Happy New Year! (By Which, Of Course, I Mean 1963)

Another week, another enormous tranche of new women’s tennis data on Tennis Abstract. Today I present an extensive view of the 1963 season, including about 250 events and almost 3,000 matches. The season page is here, so jump in whenever you’d like.

This is the fifth amateur-era season I’ve added. I hesitate to use the word “complete,” because there is no clear line separating “tour level” from the rest, and for many of the tournaments I have only partial results. Even for the top players, some early-round matches may be lost to history. But as an in-depth view of the era, we continue to break new ground. For comparison, there were about 3,100 WTA tour-level matches in 2019, and we now have almost the same number of results from 1963.

I’ve made a few more improvements to the season pages, which are now available from 1963 to 1986:

  • The Elo rankings table now includes columns for “iElo” — ratings specific to carpet (and wood and tiles and whatever artificial surfaces that organizers put on the floor of their indoor facilities). The “i” stands for “indoor,” although iElo does not include indoor hard or clay results. Those were rare at the time, and are included with the hard- and clay-specific ratings.
  • The list of number-one ranked players now shows how long each woman held the top spot–including in other seasons. For 1963, the “list” is rather boring, as it consists solely of Margaret Court, but it does show that Court owned the number one position from the end of 1961 through to her first layoff in 1967. The exact numbers and start/end dates are very much subject to change as I add more data, correct errors, and improve the Elo algorithm, but all told, I have Court at #1 for a total of 536 weeks.

Coincidentally, I recently charted the 1963 Wimbledon final between Court and Billie Jean King. While it was their only meeting this season, it was one of more than 30 in their careers between 1962 and 1973.

As usual, the raw data is now available in my GitHub repo, and I gratefully acknowledge the work done by the Blast From the Past contributors at tennisforum.com.

277 Events From the 1964 Women’s Tennis Season

The quest continues, and there are now another 3,200 matches in the women’s tennis database at Tennis Abstract. If you’d rather dive in to the data than read my ramblings about it, click here for the 1964 season page.

(If you’d like to read more of my ramblings, here are my intros to 1965, 1966, and 1967 data.)

The further back we go, we more we confirm the dominance of Margaret Court in the decade before the Open Era. In 1964, she won two majors, reached the final of a third, posted a year-end Elo just shy of 2500, and went undefeated over 44 matches on clay courts. Just about the only stats she didn’t dominate were three-set numbers, because she almost always won in straights.

Of course, there’s a lot more to 1964 than one Australian star. Importing these thousands of match results meant adding 360 new players to the database, including some important contributors whose career ended this season. Here are a few:

The women’s season pages are now available for every year from 1964 up to 1978. You can navigate between seasons using the links in the upper-left corner of every page. I’ll further integrate the season pages into the rest of the site soon.

As usual, the raw data is available in my women’s tennis GitHub repo.

Finally: Another round of thanks are due to the contributors at tennisforum.com, who searched out newspapers and annuals, then typed up all these results. The same group is responsible for the Blast Encyclopedia of Female Tennis Players, an essential source for biographical data, especially married names.

Enjoy!

New at Tennis Abstract: Over 3,000 Match Results from 1965

Welcome to the latest update on a project that has well and truly spiraled out of control. I’m pleased to announced that the Tennis Abstract site now features a huge amount of women’s tennis data from 1965. I hesitate to call it “complete,” because it is not, and it probably never will be. But the word “substantial” will do just fine:

  • 3,200 matches
  • 248 events (plus Federation Cup)
  • 400 players that weren’t previously in my database

The 1965 dataset is even more sizable than the 1967 and 1966 results that I’ve recently discussed in other blog posts. To put those 3,200 results in perspective, there were “only” about 3,100 tour-level WTA matches in 2019.

For an bird’s-eye view of the 1965 women’s season, check out my season page. I introduced the season pages with my post on 1966 last week, and I’ve since made several improvements:

  • The full event calendar has some new information to indicate the strength of the tournament: the number of top 10 players in the draw (as per that week’s Elo ratings), and the “geographic concentration” of the field–that is, the percentage of women in the draw who hail from the most common country. The second number isn’t perfect, especially when I only have a few results from the event, but as a general rule, the lower the geographic concentration, the stronger the field.
  • The year-end Elo rankings table includes some helpful additional information: each player’s age, her number of titles, and her won-loss record on the season.

The season page tends to highlight the best players, and I’d imagine that’s what most of you will find the most interesting. Margaret Court dominated the 1965 campaign, winning over 100 matches, losing only 8, and posting the best year-end Elo on all surfaces. The page will also tell that you she drew Lesley Bowrey ten times–nine of them in finals!–and Bowrey accounted for 4 of her 8 losses.

(Court and Bowrey were already familiar foes: They met in the 1960 Australian Championships girl’s final. Court lost, but bounced back quickly, winning the women’s final–her first major title–the next day.)

Equally fascinating for me are the names you almost never hear in their tennis context. Since I’m working backward, the players I added to the database for 1965 were those who finished their careers that year. (Or played predominantly at lesser regional events, and only briefly popped up on my radar.) Here are a few of the ladies whose tennis careers I stumbled upon:

I could list many more.

Data and acknowledgements

Once again, I note the huge debt I owe to the contributors at tennisforum.com’s Blast From the Past section. They’ve converted newspaper and annual results into online content that I could then further organize into a proper dataset.

All of the raw data is available in my women’s tennis GitHub repo.

The 1966 Women’s Tennis Season Like You’ve Never Seen It Before

I’ve been working hard to organize 1960s and 1970s women’s tennis results so that you can view and search it as easily as if they took place last month. It’s an enormous task, and probably never to be completed, but I do have some progress to share.

A couple of weeks ago, I announced the inclusion of the 1967 women’s tennis season on Tennis Abstract and discussed why it’s so important. Today, I give you 1966, along with a much easier way to dive in.

The season view

Here’s a one-page overview of the 1966 season. On that one page, you’ll find:

  • The results of the four majors, at a glance
  • Some key statistical leaders
  • A full calendar of all the tournaments in the database, along with finalists and semi-finalists (in 1966, that’s 159 events!)
  • Year-end Elo rankings, including surface-specific ratings (yes, Elo for the 1960s!)
  • Elo number ones for the season (Margaret Court made that rather uninteresting for much of the decade, monopolizing the top spot this year and several others)
  • Sortable stats for the 30 most active players, including won-loss records in finals, in three-setters, and on all surfaces
  • The most common head-to-heads
  • Country-versus-country won-loss records, which offers a glimpse of which nations predominated at the time

Of course, the page contains links galore. One more click gets you detailed player pages just like the ones available for current players, or event-specific pages with full tournament draws. The database contains over 2,600 matches from the 1966 season.

