Match Charting Project: More Matches, More Data, New Spreadsheet

The Match Charting Project keeps growing, and starting today, even more of the data is available for anyone who wants it. Several new contributors have helped us pass the 750-match milestone, having added an average of two matches per day since I first published the raw data.

New spreadsheet

The Match Charting spreadsheet now does a lot more. As you chart each point, the document updates stats for the match–both total and set-by-set. You’ll find the same stats you see on television (aces, double faults, winners, unforced errors, etc) along with some that are a little less common, like winning percentage in different lengths of rallies, and most consecutive points won.

In other words, As you chart the match, you’ll have access to many of the same stats that commentators do. Here’s what it looks like:


If you’ve hesitated to try charting because you couldn’t see what was in it for you, I hope this changes the calculation a bit.

Click here to download MatchChart 0.1.4.

(If you prefer to use the lighter-weight version 0.1.2, that’s fine too.)

New data

About a month ago, I published the point-by-point data from all charted matches.  In raw form, it’s a bit daunting, and it’s more than what’s necessary for many interesting research projects.

Today, I added 15 different aggregate stats files for men, and another 15 for women. These contain the data that is shown in each charted match report. For instance, if you find it interesting that Simona Halep hit 14% of her backhands down the line in the Indian Wells final, you can take a look in the ShotDirection stats file and compare that number with the results from Halep’s other charted matches, or all matches in the database as a whole.

You can find these files (along with the updated raw data for 760+ matches) by clicking here.

Chart some matches

If you haven’t already, now is a great time to start charting professional matches and contributing to the project. An enormous number of matches are televised and streamed, and as the database of charted matches grows, there’s more and more useful context to all the data we’re generating.

You can start by jumping into the ‘Instructions’ tab of the new MatchChart spreadsheet, or for other tips, you can start with my blog post introducing the project.

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Free ATP and WTA Results and Stats Databases

The vast majority of my men’s and women’s tennis results and stats databases are now free for anyone who wants to use them.

ATP Results and Stats:

  • Tour-level results back to 1968, with tons of data on both players in each match (age, handedness, country, rank), and matchstats from 1991-present.
  • Almost a decade of tour-level qualifying matches, with matchstats for the last few years.
  • Challenger results back to 1991, with matchstats for almost the last ten years.
  • Futures (and Satellite) results back to 1991.
  • Linked biographical and rankings data (introduced here).

WTA Results:

  • Tour-level results back to 1968, with the same player data as in the ATP files.
  • Tour-level qualifying matches.
  • Over 220,000 ITF main-draw matches.

Click the links to access the files. Enjoy!


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Free ATP and WTA Ranking Databases

More data!

Today I’ve made available my entire ATP and WTA ranking databases through the end of the 2014 season. In addition, you’ll find my complete player tables, which include birthdate, country, and handedness for every player who has ever been ranked or played a tour-level match. (Plus thousands more players, who are included in the database for other reasons.)

This is all the data you need to research all sorts of topics, like the rise and fall of certain countries in the rankings and the changing age of top 10s, 50s, and 100s.

This is the third major dataset I’ve published this week, and more is on the way.

ATP rankings are here, and WTA rankings are here. Enjoy!


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Raw Data From The Match Charting Project

In the last year and a half, dozens of contributors and I have amassed detailed shot-by-shot records of nearly 700 professional matches. You can see the full list here, or a menu sorted by player here.

I refer to this as The Match Charting Project, and I hope you’ll consider contributing as well. Using a straightforward text notation system, we record shot type, shot direction,  return depth, error types, and more. The more matches, the more interesting the results. The project made up part of my presentation at the Sloan Sports Analytics Conference last month, which included some very preliminary findings on player tendencies.

Now, you can dig into the raw data yourself. I’ve posted all of the user-submitted match charts in one place, in a standardized format for anyone who wants to mess around with it.




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Point-by-Point Data From the Last 17 Grand Slams

I’ve been doing a lot of griping lately about the state of tennis data, so I figured now was a good time to start doing something about it.

I’ve just released point-by-point data for most Grand Slam singles matches back to 2011. Beyond the basic point sequence–which is valuable in and of itself–you’ll find serve speed, winner type, and for a few of the slams, rally length for each point.

More detailed notes on the data are available at that link. Enjoy, and if working with it turns up any interesting findings, please let me know.

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Sloan Conference Presentation on Tennis Analytics

Last weekend at the Sloan Sports Analytics Conference in Boston, I gave a talk, “First Service: The Advent of Actionable Tennis Analytics.” The presentation was in three parts:

  1. The sorry state of tennis data
  2. Schedule optimization (based in part on this blog post)
  3. The Match Charting Project (more about that in this post, among others)

The conference video-recorded all presentations, and I understand that video will be posted on the Sloan site. When it becomes available, I’ll post a link here.

