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# Visualizing the 2019 Men's Wimbledon Final
- URL: https://www.philsimon.com/visualizing-the-2019-mens-wimbledon-final/
- Published: 2019-08-08T12:25:12.000Z
- Updated: 2025-07-04T19:10:30.000Z
- Description: A look back at one of the most exciting matches in tennis history.
- Author: Phil Simon
- Tags: Dataviz, Code, Tableau, Tennis, Twitter

![](https://storage.ghost.io/c/8f/b5/8fb5e321-49a6-4cf5-8a28-c6f6d5417e54/content/images/2025/05/federer-novak-1.png)

At the gym yesterday, I did my normal Wednesday workout while catching glimpses of the 46th Annual Cherry Pit Spitting Championship on [ESPN The Ocho](https://ftw.usatoday.com/2019/08/espn-ocho-schedule-dodgeball-programming?ref=philsimon.com). (Yeah, that's a thing.) My eyes were one place but my mind was elsewhere. Specifically, I couldn't stop thinking about how I could represent in Tableau one of the five most exciting tennis matches I've ever seen: [the 2019 Men's Final between Djokovic and Federer](https://www.youtube.com/watch?v=TUikJi0Qhhw&ref=philsimon.com).

By way of background, early yesterday morning I engaged in some back-and-forth on Twitter with a few other dataviz enthusiasts. Those exchanges confirmed what I long suspected: It's just more fun to visualize sports data compared to generic business data.

Anyway, back to tennis. Here's what I came up with:

![](https://storage.ghost.io/c/8f/b5/8fb5e321-49a6-4cf5-8a28-c6f6d5417e54/content/images/2025/05/tennis-2.jpg)

See the interactive dataviz [here](https://public.tableau.com/views/Djokovicvs%5FFederer2019MensWimbledonFinal/Story1?:embed=y&:embed%5Fcode%5Fversion=3&:loadOrderID=0&:display%5Fcount=y&:origin=viz%5Fshare%5Flink&ref=philsimon.com).

No, I wouldn't put this dataviz on the same level as [this work of art](https://public.tableau.com/profile/akanksha.joshi4843?ref=philsimon.com#!/vizhome/TheWimbledon2019MensSinglesFinal-FederervDjokovic%5F15636781635490/TheWimbledon2019MensSinglesFinal-FederervDjokovic). Still, doing this exactly the way that I wanted wasn't as simple as dragging and dropping. ([Dual axes](https://kb.tableau.com/articles/howto/dual-axis-bar-chart-multiple-measures?ref=philsimon.com) are beautiful things.) It took some thought and problem-solving. To be sure, I certainly didn't have the chops to do this a year ago. On a different level, animations demonstrate how tight this each set was—save for the second.

What do you think? How would you improve upon this data visualization?