• moseswootten

Weekly Round-Up 02.13.22

Updated: Sep 25

Between the Super Bowl tonight and the Winter Games that are currently taking place in Beijing, there's a lot of high quality sport currently taking place. Alongside this, there's also been some high-quality visualisations from the #SportsVizSunday community too. While I can't bring you the results of the Super Bowl yet (I think it's a proper 50/50), I'm pleased to say I can bring you the visualisations! So let's get into it.


I'm starting with the Super Bowl. On the one hand, I was absolutely amazed to find out from Anthony Reinhard's visualisation that the Cincinnati Bengals were the underdogs for 15 of their 17 regular season NFL games when the schedule was first published. On the other hand, I knew that they had the worst record in the whole of the NFL only a couple of years ago. Anthony's visualisation of the initial point spreads for each of their games is really clean, and shows just how remarkable this Bengal's season has been! We'll find out soon whether they can cap it off in style...


For their first #SportsVizSunday visualisation, Christian Felix took on our Winter Games monthly challenge and produced an absolute stunner of a visualisation showing the dominance of the male luge athletes from Germany, Austria and Italy through the history of the sport. This is such a beautiful visualisation that is absolutely packed with great design touches - the fade on the colours as the athletes finished further away from the medals is really clever. Personally, I love everything about this and will be coming back to it a lot for design inspiration.


Sticking with the Winter Games, Krisztina Szűcs has been visualising the results of different sports using a beautiful design of triangles to show when goals/points were scored and you may have seen her featured in our round-ups before. Most recently they have tackled the men's ice hockey results from the Winter Games (pun intended) but there are examples of others sports in their Twitter feed. Just one of the areas where I think these designs really shine is in showing the flow of a game and how the momentum can shift from one side to the other, which is something that can be hard to grasp from the scores alone.


Inspired by Krisztina's designs, Neil Richards used Tableau to create an adaptation for the Mixed Curling, which has just finished at the Winter Games. As always with Neil's work, there is a lot of artistry combined with buckets of detail buried in the little elements, like faded vs bold colours and thick borders. I'm very impressed with how much data is shown for each match without compromising the coherence when you look at all the matches at once.



Moving us into football is Yash Sakhuja's breakdown of The Art of Ronaldo's penalties, which was also their #IronViz submission too. There is a lot of great analysis in Yash's visualisation. I particularly admire the storytelling where Yash uses images of the goals showing where Ronaldo scored his penalties to bring to life how Ronaldo's penalty technique has changed over the years. I was left with an ever better appreciation of just how good Ronaldo is!


Next up is Nicola Santolini's remarkably comprehensive look into the styles of play of the different teams in the top 5 football leagues in Europe: the Premier League, Bundesliga, Ligue 1, La Liga and Serie A. As well as producing two interactive Tableau dashboards (in multiple languages might I add!) Nicola has written an easy-to-read blog post explaining the metrics that they have chosen, and has identified some really interesting shared characteristics across the leagues themselves. If you've got an interest in football, I highly recommend setting aside some time to through this properly. I will definitely be going back to it.


Tedy Iskandar has taken a look at basketball and in particular has pulled out Justin Holiday. I enjoyed the extra detail explaining why Justin Holiday was famous in Indonesia - and the clean visuals showing how Holiday's efficiency varied compared to the league average. There's some interesting insights on here - Holiday is much more efficient towards on side of the court, and has had very little success under the basket itself.

Another person flying the flag for non-Tableau visualisations this week is Soumyajit Bose, who has used Matplotlib to craft his Arsenal-based replica of Mateusz Karmalski's James Bond #IronViz. The technical difficulty of this is very high, and it's no mean feat to have been able to replicate all the original elements! I particularly like the way they have replaced the original data with very natural things about Arsenal football club instead.


Over on LinkedIn, Josh Tapley shared a visualisation made by Quinn Serfass looking at whether Temple Basketball could make a run for the March Madness this year. I love the way Quinn has focussed the narrative around Temple's star player, and what has happened to the team since that player's injury. This is a really clean visualisation which is easy to read through, and I like the extra notes that Quinn has added to allow readers to understand even if they aren't that familiar with basketball and the metrics that are commonly used (readers like me!).

https://www.linkedin.com/posts/josh-tapley_could-temple-basketball-make-a-run-for-the-activity-6898037708246392832-qeyo


Priya Yogendra Rana has created a cool visualisation around Michael Schumacher's career in Formula 1. There's lots to enjoy in this visualisation and my particular highlight is where Priya shows how Michael transformed teams into winners. The use of the dot plot, coloured by team and shaded by Michael's career, really shows the transformative effect that a superstar driver can have on a team. It's an effective visualisation that allows the reader to absorb an insightful bit of analysis.


Finally for this week is Simon Beaumont's visualisation showing the wait for a home winner across the four tennis Grand Slams. I can see Simon's experience combining visualisation and analysis in this, from the choice of colours that echo the logos, through to the tiny dot plot indicating when in the year each Slam takes place. For me, one of the things that makes this visualisation work so well is that Simon has chosen to put the detail of who actually won each Slam into the tooltip, which means that the visualisation can remained focus on the story that he is telling.


And that's a wrap for this week! As always, a big thank you to everyone who contributed visualisations this week. If you've got a bit of spare time, or would like dip your toes into the water with some new data, then do have a go at our monthly challenge. For this month's challenge we have two lovely datasets inspired by the Winter Games - one on men's luge results, and one on the position of shots in women's ice hockey. They are both excellent and I look forward to seeing the magic that you will weave!

140 views0 comments

Recent Posts

See All