In the meantime, many people have asked for my slide deck: First Service.

Also, Jim Pagels wrote a brief piece for Forbes drawing on my talk, which you can read here.

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Who Do You Love, Racket Ralliers?

Many of you probably know by now: Last week, Ben Rothenberg and I launched Racket Rally, a stock-market-style fantasy tennis game. We were overwhelmed by the initial response, getting well over 2,000 signups in only a few days before play began at the Australian Open. If you haven’t joined in yet, we’d still love to have you–you can start building the perfect portfolio for Indian Wells and beyond.

With so much user data, it’s interesting to see which players are most popular among Racket Rally members.

For the uninitiated, here’s how it works. Each member starts with a budget of $100,000. She can spend that money on shares of any player in the top 300 (along with a few injury-protected players), at prices equal to their ATP or WTA ranking points. Last week, Richard Gasquet had 1,350 ATP ranking points, so you could buy one share of Gasquet for $1,350, two shares for $2,700, and so on, up to a maximum of 50 shares or $40,000, whichever comes first.

Each week, sales are limited, so the perfect portfolio isn’t necessarily optimized for the Australian Open. Since users are stuck with many of their players from week to week, their choices reflect both short-term and long-term expectations.

The numbers

Before the Australian Open began, 1,739 members had purchased shares of at least three players–a reasonable cutoff to define active users who built portfolios. They bought over 63,000 shares of 375 different players, spending just short of 169,000,000 fake Racket Rally dollars.

The most popular player, by almost every measurement, was Novak Djokovic. More than half of users (992) bought at least one share of Novak, and the same is true of Roger Federer, who is to be found in 875 portfolios. Here’s the rest of the top ten:

Kei Nishikori      764  
Maria Sharapova    716  
Serena Williams    708  
Andy Murray        697  
Simona Halep       639  
Milos Raonic       571  
Karolina Pliskova  557  
Nick Kyrgios       517

Interesting mix, huh? Pliskova is the big surprise, and shows the savviness of at least 500 users. Since Pliskova reached the final in Sydney last week, her ranking has since gone up, meaning that members who purchased shares last week got her at a discount. Kyrgios is a more Melbourne-optimized choice, as it’s reasonable to expect Nick to perform well at his home slam.

When we switch our focus to shares purchased, many of the same names remain near the top, but the order changes quite a bit. Users bought 2,412 total shares of Kyrgios, most of any player in the game. Pliskova is right behind him, at 1,990. An unexpected name comes in third: 1,921 shares of Viktor Troicki were picked up, presumably by users who think he will return to something much closer to his pre-suspension form.

Here are the other 15 players who garnered enough interest for users to amass at least 1,000 shares each:

Andy Murray         1732  
Novak Djokovic      1723  
Roger Federer       1636  
Bernard Tomic       1563  
Kei Nishikori       1435  
Maria Sharapova     1366  
Borna Coric         1329  
Serena Williams     1292  
Venus Williams      1205  
Thanasi Kokkinakis  1173  
Simona Halep        1158  
Garbine Muguruza    1130  
Vasek Pospisil      1108  
Milos Raonic        1100  
David Goffin        1048

When we turn to total dollars invested–or, to look at it another way, percentage of portfolio allotted–top players take center stage. Djokovic, Federer, Serena, Sharapova, and Murray make up the top five, while Petra Kvitova and Rafael Nadal make their first appearance in a top ten.

The differences among dollars spent are enormous. Members spent nearly $20 million (more than 10% of in-game currency) on Djokovic, $16 million on Federer, and just over $10 million each on Serena and Sharapova.  10 players are over the $5 million mark, 22 over $2 million, and 30 over $1 million.

Plenty of notable players are another order of magnitude less–Bethanie Mattek-Sands, the best Racket Rally investment, as of this writing–is held in only 49 portfolios, for a total of $120,000. Carina Witthoeft, the unheralded German who has reached the third round, appears in only nine portfolios, for a total of $44,000. One lonely user took a chance on Evgeniya Rodina (5 shares for $2,375)–members spent more money on at least 20 players who aren’t even in the Melbourne main draw.

It may be that not every share purchase was based entirely on interest or potential. 76 players–most of them out of action this week–are held in only one portfolio. I suspect that the member who spent $146 on one share of Anastasia Grymalska had about $146 left in his or her portfolio when that choice was made.

In the near future, I’ll put together a page on the Racket Rally website to show all of this data on a weekly basis. It will also be fascinating to see what players are the most traded each week.

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