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May 2022 Monthly Challenge
- mrroweuk8
- May 2, 2022
- 1 min read
After 17 days at the Crucible Theatre, Sheffield we now know the winner of this years Snooker World Championship. Ronnie O'Sullivan was in a different league for most of the tournament and now equals Stephen Hendry's record of seven wins. This years tournament provided other notable and interesting events. The longest frame in the history of the tournament took place between Mark Selby and Yan Bingtao taking a staggering 85 minutes to complete!
We've also seen a pigeon make a presence in the theatre! For those not familiar with the story, check this out!
To celebrate this snooker fest we've pulled together data from the World Championship finals going back to the inaugural year of 1927. There are a couple of different views of the data - a tall/thin and short/fat depending on your tastes and a third tab provides some brief notes. There is some interesting data in there for sure and it's going to be fascinating to see what you all make of it!
We are looking forward to seeing what you create and don't forget to share your designs with us on Twitter with the hashtag #sportsvizsunday to be sure to be included in the weekly round-up.
Happy Sports Vizzing!
I liked how the post connected the May challenge to the recent snooker final, especially the note about Ronnie O’Sullivan matching Stephen Hendry’s record of seven World Championship titles after the 17-day tournament at the Crucible Theatre. The mention of that incredibly long 85-minute frame between Mark Selby and Yan Bingtao was a fun detail too it really shows how unpredictable sports moments can be when you start digging into the data. It made me curious to explore the dataset going all the way back to 1927 and see what kind of visual stories people might uncover. As someone who occasionally browses topics like Online Programming Assignment Help in Australia while studying data tools, it’s interesting to see how sports…
I really enjoyed seeing how the challenge results were visualized; the charts and breakdowns made the insights accessible and engaging. The way you explained the topic was very clear and helpful. I recently found a discussion on https://gocollectiv.com/ that offered a similarly thoughtful approach to visual data, which I found very insightful.
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