(Once I work out all the kinks, I’ll generate similar pages for later seasons as well.)

What’s here and what’s not

To repeat myself from the 1967 post: This project owes a tremendous debt to the contributors at tennisforum.com’s Blast From the Past section. They’ve typed in tens of thousands of results compiled from newspapers and annuals. Without their efforts, I would barely be getting started. I highly recommend browsing that forum. In addition to the singles results, it contains doubles and mixed doubles scores, as well as descriptions of some of the top events. It’s one of the truly invaluable corners of the internet.

Newspapers and annuals didn’t report everything, and even the tireless Blast compilers haven’t scanned every possible source. Thus, some tournaments are missing rounds or specific matches. For some events, I have only the final. There are still other events that I would love to include, but am unable to for lack of data, such as the annual ATA championships and many of the tournaments that took place in the USSR.

I also haven’t imported every single possible result. There was no clear demarcation between “tour-level” and the rest back then, but some events were much stronger than others. Just because the results of the Wyoming state championships have survived doesn’t mean you can find them on Tennis Abstract.

That said, I’ve erred on the side of over-inclusion. There is at least one result from over 150 different 1966 events, and that number will be over 200 from 1962 to 1965! If a tournament has even one great player, I’ve imported the entire draw. (Ann Jones, who seems to have played just about every tournament in Great Britain for 15 years, has repeatedly made me question that commitment.) I’ve included virtually everything from the USSR and the former Eastern Bloc nations, along with nearly every tournament that included players from Eastern Europe. There was much less East-West mixing than there is now, so these results are particularly important for establishing the level of play behind the Iron Curtain.

About these Elos

It’s particularly exciting to be able to rate these players, both to find unheralded women from this era, and to see how the stars of the 1960s stack up against those of later eras. Of course, a certain Elo rating doesn’t mean the same thing in 1966 as it did in 2016, because the level of play has risen, and the game has changed in innumerable ways. That said, my Elo algorithm doesn’t suffer from any kind of inflation, so a certain rating–say, Billie Jean King‘s 1966 year-end 2274–means roughly the same thing relative to her peers as it does now.

These Elo ratings are provisional, however. For one thing, there’s a lot more historical data to be added. As the algorithm can look at more matches from the early 1960s, it can better calculate proper ratings for each player in 1966.

Also, the less-structured nature of the tennis tour in the 1960s may necessitate some tweaks to the algorithm. As I’ve said, there’s no clear top level, and there’s certainly no helpful classifications like Satellites or Challengers or ITF W15s. While the best players did a lot of traveling, they represented a much smaller core than the hundreds of full-time nomads who populate today’s tour. Thus, 1960s stars played more early-round matches against locals who–at least in tennis terms–would never be heard from again.

So far, my Elo algorithm is spitting out plausible results for the 1960s without any era-specific alterations. Adding thousands more matches and hundreds of new players is not causing any noticeable inflation in the ratings of later players. But any of those things might change.

The data

I’m making all of this data available in my GitHub repo for women’s tennis results.

In addition to “new” seasons like 1966, I’m also working on filling in lower-level events and qualifying rounds for the 1970s. I have about 50 tournaments per year from 1968 through the mid-70s, but I’m finding that there are 100 or more per year that could be added, plus qualifying for the big events. I recently added 1,500 such “additional” matches from 1974 alone.

These are all on Tennis Abstract as well, so to take just one example, you can see Virginia Ruzici fighting her way through qualifying rounds at the big tournaments to start 1974. Once I finish with 1973, you’ll be able to see evidence of something almost unthinkable: Martina Navratilova playing qualies. It didn’t last long, but it did happen.

Enjoy!

Welcome to 1967

Last week, I finished* adding complete** 1967 women’s results to the Tennis Abstract site. I’ll talk about those asterisks in a bit, but for the moment I’d prefer to revel in how cool this is.

The “Open Era” starts in 1968, and in the near-decade since I launched TA, I took that year as my starting point. Along the way I added men’s slams and Davis Cup back to the beginning, but it’s buried on the site as an afterthought. I can’t imagine that anyone uses the site for amateur-era results.

Even late 60s and 70s results were spotty for women. I initially built my database from the results published on the WTA and ITF websites, neither of which is (how to put this mildly?) primarily focused on the thoroughness and accessibility of its historical data. Add in the mistakes and omissions that come from building my own database from scratch, and you end up with a lot of gaps.

A more complete Tennis Abstract

A few weeks ago, I started filling in those gaps by adding about 20 missing tournaments with a Chris EvertMartina Navratilova match. That head-to-head is now complete. Soon it will be “more than complete,” as I add various exhibitions that don’t count in the official tally. From there, I used various sources (more on that below) to fill in the remaining gaps of top-level Open Era women’s tennis back to 1968. The result is about 50 full tournaments per year, sometimes more, with various bonuses like Federation Cup and a lot of grand slam qualifying.

The further back I went and the more I stumbled on stories about the women’s game at the beginning of the Open Era, the more I wanted to know. 1968 is an important year, but a lot of tennis was unchanged from 1967 to 1968–almost all of the same players excelled, on the same surfaces and mostly at the same events. It seems a little silly to have a statistical record that starts smack in the middle of all-time-great careers like those of Billie Jean King and Margaret Court.

Into the unknown

One of the most incredible online tennis resources is one you’ve probably never heard of. On the “Blast From the Past” section of tennisforum.com, a group of contributors have assembled a unparalleled collection of women’s match results going back to the 1800s. They’ve dredged up results and tournament information from old annuals, newspapers, and just about any other source you can imagine.

The disadvantage of their forum-based, text-based format is that it is only awkwardly searchable. (Just to be clear, I am not taking anything away from their outstanding efforts.) The forum approach does allow for a certain kind of serendipity, and I’m sure I’m not the only one who has lost hours scrolling, reviewing results, reading the tournament recaps and anecdotes collected there. But it precludes the kind of serendipity made possible by sites like Baseball Reference and Tennis Abstract, where you see one result, get curious about a player, click the player’s name, and find yourself looking at a whole new list of unfamiliar scores and stats.

