played 15 points of ten strokes or more, and Rybakina won 8 of them. In her career, Elena has won 52% of those points–probably more by wearing down opponents with down-the-middle howitzers than any kind of clever point construction, but effective regardless of the means.

Rybakina won’t beat you at your own game. But she’ll play it pretty well. Combined with the best first serve in women’s tennis, drawing even on the rest is a near-guarantee of victory. Abu Dhabi marked her seventh tour-level title, and it will be far from her last.

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Ugo Humbert, Elo top-tenner

You probably don’t think of Ugo Humbert as a top-ten player, if you think of him at all. The 25-year-old left-hander cracked the ATP top 20 only a few months ago, and his title last week in Marseille gave him a modest boost to #18.

Elo is much more positive about the Frenchman. Today’s new Elo rankings place him 9th overall, just behind Hubert Hurkacz, the man he defeated to reach the Marseille final. Humbert has always been dangerous against the best, with a 22-25 career record facing the top 20, and a 10-12 mark against the top ten.

Humbert’s place in the Elo top ten might feel like a fluke; there’s a tightly-packed group between Hurkacz at #8 and Holger Rune at #13, and an early loss in Rotterdam could knock the Frenchman back out of the club. But historically, if a player reaches the Elo top ten, a spot in the official ATP top ten is likely in the offing.

I wrote about this relationship back in 2018, after Daniil Medvedev won in Tokyo. As his ATP ranking rose to #22, he leapt to #8 on the Elo list. In retrospect, it’s odd to think that “Daniil Medvedev will one day crack the top ten” was a big call, and it wasn’t that far-fetched: Plenty of people would’ve concurred with Elo on that one. He made it, of course, officially joining the elite the following July.

In that post, I called Elo a “leading indicator,” since most players reach the Elo top ten before the ATP computer renders the same judgment. This makes sense: Elo attempts to measure a player’s level right now, while the ATP formula generates an average of performances over the last 52 weeks. That’s a better estimate of how the player was doing six months ago. Indeed, for those players who cracked both top tens, Elo got there, on average, 32 weeks sooner. In Medvedev’s case, it was 40 weeks.

Most importantly for Humbert, Elo is almost always right. In October 2018, I identified just 19 players who had reached the Elo top ten but not the ATP top ten. Three of those–Medvedev, Stefanos Tsitsipas, and Roberto Bautista Agut–have since taken themselves off the list. One more has come along in the meantime: Sebastian Korda joined the Elo top ten in early 2023, but his ATP points total has yet to merit the same ranking.

Most of the Elo-but-not-ATP top-tenners had very brief stays among the Elo elite: Robby Ginepri qualified for just one week. The only exception is Nick Kyrgios, who spent more than a year in the Elo top ten, thanks to his handful of victories over the best players in the game. His upsets earned him plenty of notoriety, but his inability to consistently beat the rest of the field kept his points total deflated.

Humbert, in his much quieter way, fits the same profile. His serve means that he can keep things close against higher-ranked players, but he has struggled to string together enough routine wins to earn more of those chances. (Injuries haven’t helped.) Still, the odds are in his favor. In 32 weeks–give or take a lot of weeks–he could find himself in the ATP top ten.

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Surfaces in South American Davis Cup

It dawned on me about halfway through the deciding rubber of the Chile-Peru Davis Cup qualifying tie: They were playing on a hard court! In South America! Against another South American side!

It made sense for Chile, with big hitters Nicolas Jarry and Alejandro Tabilo leading the team, and they did indeed vanquish the Peruvian visitors. But South America is known as a land of clay courts, the home of the “Golden Swing.” It seemed weird that an all-South American tie would be played on anything else.

As it turns out, it isn’t that unusual. Since the late 1950s, I found 252 Davis Cup ties between South American sides. I don’t have surface for 37 of them, almost all from the 1970s. Presumably most of those were on clay, but since that’s the question I’m trying to answer, I’m not going to assume either way.

That leaves us with 215 known-surface ties, from 1961 to the Chile-Peru meeting last weekend. (I’m excluding the matchup between Argentina and Chile at the 2019 Davis Cup Finals, since neither side had any say in the surface.) To my surprise, 37 of those ties–about one in six–took place on something other than clay. That’s mostly hard courts, but five of them were played on indoor carpet as well.

The country most likely to bust the stereotype has been Venezuela, which preferred hard courts as early as the 1960s. Ecuador also opted to skip clay with some frequency; it accounted for the first appearance of carpet in an all-South American tie back in 1979.

Chile has generally stuck with clay, but not always. The last time they hosted a South American side on another surface was 2000, when they faced Argentina on an indoor hard court. The surface probably wouldn’t have mattered, as Marcelo Rios and Nicolas Massu were heavy favorites against a much weaker Argentinian side. Though they won, the home crowd was so disruptive that the visitors pulled out without playing the doubles. Chile was disqualified from the next round and barred from hosting again until 2002.

The crowd last weekend was typically rowdy, but Jarry and Tabilo advanced without controversy. For some South American sides, hosting on hard courts may finally become the rule, not the exception.

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What Is Going Wrong For Novak Djokovic?

Also: Arina Rodionova (probably) in the top 100

Novak Djokovic practicing at the 2023 US Open. Credit: Amaury Laporte

Fifteen break points. A week has passed, a new champion has been crowned, and I still can’t stop thinking about it. In the first two sets of his Australian Open quarter-final match against Taylor Fritz, Novak Djokovic failed to convert fifteen straight break points.

It’s so far out of character as to defy belief. Djokovic has converted more than 40% of his break chances in the past year, even counting the 4-for-21 showing in the entire Fritz match. The American, one of the better servers on tour, typically saves only two-thirds of the break points he faces. The chances that Novak would come up short 15 times in a row are about one in seven million.

Even stranger, it wasn’t because Fritz served so well. He missed his first serve on 7 of the 15 break points. He hit two aces and another four didn’t come back, but that leaves nine rallies when–under pressure, in Australia–Taylor Fritz beat Novak Djokovic. Five of those lasted at least seven strokes, including a 25-shot gutbuster at 4-3 in the second set that was followed, two points later, by yet another Fritz winner on the 17th shot. All credit to the American, who walked a tightrope of down-the-line backhands and refused to give in to an opponent who, even in the first two sets, was outplaying him. But clearly this wasn’t a matter of Fritz intimidating or otherwise imposing himself on Novak.

There’s no shortage of explanations. Djokovic is recovering from a wrist injury that hampered him in his United Cup loss to Alex de Minaur. He apparently had the flu going into the Melbourne semi against Jannik Sinner. The whole Australian adventure might be nothing more than a health-marred aberration; in this interpretation, none of Jiri Lehecka, Dino Prizmic, Alexei Popyrin, or even Fritz would otherwise have taken a set from the all-time great.

But… the man is 36 years old. If other tennis players his age are any guide, he may never be fully healthy again. He will continue to get slower, if only marginally so. He personally raised the physical demands of the sport, and finally, a younger generation has accepted the challenge. Djokovic has defied the odds to stay on top for as long as he has, but eventually he will fade, even if that means only a gentle tumble out of the top three. After a month like this, we have to ask, is it the beginning of the end?

Rally intolerance

The two marathon break points that Fritz saved were not exceptions. 64 of the 269 points in the quarter-final reached a seventh shot, and the American won more than half of them. Even among double-digit rallies, the results were roughly even.

Here’s another data point: Djokovic fought out 53 points in his first-rounder against Prizmic that reached ten shots or more. The 18-year-old Croatian won 30 of them. Yeah, Prizmic is a rising star with mountains of potential, but he’s also ranked 169th in the world. This is not the Novak we’ve learned to expect: Even after retooling his game around a bigger serve and shorter points, he remained unshakeable from the baseline, his famous flexibility keeping him in position to put one more ball back in play.

