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Does Serena do better in Grand Slams when she runs more? Watson Analytics breaks it down.

Blog Home > Does Serena do better in Grand Slams when she runs more? Watson Analytics breaks it down.

Does Serena do better in Grand Slams when she runs more? Watson Analytics breaks it down.

Hello tennis fans! Did you know that IBM is the official technology provider for each of the four Grand Slam tennis tournaments? We are and have been  for many years. This partnership allows us access to lots of tennis scoring and statistical data that we have been feeding into Watson Analytics to see what interesting insights we can gain about the matches and players. You may have even seen the recent television commercial featuring a conversation between Watson and Serena Williams.

Below are a couple of examples of explorations that Watson Analytics has helped us with using this data.

By using the number of points that each player had played along with player movement data collected at each of the four 2015 tournaments, we were able to utilize Watson Analytics to show comparisons between the average distance run per point for several of the top WTA (Woman’s Tennis Association) players. As you can see in the image below, Serena Williams’ average was 24.78 ft traveled per point over the 4 tournaments (close to the middle of this group of top players).

Serena 1

By allowing Watson Analytics to break down the same data by both tournament as well as player, we can see how each of these players stack up against one another at each of the individual tournaments.

serena 3

One thing that is interesting to note is that out of this group of top players, Serena Williams actually had the least number of feet traveled per point (23.7) at the 2015 US Open (the only one of the 4 that she didn’t win). Perhaps Serena does better when she runs more?

Serena 4

In another exploration, we have broken down the data into point types (pressure points vs. non-pressure points). Here we can see the number of Aces that Serena has hit in points of these types over the last 11 years. While we can see that she has hit more Aces in 2015 on all types of points, it is especially significant that she is hitting Aces on far more points defined as ‘pressure points’ than she has in any of the previous 10 years.

Serena 5

While these are just a few of the examples of the explorations that Watson Analytics has been able to help us with, we continue to feed new data into the system and it will be interesting to see what new insights we can gain into the world of professional tennis. Who knows? Maybe Watson Analytics will win the Grand Slam!

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