The further back in history we go, the more I want that kind of serendipity. Now, Tennis Abstract has that for 1967, and soon it will go back further still.

Okay then: 1967

The site now includes results from over 100 events in 1967, from familiar names like Rome and Queen’s Club to lesser tournaments such as the Pan-American Games (held that year in Winnipeg) and the Soviet Championships in Tblisi. I don’t have complete data for every draw–some are missing a handful of first-rounders, and others have only the final round or two. All told, the database now includes almost 2,300 matches from that single year. By comparison, there were about 3,000 tour-level WTA matches in 2019.

Since there was no formal “tour” in 1967, there’s no official definition of what’s “in” or “out.” A match is a match. I didn’t include every single event with some kind of data available, but I did import the entire main draw of any tournament with even a single “big-name” player, using a fairly broad definition of that term. (1969 Wimbledon champ Ann Jones may make me regret that decision. She played a lot of tennis.) Because the various circuits were more fractured, that means more events: There were many weeks with three or four tournaments each, and a couple with five.

Creating records for those 2,300 matches meant adding almost 300 players who weren’t in my database. The majority of those are early-round losers in small events, women who didn’t seriously pursue tennis. But where I had a full name, I did at least a cursory search for each one, turning up a noted Spanglish poet, the “first grunter,” a squash Hall of Famer, and Marat Safin’s mom.

100 events sounded like a lot until I started working on 1966. I have a provisional list of 160 tournaments to include from that year. Even with all those caveats on the meanings of “finished” and “complete,” this is going to take a while.

Diving in

Here are direct links to 1967 results for a few players:

If you go to the main page for one of those players (for example, here’s Peaches Bartkowicz), you’ll find a cool addition that all the new 60s and 70s data has made possible: women’s Elo ratings back to the end of 1967. Player pages for women who played at least 20 matches in a season include their year-end ratings and rankings, including surface-specific figures.

Here is a very provisional overall top 10 for year-end 1967:

Rank  Player               Elo  
1     Billie Jean King  2221.3  
2     Virginia Wade     2114.9  
3     Nancy Richey      2113.2  
4     Judy Dalton       2083.3  
5     Ann Jones         2042.7  
6     Lesley Bowrey     2018.8  
7     Kerry Reid        2006.0  
8     Francoise Durr    2005.4  
9     Rosie Casals      1940.4  
10    Annette Du Plooy  1926.8

I say provisional because there’s so much left to add. (You know, the entire history of tennis prior to 1967.) At the moment, the algorithm doesn’t know anything about any of the players prior to January 1st, 1967. As it learns more, each player’s rating will be different at that point, and the year-end results will be tweaked as well. That goes for all Elo ratings and rankings throughout the 60s and 70s. The broad strokes will remain constant, but the exact numbers will change, and sometimes players will swap positions. As I add more data, King, Court, and Richey (among others) keep creeping up the all-time list.

As for the project as a whole, I have no idea how far I’ll get. While fascinating, it’s a time-consuming project, and the further into history we go, the less information is available on players beyond the all-time greats. Still, every small step back in time improves the accessibility of this period of women’s tennis data, which includes some of the most important players in the history of the sport.

About those sources

I’ve mentioned tennisforum’s Blast From the Past, which is truly essential. Another exhaustive source for match results starting 1968 is John Dolan’s book, Women’s Tennis 1968-84. Wikipedia has oddly spotty coverage: the Italian Wikipedia is good for tournament data, while the French Wikipedia seems to cover more players. (For Swedish players, Swedish Wikipedia is awesome. All that time spent learning Norwegian is finally paying off.) English Wikipedia is disappointingly lacking in comparison.

Who’s the GOAT? Balancing Career and Peak Greatness With Elo Ratings

On this week’s podcast, Carl, Jeff and I briefly discussed where Caroline Wozniacki ranks among Open-era greats. She’s among the top ten measured by weeks at the top of the rankings, but she has won only a single major. By Jeff’s Championship Shares metric, she’s barely in the top 30.

I posed the same question on Twitter, and the hive mind cautiously placed her outside the top 20:

https://twitter.com/tennisabstract/status/1214491560026484737

It’s difficult to compare different sorts of accomplishments–such as weeks at number one, majors won, and other titles–even without trying to adjust for different eras. It’s also challenging to measure different types of careers against each other. For more than a decade, Wozniacki has been a consistent threat near the top of the game, while other players who won more slams did so in a much shorter burst of elite-level play.

Elo to the rescue

How good must a player be before she is considered “great?” I don’t expect everyone to agree on this question, and as we’ll see, a precise consensus isn’t necessary. If we take a look at the current Elo ratings, a very convenient round number presents itself. Seven players rate higher than 2000: Ashleigh Barty, Naomi Osaka, Bianca Andreescu, Simona Halep, Karolina Pliskova, Elina Svitolina, and Petra Kvitova. Aryna Sabalenka just misses.

Another 25 active players have reached an Elo rating of at least 2000 at their peak, from all-time greats such as Serena Williams and Venus Williams down to others who had brief, great-ish spells, such as Alize Cornet and Anastasia Pavlyuchenkova. Since 1977, 88 women finished at least one season with an Elo rating of 2000 or higher, and 60 of them did so at least twice.

(I’m using 1977 because of limitations in the data. I don’t have complete match results–or anything close!–for the early and mid 1970s. Unfortunately, that means we’ll underrate some players who began their careers before 1977, such as Chris Evert, and we’ll severely undervalue the greats of the prior decade, such as Billie Jean King and Margaret Court.)

The resulting list of 60 includes anyone you might consider an elite player from the last 45 years, along with the usual dose of surprises. (Remember Irina Spirlea?) I’ll trot out the full list in a bit.

Measuring magnitude

A year-end Elo rating of 2000 is an impressive achievement. But among greats, that number is a mere qualifying standard. Serena has had years above 2400, and Steffi Graf once cleared the 2500 mark. For each season, we’ll convert the year-end Elo into a “greatness quotient” that is simply the difference between the year-end Elo and our threshold of 2000. Barty finished her 2019 season with a rating of 2123, so her greatness quotient (GQ) is 123.

(Yes, I know it isn’t a quotient. “Greatness difference” doesn’t quite have the same ring.)

To measure a player’s greatness over the course of her career, we simply find the greatness quotient for each season which she finished above 2000, and add them together. For Serena, that means a whopping 20 single-season quotients. Wozniacki had nine such seasons, and so far, Barty has two. I’ll have more to say shortly about why I like this approach and what the numbers are telling us.