Down Under, though, those skills went missing. Based on 278 charted matches since the start of 2015, the following table shows the percentage of points each year that he takes to seven shots or more, and his success rate in those rallies:

Year  7+ Freq  7+ Win%  
2015    23.3%    54.9%  
2016    26.7%    53.1%  
2017    29.1%    53.3%  
2018    24.4%    52.6%  
2019    25.0%    55.1%  
2020    26.0%    54.3%  
2021    23.8%    53.6%  
2022    23.2%    54.7%  
2023    23.4%    54.1%  
2024    26.0%    49.8%

By the standards of tennis’s small margins, that’s what it looks like to fall off a cliff. The situation probably isn’t quite so bad: The sample from 2024 is limited to only the matches against Lehecka, de Minaur, Prizmic, Fritz, and Sinner. On the other hand, matches charted in previous years also skew in favor of novelty, so upsets, close matches, and elite opponents are overrepresented there too.

It is especially unusual for Djokovic to see such a decline on hard courts. Over the last decade, he has gone through spells when he loses more long rallies than he wins. But they typically come on clay. Carlos Alcaraz shut him down in last year’s Wimbledon final as well, winning 57% of points that reached the seventh shot and 63% of those with ten or more strokes. The only period when hard-court Novak consistently failed to win this category was late 2021, when Medvedev beat him for the US Open title (and then outscored him in long rallies in Paris), and Alexander Zverev won 62% of the seven-plusses (and 70% of ten-plusses!) to knock him out of the Tour Finals.

Protracted rallies are a young man’s game, and Djokovic’s results are starting to show it. Before dissecting Alcaraz in Turin last November, Novak had never won more than half of seven-plusses against Carlitos. He has barely held on against Sinner, winning 43% of those points in their Tour Finals round-robin match and 51% at the Davis Cup Finals. In 13 meetings since 2019, Medvedev has won more of these long rallies than Djokovic has. Zverev, too, has edged him out in this category since the end of 2018.

Against the rest of the pack, Djokovic manages just fine. He dominates seven-plusses against Casper Ruud and Stefanos Tsitsipas, for instance. But it’s one of the few chinks in his armor against the best, and if January represents anything more than the temporary struggles of an ailing star, more players are figuring out how to take advantage.

Avoiding danger

For players who lose a disproportionate number of long points, the best solution is to shorten them. Djokovic may never have thought in exactly those terms, but perhaps with an eye toward energy conservation, he has done exactly that.

Especially from 2017 to 2022, Novak drastically reduced the number of points that reached the seven-shot threshold:

In 2017, 29% of his points went that long; in 2022 and 2023, barely 23% did. It remains to be seen whether January 2024 is more than a blip. In his up-and-down month, Novak remained able to control his service points, but he was less successful avoiding the grind on return. As we’ve seen, that’s dangerous territory: Djokovic won a healthy majority of the short points against Fritz but was less successful in the long ones, especially following the American’s own serve.

Much rests on the direction of these trends. If the players Djokovic has faced so far this year can prevent him from finishing points early, how will he handle Medvedev or Zverev?. If Novak can’t reliably outlast the likes of Fritz and Prizmic, what are his chances against Alcaraz?

Djokovic is well-positioned to hold on to his number one ranking until the French Open, when he’ll be 37 years old. By then, presumably, he’ll be clear of the ailments that held him back in Australia. Still, holding off the combination of Sinner, Alcaraz, Medvedev, Zverev, and Father Time will be increasingly difficult. The 24-time major champion will need to redouble the tactical effort to keep points short and somehow recover the magic that once made him so implacable in the longest rallies. Age is just a number, but few metrics are so ruthless in determining an athlete’s fate.

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Arina Rodionova on the cusp of the top 100

In December, Australian veteran Arina Rodionova celebrated her 34th birthday. Now she’s competing at the tour-level event in Hua Hin this week, sporting a new career-best ranking of 101. With a first-round upset win over sixth-seed Yue Yuan, she’s up to 99th in the live rankings. Her exact position next Monday is still to be determined–a few other women could spoil the party with deep runs, or she could climb higher with more victories of her own–but a top-100 debut is likely.

Rodionova, assuming she makes it, will be the oldest woman ever* to crack the top 100 for the first time. The record is held by Tzipi Oblizer, who was two months short of her own 34th birthday when she reached the ranking milestone in 2007. Rodionova will be just the fifth player to join the top-100 club after turning 30.

* I say “ever” with some caution: I don’t have weekly rankings before the mid-80s, so I checked back to 1987. Before then, the tour skewed even younger, so I doubt there were 30-somethings breaking into the top 100. But it’s possible.

Here is the list of oldest top-100 debuts since 1987:

Player                    Milestone  Age at debut  
Arina Rodionova*         2024-02-05          34.1  
Tzipi Obziler            2007-02-19          33.8  
Adriana Villagran Reami  1988-08-01          32.0 
Emina Bektas             2023-11-06          30.6  
Nuria Parrizas Diaz      2021-08-16          30.1  
Mihaela Buzarnescu       2017-10-16          29.5  
Julie Ditty              2007-11-05          28.8  
Eva Bes Ostariz          2001-07-16          28.5  
Maryna Zanevska          2021-11-01          28.2  
Ysaline Bonaventure      2022-10-31          28.2  
Mashona Washington       2004-07-19          28.1  
Laura Pigossi            2022-08-29          28.1  
Maureen Drake            1999-02-01          27.9  
Hana Sromova             2005-11-07          27.6  
Laura Siegemund          2015-09-14          27.5

* pending!

I extended the list to 16 places in order to include Laura Siegemund. She and Buzarnescu are the only two women to crack the top 100 after their 27th birthdays yet still ascend to the top 30. The odds are against Rodionova doing the same–the average peak of the players on the list is 67, and the majority of them achieved the milestone a half-decade earlier–but you never know.

A triumph of scheduling

Rodionova has truly sweated her way to the top. She played 105 matches last year, winning 78 of them, assembling a haul of seven titles and another three finals. When I highlighted the exploits of Emma Navarro a couple of weeks ago, I couldn’t help but draw attention to the Australian, who is one of only two women to win more matches than Navarro since the beginning of last year. Iga Swiatek is the other.

Most of the veteran’s recent triumphs–44 match wins and five of her seven 2023 titles–have come at the ITF W25 level. She didn’t beat a single top-200 player in those events, and she faced only five of them. In her long slog through the tennis world last year, Rodionova played just one match against a top-100 opponent, and that was a loss to 91st-ranked Dalma Galfi.

The point is, the Aussie earned her ranking with quantity, not quality. No shame in that: The WTA made the rules, and the Australian not only chose a schedule to maximize her chances of climbing the ranking table, she executed. Kudos to her.

What her ranking does not mean, however, is that she is one of the 100 best players in the world. Elo is a more reliable judge of that, and going into this week, the algorithm ranks her 207th. (She peaked in the 140s, back in 2017.) You can hack the WTA rankings with a punishing slate of ITFs, but it’s much harder to cheat Elo.

Here are the players in the official top 150 who Elo considers to be most overrated:

Player             Elo Rank  WTA Rank  Ratio  
Caroline Dolehide       124        41    3.0  
Peyton Stearns          145        54    2.7  
Arantxa Rus             103        43    2.4  
Tatjana Maria            94        44    2.1  
Arina Rodionova         207       101    2.0  
Laura Pigossi           221       114    1.9  
Elina Avanesyan         120        62    1.9  
Varvara Gracheva         89        46    1.9  
Nadia Podoroska         127        67    1.9  
Lucia Bronzetti         109        58    1.9  
Dayana Yastremska        54        29    1.9

Once you climb into the top 100, savvy scheduling is increasingly impractical. Instead, this kind of gap comes from a deep run or two combined with many other unimpressive losses. Caroline Dolehide reached the final in Guadalajara followed by a quarter-final exit at a WTA 125, then lost three of five matches in Australia. Arantxa Rus won the title in Hamburg and reached a W100 semi-final, then lost five of six. The WTA formula lets you keep all the points from a big win for 52 weeks; Elo takes them away if you don’t keep demonstrating that you belong at the new level.

The sub-200 Elo rank suggests that Rodionova will have a hard time sustaining her place on the WTA list once the ranking points from her W25 titles start to come off the board. Until then, she can continue to pad her total and–fingers crossed–enjoy the hard-earned reward of a double-digit ranking.

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Anna Kalinskaya At Her Peak

Also today: Upsets, (partly) explained; January 23, 1924

Anna Kalinskaya in the 2020 Fed Cup qualifying round. Credit: Nuță Lucian

Should we have seen this coming? Of all the surprises in the top half of the 2024 Australian Open women’s draw, Anna Kalinskaya’s run to the quarter-finals stands as one of the biggest. The 25-year-old was ranked 75th entering the tournament, and she had never reached the third round of a major in 13 previous main-draw attempts.

Had we looked closely before the tournament, we wouldn’t have found a title contender, exactly, but we would have identified Kalinskaya as about as dangerous as a 75th-ranked player could possibly be. She finished 2023 on a 9-1 run, reaching the final at the WTA 125 in Tampico, then winning the title at the Midland 125, where she knocked out the up-and-coming Alycia Parks in the semi-finals. 2024 started well, too: The Russian upset top-tenner Barbora Krejcikova in Adelaide, then almost knocked out Daria Kasatkina in a two hour, 51-minute match two days later.

The only reason her official ranking is so low is that she missed nearly four months last summer to a leg injury that she picked up in the third round in Rome. Her two match wins at the Foro Italico pushed her up to 53rd in the world, just short of her career-best 51st, set in 2022. The Elo algorithm, which measures the quality of her wins rather than the number of tournaments she was healthy enough to play, reflects both her pre-injury successes and the more recent hot streak. Kalinskaya came to Melbourne as the 31st-ranked woman on the Elo list.

These alternative rankings put a different spin on her path through the Australian Open draw so far. Here are the results from her first four rounds, in which she appeared to be the underdog three times:

Don’t be fooled!

Elo has some adjustments to make:

Round  Opponent  Elo Rk  Elo vRk  
R16    Paolini       31       37  
R32    Stephens      31       50  
R64    Rus           31      107  
R128   Volynets      31      139

Kalinskaya was hardly an early favorite–Stephens did her the favor of taking out Kasatkina, and Anna Blinkova (who lost to Paolini) eliminated the third-seeded Elena Rybakina. But given how the draw worked out, seeing the Russian’s name in the quarter-finals wasn’t so unlikely after all.

More luck

Kalinskaya has a dangerous forehand and a solid backhand, but she isn’t an aggressive player by the standards of today’s circuit. Her 14 matches logged by the Match Charting Project average 4.2 strokes per point, and that skews low because it includes three meetings with Aryna Sabalenka. Yesterday’s fourth-round match against Paolini took 5.3 strokes per point, and the third-rounder with Stephens was similar.

By Aggression Score, the 25-year-old rates modestly below average, at -17 in rallies and -15 on returns. While she doesn’t have any weaknesses that prevent her from ending points earlier, she’s more comfortable letting the rally develop. When Paolini played along, the results were remarkable: 32 points reached seven shots or more yesterday, and Kalinskaya didn’t end any of them with an unforced error.

The downside of such a game style is that a lot of opponents won’t be so cooperative. Last fall, the Russian lost back-to-back-to-back matches against Ekaterina Alexandrova, Viktoria Hruncakova, and Ashlyn Krueger, three women who opt for big swings and short points. By contrast, consider the Rally Aggression Scores of the quartet Kalinskaya has faced in Melbourne:

Round  Opponent  AggScore  
R16    Paolini         -5  
R32    Stephens       -16  
R64    Rus            -59  
R128   Volynets       -38

Paolini and Stephens have roughly similar profiles to Kalinskaya’s own; Rus and Volynets are even more conservative.

This isn’t just a convenient narrative: Kalinskaya really is better against more passive players. She has played 118 career tour-level matches against women with at least 20 matches in the charting database. Sort them by Rally Aggression Score and separate them into four equal bins, and the Russian’s preferences become clear:

AggScore Range  Match Win%  
57 to 175            35.7%  
0 to 56              46.4%  
-27 to -1            50.0%  
-137 to -27          59.4%

If the whole tour were as patient as she is, the Russian would already be a household name.

Alas, it’s rare to draw four straight players as conservative as the bunch Kalinskaya has faced in Melbourne. And having reached the quarter-finals, her luck has run out. Her next opponent is Qinwen Zheng, who has a career Aggression Score of 27 and upped that number in 2023. It could be worse–fellow quarter-finalists Sabalenka and Dayana Yastremska are triple-digit aggressors–but it is a different sort of challenge than she has faced at the tournament so far.

To win tomorrow, Kalinskaya will need to play as well as she has for the last few months, only a couple of shots earlier in the rally. Otherwise, Zheng will end points on her own terms, and thousands of potential new fans will be convinced that Kalinskaya really is just the 75th best player in the world.

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Why are upsets on the rise?

Only four seeds, and two of the top eight, survived to the Australian Open women’s quarter-finals. Many of the top seeds lost early. This feels like a trend, and it isn’t new.

One plausible explanation is that the field keeps getting stronger. Top-level players now develop all over the world, and coaching and training techniques continue to improve. There are few easy, guaranteed matches, even if Iga Swiatek and Aryna Sabalenka usually(!) make it look that way. I believe this is part of the story.

Another component, I suspect, is the shift in playing styles. I noted a couple of weeks ago when writing about Angelique Kerber is that WTA rally lengths have steadily declined in the last decade. In 2013, the typical point lasted 4.7 strokes; it’s now around 4.3. Shorter points are caused by more risk-taking. Risks don’t always work out, full-power shots go astray, and the better-on-paper player doesn’t always win.

In 2019, I tested a similar theory about men’s results. I split players in four quartiles based on Aggression Score and tallied the upset rate for every pair of player types. When two very aggressive players met, nearly 39% of matches resulted in upsets, compared to 25% when two very passive players met. The true gap isn’t quite that big: given the specific players involved, there should have been a few more upsets among the very aggressive group. But even after adjusting for that, it remained a substantial gap.

It stands to reason that the story would be the same for women. Instead of Aggression Score, I used average rally length. I doubt there’s much difference. I didn’t intend to change gears, I just got halfway through the project before checking what I did the first time.

The most aggressive quartile (1, in the table below) are players who average 3.6 shots per rally or less. The next group (2) ranges from 3.7 to 4.0, then (3) from 4.1 to 4.5, and finally (4) 4.6 strokes and up. The following table shows the frequency of upsets (Upset%) and how the upset rate compares to expectations (U/Exp) for each pair of groups:

Q1  Q2  Upset%  U/Exp  
1   1    40.7%   1.07  
2   1    36.2%   0.99  
2   2    35.7%   0.99  
3   1    35.1%   0.93  
3   2    35.5%   0.97  
3   3    40.9%   1.07  
4   1    37.6%   1.03  
4   2    36.6%   1.02  
4   3    34.6%   0.95  
4   4    34.7%   0.97

(If you look back to the 2019 study, you’ll notice that I did almost everything “backwards” this time — swapping 1 for 4 as the label for the most aggressive group, and calculating results as favorite winning percentages instead of upsets. Sorry about that.)

Matches between very aggressive players do, in fact, result in more upsets than expected. It’s not an overwhelming result, partly because it’s only 7% more than expected, and partly because matches between third-quartile players–those with average rally lengths between 4.1 and 4.5–are just as unexpectedly unpredictable.

I don’t know what to make of the latter finding. I can’t think of any reasonable cause for that other than chance, which casts some doubt on the top-line result as well.

If the upset rate for matches between very aggressive players is a persistent effect, it would give us more upsets on tour today than we saw a decade ago. An increasing number of players fit the hyper-aggressive mold, so there are more matchups between them. The logic seems sound to me, though it may be the case that other sources of player inconsistency outweigh a woman’s particular risk profile.

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January 23, 1924: Debuts and dropshots

Men’s tennis ruled at the early Australian Championships. The tournament had been held since 1905 (as the “Australasian” Championships), but there was no women’s singles until 1922. On January 23rd, midway through the 1924 edition, the press corps was preoccupied with the severity of Gerald Patterson’s sprained ankle and the question of whether Ian McInnes had been practicing.

James O. Anderson, the 1922 singles champion who would win the 1924 edition as well, introduced what was then–at least to the Melbourne Argus–an on-court novelty:

He has developed a new stroke since he last played in Melbourne, and it has proved successful. On the back of the court he makes a pretence of sending in a hard drive, but with a delicate flick of the wrist he drops the ball just over the net, leaving his opponent helpless 30 feet away.

A veritable proto-Alcaraz, was James O.