First, let’s look at the rankings. I’ve shown every player with at least two qualifying seasons. “Seasons” is the number of years with year-end Elos of 2000 or better, and “Peak” is the highest year-end Elo the player achieved:

Rank  Player                     Seasons  Peak    GQ  
1     Steffi Graf                     14  2505  4784  
2     Serena Williams                 20  2448  4569  
3     Martina Navratilova             17  2442  4285  
4     Venus Williams                  14  2394  2888  
5     Chris Evert                     14  2293  2878  
6     Lindsay Davenport               12  2353  2744  
7     Monica Seles                    11  2462  2396  
8     Maria Sharapova                 13  2287  2280  
9     Justine Henin                    9  2411  2237  
10    Martina Hingis                   8  2366  1932  
11    Kim Clijsters                    9  2366  1754  
12    Gabriela Sabatini                9  2271  1560  
13    Arantxa Sanchez Vicario         12  2314  1556  
14    Amelie Mauresmo                  6  2279  1113  
15    Victoria Azarenka                9  2261  1082  
16    Jennifer Capriati                8  2214   929  
17    Jana Novotna                     9  2189   848  
18    Conchita Martinez               11  2191   836  
19    Caroline Wozniacki               9  2189   674  
20    Tracy Austin                     5  2214   647  
                                                      
Rank  Player                     Seasons  Peak    GQ  
21    Mary Pierce                      8  2161   637  
22    Elena Dementieva                 9  2140   629  
23    Simona Halep                     7  2108   562  
24    Svetlana Kuznetsova              6  2136   543  
25    Hana Mandlikova                  6  2160   516  
26    Jelena Jankovic                  4  2178   450  
27    Pam Shriver                      5  2160   431  
28    Vera Zvonareva                   5  2117   414  
29    Agnieszka Radwanska              8  2106   399  
30    Ana Ivanovic                     5  2133   393  
31    Petra Kvitova                    6  2132   346  
32    Na Li                            4  2095   310  
33    Anastasia Myskina                4  2164   290  
34    Anke Huber                       6  2072   277  
35    Mary Joe Fernandez               4  2110   274  
36    Nadia Petrova                    6  2094   265  
37    Dinara Safina                    3  2132   240  
38    Andrea Jaeger                    4  2087   237  
39    Angelique Kerber                 4  2109   224  
40    Nicole Vaidisova                 3  2121   222  
                                                      
Rank  Player                     Seasons  Peak    GQ  
41    Manuela Maleeva Fragniere        6  2059   194  
42    Anna Chakvetadze                 2  2107   174  
43    Ashleigh Barty                   2  2123   162  
44    Helena Sukova                    3  2078   150  
45    Jelena Dokic                     2  2110   142  
46    Iva Majoli                       2  2067   119  
47    Elina Svitolina                  3  2052   108  
48    Garbine Muguruza                 2  2061    98  
49    Zina Garrison                    2  2065    96  
50    Samantha Stosur                  3  2061    92  
51    Daniela Hantuchova               2  2050    80  
52    Irina Spirlea                    2  2064    76  
53    Nathalie Tauziat                 3  2041    73  
54    Patty Schnyder                   2  2057    70  
55    Chanda Rubin                     3  2034    68  
56    Marion Bartoli                   2  2033    66  
57    Sandrine Testud                  2  2041    62  
58    Magdalena Maleeva                2  2024    41  
59    Karolina Pliskova                2  2028    37  
60    Dominika Cibulkova               2  2007     7

You’ll probably find fault with some of the ordering here. While it isn’t the exact list I’d construct, either, my first reaction is that this is an extremely solid result for such a simple algorithm. In general, the players with long peaks are near the top–but only because they were so good for much of that time. A long peak, like that of Conchita Martinez, isn’t an automatic ticket into the top ten.

From the opposite perspective, this method gives plenty of respect to women who were extremely good for shorter periods of time. Both Amelie Mauresmo and Tracy Austin crack the top 20 with six or fewer qualifying seasons, while others with as many years with an Elo of 2000 or higher, such as Manuela Maleeva Fragniere, find themselves much lower on the list.

Steffi, Serena, and the threshold

It’s worth thinking about what exactly the Elo rating threshold of 2000 means. At the simplest level, we’re drawing a line, below which we don’t consider a player at all. (Sorry, Aryna, your time will come!) Less obviously, we’re defining how great seasons compare to one another.

For instance, we’ve seen that Barty’s 2019 GQ was 123. Graf’s 1989 season, with a year-end Elo rating of 2505, gave her a GQ of 505. Our threshold choice of 2000 implies that Graf’s peak season has approximately four times the value of Barty’s. That’s not a natural law. If we changed the threshold to 1900, Barty’s GQ would be 223, compared to Graf’s best of 605. As a result, Steffi’s season is only worth about three times as much.

The lower the threshold, the more value we give to longevity and the less value we give to truly outstanding seasons. If we lower the threshold to 1950, Steffi and Serena swap places at the top of the list. (Either way, it’s close.) Even though Williams had one of the highest peaks in tennis history, it’s her longevity that truly sets her apart.

I don’t want to get hung up on whether Serena or Steffi should be at the top of this list–it’s not a precise measurement, so as far as I’m concerned, it’s basically a tie. (And that’s without even raising the issue of era differences.) I also don’t want to tweak the parameters just to get a result or two to look different.

Ranking Woz

I began this post with a question about Caroline Wozniacki. As we’ve seen, greatness quotient places her 19th among players since 1977–almost exactly halfway between her position on the weeks-at-number-one list and her standing on the title-oriented Championship Shares table.

If we had better data for the first decade of the Open era, Wozniacki and many others would see their rankings fall by at least a few spots. King, Court, and Evonne Goolagong Cawley would knock her into the 20s. Virginia Wade might claim a slot in the top 20 as well. We can quibble about the exact result, but we’ve nailed down a plausible range for the 2018 Australian Open champion.

One-number solutions like this aren’t perfect, in part because they depend on assumptions like the Elo threshold discussed above. Just because they give us authoritative-looking lists doesn’t mean they are the final word.

On the other hand, they offer an enormous benefit, allowing us to get around the unresolvable minor debates about the level of competition when she reached number one, the luck of the draw at grand slams she won and lost, the impact of her scheduling on ranking, and so on. By building a rating based on every opponent and match result, Elo incorporates all this data. When ranking all-time greats, many fans already rely too much on one single number: the career slam count. Greatness quotient is a whole lot better than that.