For the few fans who weren’t solely focused on Australia’s Davis Cuppers, a superstar was emerging before their eyes. Also on the 23rd, 20-year-old Daphne Akhurst made quick work of Violet Mather, advancing to the semi-finals in her first appearance at the Championships.

Akhurst wouldn’t go any further, unable to withstand the heavy forehand of Esna Boyd in the next round. But it was nonetheless a remarkable debut: She won both the women’s and the mixed doubles titles. The correspondent for the Melbourne Age, recapping the mixed final, could hardly contain his admiration:

Miss Akhurst–an artist to her finger tips–belied her delicate mid-Victorian appearance that suggested that she had slipped out of one of Jane Austen’s books by sifting out cayenne pepper strokes from a never-failing supply.

Daphne and Jack Willard–“who ran for every ball, and continued running after he played the ball”–defeated Boyd and Gar Hone in straight sets.

The pair of championships was a harbinger of things to come. Between 1925 and 1931, Akhurst would win five singles titles (losing only in 1927 when she withdrew), four more in the women’s doubles, and another three mixed. The only thing that could stop her were the customs of the day: She married in 1930 and retired a year later. Tragically, she died from pregnancy complications in 1933, at the age of 29.

Daphne is best known these days as the name on the Australian Open women’s singles trophy. For the next several years, there will be many more Akhurst centennials to celebrate.

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Andrey Rublev, Grand Slam Quarter-finalist

Also today: Jannik Sinner’s rosy forecast; lopsided fifth sets

Andrey Rublev at Wimbledon in 2023. Credit: aarublevnews

Andrey Rublev is a known quantity. He will hit big first serves, but his second serves can be attacked. He will hit monster forehands, often venturing far into his backhand corner to play them, and his opponents will often be stuck in place, watching them go by. He’ll also miss a lot of them. His backhand isn’t the same type of offensive shot; he can be dragged into long rallies if you pepper that side.

There isn’t a lot of subtlety to his game. That isn’t a criticism: Subtlety can win you acolytes and endorsement deals, but it isn’t necessary to win championships. With yesterday’s five-set win in Australia over home hope Alex de Minaur, Rublev advanced to his tenth career grand slam quarter-final. He’s 0-9 so far in those matches, but his consistency in getting there is the bigger story. Alexander Zverev is the only other man under the age of 30 with ten major quarter-finals. Rublev will get on the board eventually.

What you might not know about the 26-year-old Russian is that he has matured into a reliably dangerous returner. He’s always been effective on that side of the ball, and his return numbers have remained steady as the strength of his competition has increased. Last year, he won nearly 39% of his return points, good for 3.2 breaks of serve per match–seventh-best on tour. At the 2023 US Open against Daniil Medvedev, his most recent attempt to reach a major semi-final, Rublev broke serve five times in his straight-set defeat. The return wasn’t the problem.

That day, Medvedev’s return was the problem. (Andrey’s second serve didn’t do him any favors either, but that’s nothing new.) Of Rublev’s 98 serve points, 65 of them lasted four shots on longer. I can’t emphasize enough how bizarre that is–or, seen from another perspective, what a performance it was from his opponent. Medvedev not only got 65 serves in play, he got 65 plus-one shots back. Rublev’s top two weapons were negated.

The standard Rublev performance, at least among the 138 matches logged by the Match Charting Project, involves 59% of his service points ending by the third shot. He wins just over three-quarters of those. (Against Medvedev, he tallied a respectable 70%, but 70% of not very many is still not very many.) Put those numbers together, and 45% of his serve points end in his favor in three shots or less.

That’s a pretty good head start! Last year, the Russian won 66% of his total serve points. The majority of the damage gets done early.

The serves and plus-ones not only account for a decent chunk of the points played–at least on a good day–but they also serve as a proxy for how the longer rallies turn out. When Rublev wins most of his short service points–even when he doesn’t play as many as he would like–he almost always comes out on top. If we sort his charted matches by winning percentage on short service points, then split them into thirds, the difference is stark:

<=3 SPW%       Matches  Match Win%  
81%+                45         87%  
75.5% - 80.9%       44         64%  
up to 75.4%         49         24%

(The buckets are slightly different sizes only because I didn't want to put nearly identical percentages into separate categories.)

When Rublev wins most of the short service points, he wins the match. When he doesn't, he usually loses. If anything, the table understates the contrast; a disproportionate number of the low-percentage victories came on clay, including several on the slow dirt of Monte Carlo.

To some extent, it's obvious that "winning more of some subset of points" correlates with "winning more of all the points" and thus winning the match. But remember, this is the success rate independent of how many points end quickly. The combination of frequency and success--"what percent of total service points end quickly and in the server's favor"--should tell us more about the overall result. But for Rublev, that metric isn't as predictive of final outcomes as the winning percentage alone.

Battling demon

Yesterday against de Minaur, Rublev won 82% of the short service points. The Australian kept it close by reducing the number of short points to just under half of Rublev's serves. But the rule I've just outlined held true, despite a pesky defense. When de Minaur put the fourth shot back in play, he won 57% of return points. That's great, but with Rublev cleaning up the overwhelming majority of the short points, it wasn't enough.

We have shot-by-shot logs for four of the six matches between these two guys:

Tournament        Result  Short%  Short W%  
2024 Australian        W   49.4%     82.0%  
2023 Rotterdam         L   60.3%     75.6%  
2022 Monte Carlo       W   42.7%     73.2%  
2018 Washington        L   53.2%     71.6%

De Minaur did his job yesterday, keeping the ball in play more often than he did in the two previous hard-court meetings. (The Monte Carlo surface presumably helped lengthen points in that match.) The Australian won both of those earlier contests, watching Rublev make more plus-one mistakes and taking care of business when the rallies lasted longer.

In Melbourne, the Russian stayed a bit more within himself. He was able to hit a forehand on barely half of his plus-one shots--below both tour average and his own typical rate. Instead of blasting away with ill-advised backhands--part of what lost him the Rotterdam match--he accepted the invitation to rally. His 43% rate of winning longer service points isn't great, but it's far superior to the 0% chance of claiming the point after smacking an unforced error.

I don't want to overstate Rublev's caution, because he didn't play a cautious match. He probably never should. But getting a few more balls in play and fighting out the ensuing rallies makes his second serve look a lot better. As we've seen, Rublev does well on return. His second-serve points aren't much better than return points... but that's okay! Yesterday he won 55% behind his second serve, a glittering result compared to the 37% and 38% he won against de Minaur in Washington and Rotterdam, respectively.

Is this the one?

Rublev can be forgiven for having a losing record in major quarter-finals; he's been the lower-ranked player in seven of the nine. He's dropped two to Novak Djokovic, one to Rafael Nadal, and three to Medvedev. He should have picked up one (or three) along the way, but as the fifth man on a tour that always seems to have a big three or four, it's an uphill struggle.

Tomorrow's opponent is Jannik Sinner, just one place above him in the ATP rankings. (Elo likes him more than that--a lot more. See below.) This will be their seventh meeting, and history doesn't bode well for the Russian. Sinner has retired twice but won the other four.

Here are the short-service-point stats for Rublev in three of those matches:

Tournament        Result  Short%  Short W%  
2023 Miami             L   62.5%     77.1%  
2022 Monte Carlo       L   41.0%     58.5%  
2021 Barcelona         L   43.8%     85.7%

(Unfortunately we don't yet have a chart of his 7-6, 7-5 loss last fall in Vienna.)

This isn't insurmountable for the Russian: He often wins matches behind 77% of his short service points, and he almost always does with a 86% win rate. He'd like more than 44% of his serve points to end quickly, but that's tougher to execute on clay.

Against Sinner, the first three shots are even more important than usual, because the Italian plays a similar game, and once a rally reaches four strokes, he plays that game better. In Miami, Sinner won two-thirds of Rublev's "long" service points. In Monte Carlo, he won 54%, in the vicinity of what de Minaur did yesterday. In Barcelona, Sinner won a whopping 70% of return points when he got the fourth shot in play--as he more often than not did.

Rublev's second serves tell the story, as they did in the de Minaur match. Those, typically, are the points he can't finish early, when he should be thinking in terms of constructing the point, not grunting and crushing. In the four completed Sinner matches, he won only 37.5% of second-serve points. That's not going to get it done.