WTA Decisions From the Backhand Corner

Earlier this week I presented a lot of data about what happens when men face a makeable ball hit to their backhand corner. That post was itself a follow-up on a previous look at what happened when players of both genders attempted down-the-line backhands. You don’t need to read those two articles to know what’s going on in this one, but if you’re interested in the topic, you’ll probably find them worthwhile.

Decision-making in the backhand corner is one of the biggest differences between pro men and women. Let me illustrate in the nerdiest way possible, with bug reports from the code I wrote to assemble these numbers. My first stab at the code to aggregate player-by-player numbers for men failed because some men never hit a topspin backhand from the backhand corner. At least, not in any match recorded by the Match Charting Project. The offending player who generated those divide-by-zero errors was Sam Groth. In his handful of charted matches, he relied entirely on the slice, at least in those rare cases where rallies extended beyond the return of serve.

Compare with the bug that slowed me down in preparing this post. The problematic player this time was Evgeniya Rodina. In nine charted matches, she has yet to hit a forehand from the backhand corner. If your backhand is the better shot, why would you run around it? Of the nearly 200 players with five charted matches from the 2010s, Rodina is the only one with zero forehands. But she isn’t really an outlier. 23 other women hit fewer than 10 forehands in all of their charted matches, including Timea Bacsinszky, who opted for the forehand only four times in 32 matches.

Faced with a makeable ball in the backhand corner, men and women both hit a non-slice groundstroke about four-fifths of the time. But of those topspin and flat strokes, women stick with the backhand 94% of the time, compared to 82% for men.

A few WTA players seek out opportunities to run around their backhands, including Sam Stosur and Polona Hercog, both of whom hit the forehand 20% of the time they are pushed into the backhand corner. Ashleigh Barty also displays more Federer-like tactics than most of her peers, using the forehand 13% of the time. Yet most of the women with powerful forehands, like Serena Williams, have equal or better backhands, making it counter-productive to run around the shot. Serena hits a forehand only 1% of the time her opponent sends a makeable ball into her backhand corner.

Directional decisions

Backhand or forehand, let’s start by looking at which specific shot that players chose. The Match Charting Project contains shot-by-shot logs of about 2,900 women’s matches from the 2010s, including 365,000 makeable balls hit to one player’s backhand corner. (“Makeable” is defined as a ball that either came back or resulted in an unforced error.)

Here is the frequency with which players hit backhand and forehands in different directions from their backhand corner. I’ve included the ATP numbers for comparison:

BH Direction               WTA Freq  ATP Freq  
Down the line                 17.4%     17.4%  
Down the middle               35.2%     29.5%  
Cross-court                   47.3%     52.9%  
                                               
FH Direction               WTA Freq  ATP Freq  
Down the line (inside-in)     35.2%     35.1%  
Down the middle               16.2%     12.8%  
Cross-court (inside-out)      48.4%     51.8%

Once a forehand or backhand is chosen, there isn’t much difference between men and women. Women go up the middle a bit more often, which may partly be a function of using the topspin or flat backhand in defensive positions slightly more than men do. I’ve also observed that today’s top women are more likely to hit an aggressive shot down the middle than men are. The level of aggression and risk may be similar to that of a bullet aimed at a corner, but when we classify by direction, it looks a bit more conservative. That’s just a theory, however, so we’ll have to test that another day.

Point probability

Things get more interesting when we look at how these choices affect the likelihood of winning the point. On average, a woman faced with a makeable ball in her backhand corner has a 47.2% chance of winning the point. (For men, it’s 47.7%.) The serve has some effect on the potency those shots toward the backhand corner. If the makeable ball was a service return–presumably weaker than the average groundstroke–the probability of winning the point is 48.2%. If the makeable ball is one shot later, an often-aggressive “serve-plus-one” shot, the chances of fighting back and winning the point are only 46.3%. It’s not a huge difference, but it is a reminder that the context of any given shot can affect these probabilities.

The various decisions available to players each have their own effect on the probability of winning the point, at least on average. If a woman chooses to hit a down-the-line backhand, her likelihood of winning the point increases to 53.0%. If she makes that shot, her odds rise to 68.4%.

The following table shows those probabilities for every decision. The first column of percentages, “Post-Shot,” indicates the likelihood of winning after making the decision–the 53.0% I just mentioned. The second column, “In-Play,” is the chance of winning if she makes that shot, like 68.4% for the down-the-line backhand.

Shot      Direction  Post-Shot  In-Play  
Backhand  (all)          48.5%    55.2%  
Backhand  DTL            53.0%    68.4%  
Backhand  Middle         44.6%    48.8%  
Backhand  XC             49.9%    55.8%  
                                         
Forehand  (all)          56.3%    56.1%  
Forehand  DTL (I-I)      61.4%    73.7%  
Forehand  Middle         45.7%    50.3%  
Forehand  XC (I-O)       56.2%    64.4%

The down-the-line shots are risky, so the gap between the two probabilities is a big one. There is little difference between Post-Shot and In-Play for down-the-middle shots, because they almost always go in. For the forehand probabilities, keep in mind that they are skewed by the selection of players who choose to use their forehands more often. Your mileage may vary, especially if you play like Rodina does.

Cautious recommendations

Looking at this table, you might wonder why a player would ever make certain shot selections. The likelihood of winning the point before choosing a wing or direction is 47.2%, so why go with a backhand down the middle (44.6%) when you could hit an inside-in forehand (61.4%)? It’s not the risk of missing, because that’s baked into the numbers.

One obvious reason is that it isn’t always possible to hit the most rewarding shot. Even the most aggressive men run around only about one-quarter of their backhands, suggesting that it would be impractical to hit a forehand on the remaining three-quarters of opportunities. That wipes out half of the choices I’ve listed. And even a backhand wizard such as Simona Halep can’t hit lasers down the line at will. The probabilities reflect what happened when players thought the shot was the best option available to them. Even though were occasionally wrong, this is very, very far from a randomized controlled trial in which a scientist told players to hit a down-the-line backhand no matter what the nature of the incoming shot.

Another complication is one that I’ve already mentioned: The success rates for rarer shots, like inside-in forehands, reflect how things turned out for players who chose to hit them. That is, for players who consider them to be weapons. It might be amusing to watch Monica Niculescu hit inside-out topspin forehands at every opportunity, but it almost certainly wouldn’t improve her chances of winning. You only get those rosy forehand numbers if you can hit a forehand like Stosur does.