To beat an elite opponent, Rublev needs to remember when to bash and when to think. He executed well yesterday, pulling away in the end against a man who never stops fighting. Reaching his first major semi-final, against 22-year-old who seems to get stronger every week, he'll need to play even better.

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Sinner in the hands of a friendly forecast

Jannik Sinner is the favorite tomorrow: According to my Elo-based forecast, he has a 78% chance of advancing to the final four. That's a hefty margin for a match between players adjacent to one another in the official rankings. The difference is more about Sinner than Rublev: My forecast gives Sinner a nearly 30% shot at taking the title, second only to Djokovic.

While the Italian ranks fourth on the ATP computer, he's second according to the Elo algorithm, closer to Djokovic than anyone else is to him. Here is the top of the table entering the Australian Open:

Rank  Player             Elo  
1     Novak Djokovic    2217  
2     Jannik Sinner     2197  
3     Carlos Alcaraz    2149  
4     Daniil Medvedev   2104  
5     Alexander Zverev  2037  
6     Andrey Rublev     2035  
7     Grigor Dimitrov   2032 

If you think in terms of major titles, official ranking points, or hype, this probably seems wrong. By those measures, Sinner is the laggard among the top four.

But Elo gives credit based on the quality of opponents beaten, and Sinner built quite a resume in the last quarter of 2023. He beat Rublev, Alcaraz, Medvedev (three times!), and most important, Djokovic twice. Nothing catapults you up the Elo list faster than knocking off the top dog.

The question, then, is whether Elo has overreacted to those two victories. My implementation of the Elo algorithm doesn't differentiate between narrow wins and blowouts. (Other versions use sets, games, or even points, though in my testing, those alternatives don't make the ratings more predictive.) The two Djokovic upsets were nail-biters. The Tour Finals round-robin match was decided in a third-set tiebreak, and each man won exactly 109 points. At the Davis Cup Finals, Sinner took the third set 7-5 despite winning fewer total points than his opponent.

While Sinner certainly deserved those victories--staring down match point against a 24-time major winner is a feat in itself--we might wonder how much they tell us about future results. If the two men keep fighting out such close matches, Djokovic is going to win some of them.

Each of the two upsets were worth a gain of 15 Elo points. Had Sinner lost them, he would've dropped 10 or 11 points instead. Call it a 25-point swing for each match. Thus, if we take the most pessimistic possible route and give both of the dead-heat results to Djokovic, Sinner's Elo rating would stand about 50 points lower, roughly tied with Alcaraz around 2,150.

(That isn't exactly right, because if Djokovic had won the Davis Cup match, Italy wouldn't have advanced to the final, and Sinner would've have beaten de Minaur. But Sinner did beat de Minaur, handily, and if we want to assess his current level, we shouldn't ignore that match.)

Handing both of the close results to Djokovic seems extreme. If we want to measure each player's current level without putting too much weight on the tiny number of points that decided those two matches, we might give one of the two victories to Djokovic. That would knock Sinner down to about 2,172, while boosting Djokovic to around 2,225.

In the Australian Open title-chances forecast, Novak would look a little better, and there would be more daylight between him and Sinner. Still, unless we make the harshest possible adjustment to Sinner's Elo rating, the Italian remains the next most likely Melbourne champion and a heavy favorite against Rublev tomorrow.

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Dessert bagels

The Rublev-de Minaur match had an unusual ending: After splitting four sets, the Russian ran away with the fifth, 6-0.

Typically, if two players are so evenly matched that they reach a fifth set, neither one is going to dominate the decider. For the rare occasions that it happens, it's unique enough that I think it deserves its own name. I propose "dessert bagel."

In grand slam competition since 1968, there have been just 159 dessert bagels, including Rublev's--fewer than one per major. No one has ever recorded a dessert bagel in a final, but it has happened twice in semis. Mats Wilander polished off Andre Agassi in the 1988 Roland Garros semi-final, and Djokovic finished his 2015 Australian Open semi against Stan Wawrinka the same way. Still, second-week dessert bagels are rare: Rublev's was only the 16th in more than a half-century.

It's an oddity piled on oddities: Rublev-de Minaur was the fifth dessert bagel in Melbourne this year:

Round  Winner      Loser       Score                
R128   Mannarino   Wawrinka    6-4 3-6 5-7 6-3 6-0  
R64    van Assche  Musetti     6-3 3-6 6-7 6-3 6-0  
R64    Medvedev    Ruusuvuori  3-6 6-7 6-4 7-6 6-0  
R32    Kecmanovic  Paul        6-4 3-6 2-6 7-6 6-0  
R16    Rublev      de Minaur   6-4 6-7 6-7 6-3 6-0

Five 6-0 deciders is a record for a single slam. There haven't been as many as three since the 2007 Australian, and no major has seen more than one since 2017. If even more dessert bagels start piling up in the quarter-finals, we'll know that something bizarre is going on Down Under.

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Predicting Next Year’s Elo Ratings

I often illustrate the difference between Elo ratings and the traditional ATP and WTA ranking-point systems as follows: The official rankings tell you how good a player was six months ago. Elo estimates where they are today. For the purposes of tournament entry and so on, a 52-week average makes sense. But if you’re predicting the outcome of tomorrow’s match, you don’t want to assign the same weight to a year-old result that you give to yesterday’s news.

That said, Elo ratings are not explicitly predictive. They rely only on past results. They don’t recognize the fact that a player on a hot streak will probably cool off, or that a younger player is more likely to improve than an older one. If we want to look further ahead than tomorrow’s match, we need to take some of those additional factors into account.

Hence today’s project: Projecting Elo ratings one year in advance. Elo ratings tend to be a leading indicator of official rankings, so if we can get some idea of a player’s future in Elo terms, we can estimate–very approximately, I admit–his or her ATP or WTA ranking even further out.

I kept things simple. Each player’s forecast is based on four variables: Age, current Elo rating, rating one year ago, and rating two years ago. Current rating is by far the most important consideration. It accounts for over 70% of the men’s forecast and 80% of the women’s. Everything else is essentially a tweak. The two older ratings allow the forecast to make adjustments if the current rating is an outlier. By including player age, we account for the fact that players over 25 or 26 start–on average!–to decline, and the older they are, the sharper the decline.

Take Novak Djokovic as an example. His current Elo rating is 2,227, one year ago it was 2,145, and two years ago it was 2,186. Because his 2023 year-end rating was higher than 2021 or 2022, we’d expect a small step backwards. And because he’s 36 years old, the laws of physics might eventually slow him down. Put it all together, and the model projects his 2024 year-end Elo at 2,116. Excellent, but slightly more human, and a number that would’ve placed him third on this year’s list.

Here is what the model predicts as the 2024 year-end top ten:

Rank  Player              2024 Elo  2023 Rank  2023 Elo  
1     Jannik Sinner           2144          2      2197  
2     Carlos Alcaraz          2137          3      2149  
3     Novak Djokovic          2116          1      2227  
4     Daniil Medvedev         2059          4      2104  
5     Alexander Zverev        2021          5      2024  
6     Andrey Rublev           1988          6      2020  
7     Stefanos Tsitsipas      1969          9      1974  
8     Holger Rune             1954         12      1936  
9     Hubert Hurkacz          1950          8      1983  
10    Grigor Dimitrov         1928          7      2011

As precise as that table looks, it is hard to predict the future. Here are the same ten players, with a 95% prediction interval shown:

The intervals demonstrate just how uncertain we are, with 12 months of tennis to play. If Jannik Sinner or Carlos Alcaraz hits the high end of his range, in the mid-2,300s, he’ll have established himself as a runaway number one. But if they surprise in the other direction, they’ll land below 2,000 and just barely stay in the top ten. Even these intervals don’t quite account for all the unknowns. There’s a nonzero chance that any of these guys will get hurt and miss most of the season, leaving them off the 2024 year-end list entirely.

I suspect, also, that a more sophisticated model would give a different range of outcomes for Djokovic. There are few precedents for his level of play at age 36, and he outperformed expectations in 2023. Had we run this model a year ago, it would’ve predicted a 2,071 Elo for him now. He beat that by more than 150 points, landing around the 85th percentile of the projection. But time is cruel. Since 1980, five out of six 36-year-olds have seen their Elo decline from the previous season. The average year-over-year change–including those few players who gained–is a loss of 45 points. It’s hard to bet against Djokovic, but at this point in his career, his downside almost certainly exceeds his upside.