That said, the table does drive home the point that conservative shot selection has an effect on the probability of winning points. Some women are happy sending backhand after backhand up the middle of the court, and sometimes that’s all you can do. But when more options are available, the riskier choices can be more rewarding.

Player probabilities

Let’s wrap up for today by taking a player-by-player look at these numbers. We established that the average player has a 47.2% chance of winning the point when a makeable shot is arcing toward her backhand corner. Even though Tsvetana Pironkova’s number is also 47.2%, no player is average. Here are the top 14 players–minimum ten charted matches, ranked by the probability of winning a point from that position. I’ve also included the frequency with which they hit non-slice backhands:

Player                     Post-Shot  BH Freq  
Kim Clijsters                  53.4%    77.6%  
Na Li                          53.2%    87.5%  
Camila Giorgi                  52.9%    93.8%  
Patricia Maria Tig             52.1%    66.1%  
Simona Halep                   52.1%    83.6%  
Belinda Bencic                 51.5%    91.7%  
Dominika Cibulkova             51.3%    70.1%  
Veronika Kudermetova           50.9%    73.9%  
Jessica Pegula                 50.7%    73.7%  
Su-Wei Hsieh                   50.6%    81.8%  
Dayana Yastremska              50.6%    87.6%  
Anna Karolina Schmiedlova      50.3%    87.4%  
Serena Williams                49.9%    89.2%  
Sara Errani                    49.8%    70.0%

These numbers are from the 2010s only, so they don’t encompass the entire careers of the top two players on the list, Kim Clijsters and Li Na. It is particularly impressive that they make the cut, because their charted matches are not a random sample–they heavily tilt toward high-profile clashes against top opponents. The remainder of the list is a mixed bag of elites and journeywomen, backhand bashers and crafty strategists.

Next are the players with the best chances of winning the point after hitting a forehand from the backhand corner. I’ve drawn the line at 100 charted forehands, a minimum that limits our pool to about 50 players:

Player                Post-Shot  FH Freq  
Maria Sharapova           69.0%     4.1%  
Dominika Cibulkova        65.1%    10.5%  
Ana Ivanovic              64.7%    11.1%  
Yafan Wang                64.4%     8.8%  
Rebecca Peterson          63.4%    15.2%  
Simona Halep              63.1%     6.8%  
Carla Suarez Navarro      63.0%     7.7%  
Andrea Petkovic           62.3%     5.3%  
Christina McHale          61.9%    15.2%  
Anastasija Sevastova      61.3%     4.2%  
Petra Kvitova             60.8%     4.6%  
Caroline Garcia           60.7%     7.5%  
Misaki Doi                60.5%    17.0%  
Madison Keys              59.3%     9.3%  
Elina Svitolina           59.1%     3.9%

Maria Sharapova is the Gilles Simon of the WTA. (Now there’s a sentence I never thought I’d write!) Both players usually opt for the backhand, but are extremely effective when they go for the forehand. Kudos to Sharapova for her well-judged attacks, though it could be that she’s leaving some points on the table by not running around her backhand more often.

Next

As I wrote on Thursday, we’re still just scratching the surface of what can be done with Match Charting Project data to analyze tactics such as this one. A particular area of interest is to break down backhand-corner opportunities (or chances anywhere on the court) even further. The average point probability of 47.2% surely does not hold if we look at makeable balls that started life as, say, inside-out forehands. If some players are facing more tough chances, we should view those numbers differently.

If you’ve gotten this far, you must be interested. The Match Charting Project has accumulated shot-by-shot logs of nearly 7,000 matches. It’s a huge number, but we could always use more. Many up and coming players have only a few matches charted, and many interesting matches of the past (like most of those played by Li and Clijsters!) remain unlogged. You can help, and if you like watching and analyzing tennis, you should.

There’s Always a Chance: Marie Bouzkova Edition

Last night in Toronto, 91st-ranked qualifier Marie Bouzkova won her quarter-final match against 4th-ranked Simona Halep. Halep retired with a leg injury after losing the first set, so there’s a caveat–even if we were prepared to read too much into a single match, we wouldn’t attribute a lot of meaning to this one. But it’s a big accomplishment for the 21-year-old Czech, who earned her second top-ten scalp of the week and will advance to her first Premier-level semi-final, against no less of an obstacle than Serena Williams.

Here’s the nutty thing: It was Bouzkova’s 62nd match of the 2019 season, her 61st against someone with a WTA ranking. She got the win against the highest-ranked foe–Halep–but just last week, she lost to 636th-ranked CoCo Vandeweghe, her lowest-ranked opponent of the year. Yeah, the caveats keep coming: Vandeweghe is coming back from injury and is surely better than a ranking outside the top 600, and the ITF Transition Tour hijinks mean that the ranking system didn’t work as usual in 2019. Some players who would normally have a very low ranking, like the Kazakh wild card who Bouzkova crushed a couple of weeks ago, don’t count.

Still. 61 matches, with a win against the highest-ranked player and a loss against the lowest.

That sent me to my database, which had plenty more surprises in store. Going back less than a decade, to 2010, I found 127 players who recorded the same oddball combination of feats in a single season, minimum 30 matches. (To be consistent with the Halep result, I included retirements if at least one set was completed.) While many of the players won’t be of wide interest–last year, one of the exemplars was Mira Antonitsch, who didn’t play anyone ranked in the top 400–63 of the 127 player-seasons involved beating a top-100 opponent, 44 included the defeat of someone in the top 50, and 25 were highlighted by a top-ten upset.

Three of them included Halep as the top-ten scalp! That makes Bouzkova the fourth player to beat Halep, not face anyone higher ranked, and also lose to her lowest-ranked opponent of the season. (Through eight months, anyway.) Halep shouldn’t feel too bad, though, as Angelique Kerber has been the extreme-ranked loser in five such cases, four of them in 2017. Ouch.