Finally, let’s take a look at the projected 2024 top ten on the women’s side. It’s not nearly as juicy as the men’s forecast, as it barely differs from the 2023 list. As I mentioned above, a player’s current rating is a bigger factor in the forecast than it is for men–age is less of a factor, and if a player’s rating jumps around from year to year, women are more likely to stay at their current level than bounce back to a previous one. The forecast:

Rank  Player               2024 Elo  2023 Rank  2023 Elo  
1     Iga Swiatek              2197          1      2237  
2     Cori Gauff               2100          2      2127  
3     Aryna Sabalenka          2062          3      2099  
4     Jessica Pegula           2035          4      2089  
5     Elena Rybakina           2024          5      2059  
6     Marketa Vondrousova      1977          8      2005  
7     Ons Jabeur               1976          7      2007  
8     Karolina Muchova         1965          6      2014  
9     Qinwen Zheng             1961          9      2000  
10    Liudmila Samsonova       1938         11      1959

You might have noticed in both the ATP and WTA lists that most ratings–at least for top-tenners–are projected to go down. There’s a small regression component in the model, meaning that every player is expected to pull a bit back toward the middle of the pack. That doesn’t mean they will, of course, but on average, that’s what happens.

Here are the prediction intervals for the women’s top ten:

The magnitude of the intervals is about the same as it was for the men. Iga Swiatek could launch into a peak-Serena-like stratosphere, or she could, conceivably, land at the fringes of the top ten. Liudmila Samsonova, bringing up the end of this list, might challenge for a place in the top three, or she could be scrambling to stay in the top 50.

One thing is certain: The 2024 year-end lists won’t actually look like this. The value of this sort of forecast, even when it is so approximate, lies in the context it gives us. A year from now, we’ll be talking about which players outperformed or underperformed their expectations. Projections like these help us pin down what, exactly, was a reasonable expectation in the first place.

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The Purpose of Elo Ratings

The Tennis 128 will return tomorrow with player #126.

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The good news: Elo ratings for tennis are popping up in more and more places, exposing an increasing number of fans to an alternate (and superior) system for ranking tennis players.

The bad news: A lot of people don’t yet understand how Elo ratings differ from the traditional points-based rankings. Many newcomers criticize either specific ratings or the system as a whole, often because they expect Elo to be just like the official rankings, only with slight tweaks to better match their own beliefs.

The purpose in one sentence: Elo ratings are designed to estimate each player’s ability level right now.

That’s it. The ATP and WTA systems are a hodge-podge of arbitrary decisions meant to balance results, willingness to play lots of tournaments, and performance in the latter stages of particular events. That doesn’t mean they are wrong–there’s often not much difference between the official rankings and the Elo list. You can devise an awful lot of methods for ranking women tennis players right now, and almost all of them will put Ashleigh Barty at the top of the list.

When the results do differ, it’s important to remember what the official rankings prioritize. In the rankings released today, Naomi Osaka is 85th on the WTA computer, against 12th in my Elo ratings. Despite the enormous gap, in a way, they’re both right. Osaka has played only seven events since last year’s Australian Open, so the WTA method treats her as a part-timer with a handful of decent results. Elo, on the other hand, recognizes that she won two of the last six grand slams. It rates her lower than it did a year ago, but Elo doesn’t simply forget about extremes of form because a magic 52-week window expires.

If you’re interested in what a player deserves (whatever that means), the ATP and WTA formulae are probably what you’re looking for. You may have some quibbles with the system, but everybody knows (approximately) how it works. If a player wants to crack the top ten, she understands what she needs to do, and at which events, to accomplish that.

If you’re interested in who will win tomorrow, Elo is almost always your better bet. The official rankings don’t even try to estimate a player’s current level. By definition, they serve as the average of a player’s performances over the last 52 weeks (unless a pandemic changes the rules), so the ranking is a decent approximation of their level five or six months ago. Osaka may not “deserve” a spot in the top 80, but most of us would be ecstatic to make an even money bet that she would beat #84 Anna Bondar or #86 Xinyu Wang. Elo’s estimate of #12 suggests a much more plausible range for how well she will play the next time she steps on court.

Just as the official rankings don’t try to estimate a player’s current form, Elo doesn’t concern itself with what players “deserve.” You might think that Gael Monfils has earned his spot in the top 20–after all, he won a tournament to start the year and followed it up with a run to the Australian Open quarter-finals. Elo had him several places lower, even before his opening-match loss to Mikael Ymer last week. Now he sits at #32. A major quarter-final is a nice achievement, but Elo recognizes that Monfils’s eight wins in Adelaide and Melbourne were against mediocre competition, including several players who were playing on their weaker surface.

Personally, I don’t care much about what players “deserve” from a system that–while adequate and widely accepted–is slapped together and incoherent. I’m more interested in who’s playing the best tennis, so Elo is exactly what I want to see. But that doesn’t mean you have to feel the same way. If you want your rankings to measure something else, that’s fine. Just don’t get mad at Elo.

20 > 21 > 20

Rafael Nadal has finally nosed his way into the lead. With his Australian Open title yesterday, he became the first man to 21 major singles titles, breaking away from the three-way tie at 20 with Novak Djokovic and Roger Federer.

For some people, leading the all-time grand slam race is enough to cement a player as the greatest of all time. A different crowd considers this year’s Australian Open tainted because Djokovic was not allowed to play. Still others think that Federer played some beautiful tennis, and they considered the matter concluded at least five years ago.

I belong to a fourth camp, which I can summarize with two positions:

  1. The grand slam race isn’t everything.
  2. If you do focus on grand slams, you must adjust the major count for the quality of opponents each player faced.

I’ve written about this before, first at The Economist, and then here at the blog. When I checked in 18 months ago, Nadal’s 20 majors were worth a bit more than Djokovic’s 17, which were themselves more impressive than Federer’s 20. The margins have always been slim between these three, and properly adjusting for quality of opponents makes things even tighter.

The update

Here’s how the adjustment works. For each slam that a player won, we take the Elo rating of all of his opponents, and work out the probability that the average Open Era grand slam winner would beat all of them. Once we have that number–which centers around 23%–we normalize it so that the value of an “average” major is 1.0.

When a major title requires facing down a lot of tough opponents, its rating is higher than 1.0, while a relatively easy one rates below 1.0. In the last few years, the numbers have drifted downward, because while the familiar names keep winning quite a bit, they haven’t needed to face each other as often as they used to.

You might disagree with the methodology, and that’s fine. But I find that most people end up making some sorts of adjustments, even if they shy away from stats or only tweak the totals when it favors their idol. Some Djokovic fans want to downplay Nadal’s recent win, and it’s true that Novak’s absence lowered the quality of the draw. But surely Rafa’s title isn’t worth zero. He beat many excellent players, and there was no guarantee that Novak would advance through the draw–or that Rafa would lose if they met.

This approach allows us to avoid specific minefields and answer all the analogous questions about every slam. Considering the seven opponents that Nadal faced, his Melbourne title rates at 0.84, weaker than average, but more difficult than seven of his prior titles. Djokovic has not enjoyed as many “easy” paths to major titles, but his Wimbledon victory last summer rates at a mere 0.60, the second-weakest of his career and lower than all but one of Rafa’s. Sometimes players just get lucky, with or without a geopolitical brouhaha.

Nadal’s 21st title rates only a bit lower than Djokovic’s two other titles last year: 0.90 at the Australian and 0.93 at the French.

Here are the updated rankings for “adjusted slams,” along with a table showing how many easy, medium, and hard paths that the Big Three have endured:

Player    Slams  Avg Score  Total  
Nadal        21       0.95   19.9  
Djokovic     20       1.01   20.1  
Federer      20       0.89   17.9  
                                   
Player     Easy     Medium   Hard  
Nadal         8          8      5  
Djokovic      6          7      7  
Federer       9         10      1

As if 21 and 20 weren’t close enough, this approach gives Djokovic 20.1 adjusted slams to Nadal’s 19.9. Again, you don’t have to agree with every step of my approach here to accept that we often think in terms of these kind of adjustments, and that Djokovic has–on average–faced tougher roads to titles than Nadal, while Federer had it easier than both of them.

Players can’t control who they face, but as fans, we can appreciate who worked the hardest to achieve near-equivalent feats. Fingers crossed that both Novak and Rafa excel at Roland Garros, so they can fight it out on the court, not in some random guy’s spreadsheets.

Aslan Karatsev Isn’t Better Than Novak Djokovic, But…

What’s better, winning 15 of 17 matches, or going undefeated for 9?

Even if you know that the 15-2 guy is Aslan Karatsev in 2021, and the 9-0 guy is Novak Djokovic this year, there’s no obvious answer. Sure, Djokovic beat Karatsev easily, and Novak’s nine wins included a grand slam title. We know Djokovic is the better player–he’s got more than a decade of proof to support that claim–and no one in their right mind would take Karatsev’s last three months over Novak’s.

True as all of that is, it’s not the question I’m asking.

The player with the 15-2 record has two advantages over his 9-0 peer. First, he has more wins. (Mind-blowing stuff, I know.) Second and more importantly, he has more evidence of his current level, even if it includes two losses. The 9-0 guy could go undefeated for 17 matches… but he could also end up 11-6. His nine-match record simply doesn’t give us as much information.

Again, if you know which players I’m talking about, that doesn’t matter–we have 1,100 matches worth of information about Djokovic, most of which say that his 9-0 is business as usual. He might not win his next eight matches, but he’s certainly not going to lose more than a few of them.

The yElo light at the end of the tunnel

If you’ve been reading my last couple of posts, you know where I’m going with this.

Last week, I introduced the concept of yElo. The “y” stands for year, but it can be used for any unit of time shorter than an entire career. Instead of using every bit of available information, we look only at a designated time frame, such as the 2021 season. While maintaining our knowledge of other players (e.g. Andrey Rublev is a really tough opponent; Egor Gerasimov not so much), we treat each player as if we know nothing else about him.

So truly, we’re comparing Karatsev’s 15-2 with Djokovic’s 9-0, taking into account the quality of their competition.

Plug every ATPer’s 2021 season into the formula, and here are the yElo leaders, through last weekend’s finals in Dubai and Acapulco:

Rank  Player                  W-L  yElo  
1     Aslan Karatsev         15-2  2082  
2     Novak Djokovic          9-0  2081  
3     Daniil Medvedev        13-2  2061  
4     Andrey Rublev          15-3  2006  
5     Marton Fucsovics       14-4  2000  
6     Stefanos Tsitsipas     14-4  1983  
7     Alexander Zverev        9-4  1922  
8     Matteo Berrettini       8-2  1918  
9     Jeremy Chardy          13-6  1915  
10    Lloyd Harris           11-5  1878  
11    Jannik Sinner           9-4  1848  
12    Alexei Popyrin          9-3  1836  
13    Roberto Bautista Agut   8-7  1831  
14    Taylor Fritz            7-4  1830  
15    Sebastian Baez         14-1  1820  
16    Felix Auger Aliassime   8-4  1818  
17    Karen Khachanov         9-5  1810  
18    Mackenzie McDonald     11-5  1809  
19    Tomas Machac           10-3  1806  
20    Daniel Evans            6-3  1800

Yes, Karatsev really does outscore Djokovic. Barely.

We are accustomed to 52-week rankings and Elo ratings that carefully weigh an entire career’s worth of work. So this is a deeply weird list, with only a handful of players anywhere near where we’d expect. #15 and #19 are Challenger-level guys, for crying out loud!

Embrace the race

The official Race to Turin doesn’t look as bizarre as the yElo list, but imagine showing it to someone in December, with Karatsev 5th, Marton Fucsovics 7th, and Rafael Nadal outside the top 20. Both the Race and the yElo list are “wrong” in the traditional sense, but they tell us much more about the 2021 season than the old-fashioned rankings do.

Tennis’s relentless focus on the long view sucks some excitement out of the season. Think of virtually any team sport. A month into the season, some unheralded club has gotten off to a hot start, and at least in some quarters, that’s the story–can they keep it up? should we have seen this coming all along? Nobodies are cast in the role of front-runners, and established stars play the part of underdogs.

In tennis, nobodies are… well, nobodies who won a few matches lately. Superstars play the part of superstars who’ve been taking some time off. Sure, we know that Djokovic and Nadal are going to end up near the top of the rankings list in November, just like we know the Dodgers and Yankees will be in the playoffs. But that doesn’t mean we ought to take it as a foregone conclusion from day one. In baseball, as the saying goes, everybody’s in first place on Opening Day.

Embracing the race–focusing on which players are leading the pack at each point throughout the season–doesn’t have to mean throwing away longer-term rankings. The traditional calculations should still be used for tournament entries and (maybe) for seedings. Top players have earned as much, and tournament entry is a factor that isn’t present in the major team sports.

Everybody wants to know how the ATP will survive when the Big Three are out of the picture. Well, this is a start–pay attention to who’s winning in 2021. If we take yElo’s word for it, a virtual nobody emerged to overtake Djokovic for the #1 spot going into Miami! An Argentinian prospect is playing like a top-15 guy just by winning a bunch of Challengers! Jeremy Chardy is more than just a hitting partner for the other Frenchmen!

The stories are out there, just like they are every year. It’s a shame that they get buried by all the talk about players who won last year.

I’ve added men’s and women’s yElo ratings to the Tennis Abstract website, and they’ll be updated weekly.

The Best 22-Match yElo Streaks

Earlier this week I wrote about Garbine Muguruza’s outstanding start to the season, and I introduced a new method to quantify a player’s level in a relatively short time span. Instead of using traditional Elo, which takes into account everything we know about a player, my new metric, yElo, uses what we know about everyone else, but treats a player’s short-term performance as if it is all we know about her. The parameters for yElo, such as k-value, are the same as the ones I’ve arrived at to make “regular Elo” as predictive as possible.

In other words, we measure Muguruza’s 22 matches in 2021 as if she had never played a WTA event before. As we saw in my earlier post, this approach considers the strength of opponents each player faced, and it rates her 18-4 record as better than anyone else in 2021, including Naomi Osaka’s 10-0 start.*

* excluding walkovers, which I ignore for all versions of Elo and yElo.

Muguruza’s season start has been outstanding and it is definitely underrated by the official WTA rankings and maybe even by the race, but I don’t want to make too much of it–one title in five tournaments in hardly world-historical stuff. On the other hand, it’s a good way to get our feet wet with a new metric that I think will prove useful for a wide range of tennis comparisons.

Garbine vs Garbine

The Spaniard won majors in 2016 and 2017, and she briefly reached number one in the rankings in September of 2017. Those achievements belong on a Hall of Fame plaque over her recent Dubai title and Yarra River Classic final. But was she really playing better back then?

She was not! I ran the yElo formula for every 22-match sequence in Muguruza’s career. The best of the bunch–again, taken entirely out of context, as if we know nothing beyond those 22 matches–was a run late in 2015 when she reached the Wuhan final, won Beijing, then went undefeated in the WTA Finals round robin stage. Her yElo based on those 22 matches was 2172, narrowly better than her 2021 yElo of 2160.

The more memorable moments of her career don’t quite stack up:

Elo   W-L   Span                            
2172  17-5  2015 Wim R16 - WTA Finals RR    
2160  18-4  2021 Abu Dhabi R64 - Dubai F    
2148  18-4  2017 Birmingham R32 - Cinci F   
2122  19-3  2017 Wimb R128 - USO R16 (#1)   
2084  17-5  2017 Miami R64 - Wimb F         
2076  16-6  2016 Doha QF - Roland Garros F 

I haven’t shown every 22-match sequence of her career, because that list is long and boring–the streaks heavily overlap with each other, and thus there are often tiny differences between them. But it is instructive to look at the time periods that ended at key moments.

The best of that bunch was the 22-match run ending with Muguruza’s 6-1 6-0 beatdown of Simona Halep at the 2017 Cincinnati final. That set the stage for her ascent to #1, though the ranking move didn’t happen until after the US Open. That streak is close to her current level. The 22 matches leading up to the official #1 takeover are a bit lower (she lost to Petra Kvitova at the US Open, which was less forgivable then than now), and the timespans ending with her two slam finals are still further down the list.