Here are the 25 player-seasons between 2010 and 2018 in which a WTAer beat her highest-ranked opponent and lost to her lowest:

Year  Player       High-Ranked  Rk  Low-Ranked  Rk       
2017  Kasatkina    Kerber       1   Kanepi      418      
2018  Hsieh        Halep        1   Gasparyan   410      
2010  Jankovic     Serena       1   Diyas       268      
2010  Clijsters    Wozniacki    1   G-Vidagany  258   *  
2014  Cornet       Serena       1   Townsend    205      
2010  Yakimova     Jankovic     2   Dellacqua   980      
2017  Bouchard     Kerber       2   Duval       896   *  
2017  Vesnina      Kerber       2   Azarenka    683      
2016  Bencic       Kerber       2   Boserup     225      
2014  Rybarikova   Halep        2   Eguchi      183      
2017  Mladenovic   Kerber       2   Andreescu   167   *  
2018  Goerges      Wozniacki    3   Serena      451      
2014  Tomljanovic  Radwanska    3   A Bogdan    308      
2015  Mladenovic   Halep        3   Savchuk     262      
2017  Kerber       Pliskova     4   Stephens    934      
2014  Pavlyu'ova   Radwanska    4   Wozniak     241      
2017  Dodin        Cibulkova    5   Rybarikova  453      
2017  Bellis       Radwanska    6   Azarenka    683      
2018  Buyukakcay   Ostapenko    6   Di Sarra    555      
2017  Sakkari      Wozniacki    6   Potapova    454      
2015  L Davis      Bouchard     7   E Bogdan    527      
2015  Ostapenko    S-Navarro    9   Dushevina   1100  *  
2016  KC Chang     Vinci        10  S Murray    862      
2018  Pera         Konta        10  Hlavackova  825      
2018  Danilovic    Goerges      10  Pegula      620

* also faced one unranked player

A quick glance is all it takes to establish that Vandeweghe isn’t the first lowest-ranked player to inspire a “yeah, but” reaction. The list of purportedly weak opponents is very strong for one made up of players with an average ranking outside of the top 500. We have stars such as Victoria Azarenka (twice) and Serena as well as a helping of prospects such as Bianca Andreescu and Victoria Duval.

Consider this as today’s reminder of the limitations of the WTA computer rankings. They tell us who has won a lot of matches in the last 52 weeks, not necessarily who is playing well right now. These cases include many of the most extreme mismatches between official ranking and on-the-day ability. I don’t think it says anything meaningful about a player to show up on this list–though Kerber’s many appearances (as both player and scalp!) are a good summary of her disappointing 2017 campaign.

Bouzkova will remain on the list for at least a couple more days: Serena is currently ranked 10th and both of the other semi-finalists are ranked lower, so Halep will remain her “toughest” opponent. Despite the Czech’s breakout week, it would be understandable if she found herself overawed to face a 23-time slam champion across the net. But one thing is certain: Bouzkova couldn’t care less about the number next to the name.

The Effect of Serena’s Serve Speed

Italian translation at settesei.it

Yesterday at FiveThirtyEight, Tom Perrotta highlighted the relationship between Serena Williams’s first serve performance and her chances of winning. According to the article, Serena has won only (“only”) 74% of her first serve points over the fortnight, compared to an outlandish 87.5% when she won the title in 2010. She has never won Wimbledon while winning fewer than 75% of her first-serve points, and even the three-quarters mark is no guarantee, as she topped 77% last year en route to a second-place finish.

A lot of factors go into first-serve winning percentage, including serve placement, serve tactics, and all the shots that a player hits when the return comes back. The most obvious, though, is another category in which Serena has often topped the charts: serve speed. When Williams beat Garbine Muguruza to win the Championships in 2015, her average first serve clocked in at 113 miles per hour, the third straight match in which her typical first delivery topped 111 mph. Over her last 13 matches, she has averaged only (“only”) 106.4 mph, never exceeding 109 mph in a single contest.

How much does it matter?

It seems fair to assume that, all else equal, a faster serve is more effective than a slower one. Complicating things is the fact that all else is rarely equal: wide serves are often deadly despite requiring less raw power, more conservative serves can be easier to place, andwe haven’t even scratched the surface of the effect of spin. A faster serve isn’t always better than a slower one. But on average, the basic assumption holds true.

For each of Serena’s 23 matches at Wimbledon 2014, 2015, 2018, and 2019 (she didn’t play in 2017, and I don’t have the relevant data at hand for 2016–don’t ask), I split her first serve points into quintiles, ranked from fastest serves to slowest serves. This is a crude way of controlling for the effects of different opponents and giving us an initial sense of how much Serena’s serve speed influences the outcome of first-serve points:

Quintile     1SP W%  Avg MPH  
Fastest       80.6%    116.9  
2nd fastest   73.7%    112.2  
Middle        79.5%    108.0  
2nd slowest   73.7%    103.7  
Slowest       74.9%     98.1

Clearly, serve speed doesn’t tell the whole story. At the same time, it looks like a 117 mph serve–or even a 108 mph one–is a better bet than a 98 mph offering.

Another way to isolate the effect of serve speed is to ignore the influence of specific opponents and simply sort first serves by miles per hour. From these 23 matches, we have 43 first serves recorded at exactly 100 mph, with a corresponding winning percentage of 72.1%. Serena hit 33 first serves at 101 mph, of which she won 72.7%. While the winning percentages don’t usually move so neatly in lockstep with first serve speed, there is a general trend:

The correlation is a loose one: winning percentages at 99 mph and 103 mph are better than those at 116 mph and 117 mph, for example. We could attribute that to the possibility that the slower serves are tactically savvier, or more approximate placement of the faster deliveries, or just dumb luck, because our sample size at any specific speed isn’t that great. Still, we can draw an approximate conclusion:

Each additional two miles per hour of first-serve speed is worth an additional one percentage point to Serena’s 1st serve winning percentage.

To take it one step further: Serena usually lands about 60% of her first serves, and roughly half of total points will be on her serve, so each additional two miles per hour of first-serve speed is worth an additional 0.6 percentage points of total points won. In a close match, like her 2014 loss to Alize Cornet–in which she averaged only 104 mph on her first serves and won exactly 50% of the points played–that could be the difference.

Serena in context

The same general rule cannot be applied to all women. (Several years ago, I took a similar look at ATP serve speeds, and–perhaps foolishly–I didn’t break it down by player.) I ran the same algorithm on the recent Wimbledon records of the nine other women for whom I have at least 15 matches worth of data. The effect of serve speed varies from “quite a bit” for Johanna Konta to “not at all” for Venus Williams and “I don’t understand the question” for Caroline Wozniacki.