Don’t misunderstand–Muguruza was playing very well throughout all of these time periods. But when we crunch the numbers, we find that her current level is roughly on par with the best she’s ever played.

Garbine vs the world

Metrics are a lot more informative once we gain some context. Many of you probably have a good sense of what regular Elo ratings mean–2100+ is outstanding, 2000+ is top ten-ish, 1900+ is approximately the top 20, and so on. We can piggyback on that for yElo. When Muguruza’s 22-match yElo this season is 2160, it really does mean that, when feeding that very limited set of results into the Elo formula, it thinks Muguruza’s level is close to that of the best player in the world.

Well… the best player in the world right now. There’s no truly dominant force in women’s tennis at the moment, so we’re not seeing players at the top end of the all-time Elo scale. In regular Elo, peak Martina Navratilova and peak Steffi Graf topped 2600, more than 400 points above Osaka’s current rating of 2189. It will not surprise you, then, to learn that Navratilova, Graf, Serena Williams, Chris Evert, and many others put together 22-match runs* that make Muguruza’s 2021 season look positively pedestrian.

* yes, I know how ridiculous it is that this whole article is based on the arbitrary 22-match time span. We could do the same stuff with the more natural-sounding 20-match span, but there wouldn’t be an intuitive way to fit Muguruza’s current run into the discussion. And let’s face it, 20 is just as arbitrary as 22.

Out of my entire database on women’s tennis results going back to 1950 or so, about 100 women have enjoyed a 22-match run that outscores Muguruza’s best. The top of the list is the end of Navratilova’s 1983 season, which is worth a yElo of 2445. Close behind is Monica Seles, who reached 2438 with a streak starting at the end of 1992 and extending into the 1993 season. Three more women topped 2400, another 27 exceeded 2300, and 46 more put together 22 consecutive matches worth at least 2200.

Here are the 15 active women who’ve played at least as well as Muguruza for their best 22-match spans:

yElo  Player                W-L   Year(s)  
2389  Serena Williams       21-1  2001-02  
2386  Venus Williams        22-0  2000     
2335  Kim Clijsters         20-2  2002-03  
2332  Victoria Azarenka     22-0  2012     
2234  Vera Zvonareva        18-4  2008     
2217  Svetlana Kuznetsova   19-3  2004     
2217  Naomi Osaka           20-2  2019-20  
2209  Samantha Stosur       20-2  2010     
2205  Petra Kvitova         19-3  2011-12  
2205  Simona Halep          20-2  2018     
2196  Caroline Garcia       18-4  2017     
2186  Ashleigh Barty        19-3  2019     
2180  Angelique Kerber      18-4  2015-16  
2174  Carla Suarez Navarro  18-4  2015     
2172  Garbine Muguruza      17-5  2015

With the caveat that I haven’t spent much of my life thinking about the best 22-match runs in women’s tennis history, this seems like a credible list. I particularly like how yElo manages to consider strength of opponent to the point that an 18-4 run*, like Zvonareva’s in 2008, can outrank so many 20-2s. (Vera even beats a few 22-0s from the amateur era.)

* the link shows a few extra matches–the 18-4 run starts in the QFs of Guangzhou and ends in the Tour Finals semi-final. Note again that yElo skips retirements.

I hope you find the new yElo metric as interesting as I do. I’ll definitely be doing more with it, since I suspect it has value even outside the narrow context of one player and a single timespan of arbitrary lenth.

Repurposing Elo for Streaks, Seasons, and Garbine Muguruza

Elo is a fantastic tool for its explicit purpose: estimating the skill level of players based on available information. For instance, my WTA ratings currently rank Ashleigh Barty second. That seems plausible enough–it may be correct to give her the edge in a head-to-head matchup with everyone on tour except for Naomi Osaka. But with women pursuing such different schedules this season, a rating is only so useful.

For all of Barty’s or Osaka’s skill, is it right to say either one of them has had a better 2021 season than Garbine Muguruza? Osaka won the Australian Open, so she has a valid claim. Barty’s argument is a lot more tenuous, based on only eight victories. The Spaniard’s case writes itself–only a handful of players are up to double digits in wins this year, and Muguruza already has 18. How could we decide? If Elo is the smart version of the official rankings, what’s the smart version of the official race?

Starting fresh

The Elo algorithm itself offers a solution. A big part of the reason Muguruza is rated 4th on my current Elo list–and not higher–is her career before 2021. We had hundreds of matches worth of data on Garbine before January 1st, and it would be silly to throw all that away. Her 18-4 start is fantastic, but it doesn’t supersede everything that came before. It just gives us reason to update our rating.

Here’s where the ranking/race analogy is useful. The official rankings use a time span of 52 weeks (or more). The race restarts on January 1st. We could do the exact same thing with Elo, throwing away all results from the previous year and starting over, but that would be wasteful–it wouldn’t allow us to take into account whether players had faced particularly easy or tough draws, for instance.

The solution is to set Elo ratings back to zero (or 1500, in Elo parlance) one player at a time.

Take Muguruza. Instead of starting the year with a rating of 1981 and a history of several hundred matches, we pretend to know nothing about her. We give her a newbie’s rating of 1500 and a history of zero matches. Then we run the Elo algorithm to update her rating over the course of her 22 matches. First she faces Kristina Mladenovic (with her actual rating at the time of 1817), and improves to 1605. Then she beats Aliaksandra Sasnovich (and her rating of 1805), and improves to 1692. Repeat for each of her 2021 results, and the end result is a rating of 2160–almost 100 points higher than her current “real Elo” rating and within shouting distance of Osaka’s 2189.

To compare players, work through the same steps for everybody else, calculating their current-season rating as if they played their first career match in January.

It’s worth taking a moment to think about exactly what we’re measuring. That outstanding 2160 rating is what you get if a complete unknown shows up with zero match experience, then goes on the 22-match run that has been Muguruza’s season so far. The difference between real-Garbine and fake-newbie-Garbine is that the real one has an extensive track record that tells us she’s always been good–but that she probably isn’t quite this good.

I call it … yElo

This approach is “Elo for seasons” or “year Elo”–yElo*. It doesn’t have to be limited to calendar years, as the same approach would be useful to comparing, say, 20-match segments. It allows us to take advantage of the Elo algorithm–and the well-informed ratings of other players–to measure partial careers.

* you can pronounce it like the color “yellow,” but I prefer to say it like Phil Dunphy from Modern Family answering the phone.

Muguruza’s 2160 rating sure looks good, so how does it stack up against the rest of the tour? Here’s the 2021 top 20, considering players with at least five match wins through the Dubai and Guadalajara finals last weekend:

Rank  Player                W-L  yElo  
1     Garbine Muguruza     18-4  2160  
2     Naomi Osaka          10-0  2094  
3     Jessica Pegula       15-5  2002  
4     Serena Williams       8-1  1997  
5     Elise Mertens        11-2  1971  
6     Karolina Muchova      7-1  1953  
7     Aryna Sabalenka      11-4  1943  
8     Iga Swiatek          10-3  1941  
9     Daria Kasatkina      10-4  1910  
10    Barbora Krejcikova   10-5  1905  
11    Shelby Rogers         9-4  1902  
12    Jil Teichmann         9-5  1899  
13    Anett Kontaveit       9-4  1897  
14    Jennifer Brady        9-4  1892  
15    Cori Gauff           11-5  1885  
16    Danielle Collins      9-4  1883  
17    Ashleigh Barty        8-2  1878  
18    Sara Sorribes Tormo   9-2  1867  
19    Ann Li                5-1  1864  
20    Simona Halep          6-2  1854 

Like any Race list in March, this isn’t really reflective of skill. But when we consider the small amount of data it has to work with for each player, it’s … pretty good?

Again, you can quibble over whether Osaka or Muguruza has had the better season, but this approach weighs the better winning percentage and stronger average opponent against the much higher absolute win count and gives us a credible answer. Muguruza’s additional evidence of good tennis playing puts her ahead of Osaka’s evidence of short-term unbeatability.

While yElo is basically just a toy–it certainly doesn’t have the same predictive value as regular Elo–this initial look makes me like it. The possibilities are endless, from more sophisticated race tracking, to ranking the greatest seasons of all time, to comparing a player’s current hot streak to what’s she’s done in the past. Stay tuned, as I’m sure I’ll have more yElo results to report in the future.