The following table shows two numbers for each player. The “Addl MPH =” column shows the effect of one additional mile per hour on first serve winning percentage, and the “_ MPH = 1% SPW” column shows how many additional miles per hour are required to increase first serve winning percentage by one percentage point:

Player               Addl MPH =  MPH = 1% SPW  
Johanna Konta             0.89%           1.1  
Angelique Kerber          0.56%           1.8  
Serena Williams           0.48%           2.1  
Garbine Muguruza          0.47%           2.1  
Simona Halep              0.41%           2.5  
Petra Kvitova             0.29%           3.5  
Agnieszka Radwanska       0.28%           3.6  
Victoria Azarenka         0.02%          50.9  
Venus Williams            0.00%             -  
Caroline Wozniacki       -0.40%             - 

Konta’s serve speed is almost twice as important to her first-serve success as Serena’s is. Her average first-serve speed in her quarter-final loss to Barbora Strycova was 99.9 mph, her lowest at Wimbledon since a first-round loss in 2014.

At the opposite extreme, we have Victoria Azarenka and Venus, for whom serve speed doesn’t seem to matter. (Venus, for one, excels at the deadly wide serve, which she converts into aces regardless of speed.) Wozniacki apparently lulls her opponents into confusion and illogic, giving her better results on slower first serves.

Serena vs Simona

These are small effects, so even the range between Serena’s slowest serving performance this fortnight (105 mph first serves against Carla Suarez Navarro) and the 2015 final against Muguruza would only have effect Serena’s total points won by about 2.5 percentage points. Nine out of ten times Williams and Halep have gone head to head, Serena has come out on top, always with more than 52.5% of total points, usually with more than 55%. That’s an ample margin of error–or, more precisely, margin of slow serving.

On the other hand, the most recent Serena-Simona contest, the only time they’ve played since 2016, was the closest of the lot. Halep is a great returner, but she is not immune to powerful serving: her rate of return points won is affected by serve speed just as much as Williams’s serve stats are. The gap between the finalists could be narrow, and Serena’s serve speed is one of the few tools completely in her own power that she could deploy to tilt the scales in her favor.

How Good is Cori Gauff Right Now?

Italian translation at settesei.it

15-year-old sensation Cori Gauff holds a WTA ranking of No. 313. She has played only a limited number of events that are considered by the WTA’s system, so even before her impressive run began, we could’ve predicted that her ranking was an understatement. But by how much?

Gauff doesn’t show up yet on my Elo ratings list because, before Wimbledon qualies, she hadn’t played at least 20 matches at the ITF $50K level or higher in the last year. However, she still had a rating: 1,488, good for 194th place among those who had met the playing time minimum. A rating in that range translates to about a 3% chance of upsetting current top-ranked player Ashleigh Barty, and a 10% chance of beating someone around 20th, such as Donna Vekic. Given how little data we had to work with at that point, that seemed like a reasonable assessment.

Since she arrived in London, she has won six matches: Three in qualifying and three in the main draw, with wins over Venus Williams, Magdalena Rybarikova, and Polona Hercog. Not bad for a teenager who had previous won only one slam qualifying match and one tour-level main draw match in her young career!

194th place doesn’t seem like such a fair judgment anymore. Any player who comes through qualifying and reaches the fourth round at a major deserves some reassessment, and that’s even more applicable to a player about whom we knew so little two weeks ago. The tricky part is figuring out how much to adjust. Is Gauff now a top-100 player? Top 50? Top 20?

Revising with Elo

The Elo algorithm does a good job of approximating how humans make those reassessments: The more data we already have about a player, the less we will adjust her rating after a win or loss. The previous player to defeat Hercog was Simona Halep, at Eastbourne. We already have years’ worth of match results for Halep, and she was heavily favored to win the match. Thus, the fact that she recorded the victory alters our opinion of her by only a small amount. In Elo terms, it was an increase from 2,100 points to 2,102–basically nothing.

Gauff is a different story. Entering her third-round clash with Hercog, not only did we know very little about her skill level, it wasn’t even clear if she was the favorite. The result caused Elo to make a considerably larger adjustment, increasing her rating from 1,713 to 1,755, a rise 21 times greater than what Halep received after beating the same opponent. The 42-point jump caused her to leapfrog 16 players in the rankings.

Here is Gauff’s Elo progression, from the moment she arrived at Wimbledon to middle Sunday. After each match, I show her overall Elo (the numbers I’ve been discussing so far), her grass-specific Elo, and her grass-weighted Elo, a 50/50 blend of overall and grass-specific that is used for forecasting. For each of the three ratings, I also show her ranking among WTA players with at least 20 matches in the last 52 weeks.

Match          Overall   Rk  Grass   Rk  Weighted   Rk  
Pre-Wimbledon     1488  194   1350  163      1419  187  
d. Bolsova        1540  171   1405  132      1473  155  
d. Ivakhnenko     1566  157   1447  107      1507  131  
d. Minnen         1614  132   1514   57      1564   95  
d. Venus          1670  108   1578   40      1624   73  
d. Rybarikova     1713   83   1650   21      1682   41  
d. Hercog         1755   67   1686   17      1721   31

Over the course of only six matches, Gauff has jumped from 194th in the overall Elo rankings to 67th. For forecasting purposes, her grass court rating has soared from 187th to 31st. Her current weighted rating of 1,721 is better than that of three other women in the round of 16: Karolina Muchova, Carla Suarez Navarro, and Shuai Zhang. She trails another surviving player, Elise Mertens, by only 20 points.

So you’re telling me there’s a chance

Unfortunately, none of those relatively weak grass-court players are Gauff’s next opponent. Instead, the 15-year-old will face Halep, the third-best remaining player (behind Barty and Karolina Pliskova), and a three-time quarter-finalist at the All England Club. Halep’s weighted Elo rating is 229 points higher than Gauff’s, implying that the veteran has a 79% chance of winning on Monday. The betting market concurs, suggesting that the probability of a Halep victory is about 80%.

It doesn’t usually have much of an effect on forecasts to update Elo ratings throughout a tournament. While anyone reaching the 4th round has a higher rating than they did before the event, the differences are typically small. And since forecasts are based on the difference between the ratings of two players, the forecast isn’t affected if both players’ ratings have increased by roughly the same amount.

As a teenager with such limited match experience, Gauff breaks the mold. Her pre-Wimbledon 1,488 Elo rating is only two weeks old, and it is already completely unrepresentative of what we know of her skill level. She’ll have ample time to prove us right or wrong in the upcoming years, but for now, we have good reason to estimate that she belongs–even more than some of the older players who have reached the second week at Wimbledon.