Spotting Minard on the Corner Three by Senthil Natarajan

Have you heard of the term "moonshot?" The concept of seeking out 10x solutions that have extraordinarily high barriers to overcome? Imagine how DeAndre Jordan, professional basketball player for over a decade, feels every time he steps onto the free throw line. Over his entire career, he has made, and I actually had to fact check this, fewer than 50% of his free throws. Every time he goes to the line, he’s throwing up literal and figurative moonshots. Just imagine if Christoph Scheiner had been around as a basketball fan in the 21st century. Instead of mapping the progressions of celestial bodies and sunspots, he may have instead mapped DeAndre Jordan free throws.

Actually, you don’t have to imagine any more. I took the liberty of doing it in his name. And not just Scheiner’s sun spots. Minard’s map of Napoleon’s march has been anointed by some people as the most profound example of information graphics every created. And I took all that profundity and instead asked the question: “what if Napoleon’s march and retreat, but instead it’s actually the progression into and out of overtime in a playoff game between the Miami Heat and the San Antonio Spurs?” … Maybe this is what people mean when they say just because you can ask a question doesn’t mean it needs to be asked.

I’m Senthil Natarajan, sports data scientist and graduate of Rice University. Since I started working in sports analytics in 2016, I’ve won competitions and consulted for professional teams, and the one thing I’ve learned is that the code you can write isn’t as important as the way you can communicate your findings. Maybe that’s why I’m so drawn to data visualization; because for me, it’s functionally a form of communication.

Whether it was learning data science and analytics in general or specifically data visualization, I’ve always found it helpful to look to the past for both guidance and inspiration. Re-working Scheiner’s sunspots diagram or Minard’s map of Napoleon’s march are both illuminating and amusing unto themselves, but it doesn’t always end in an infusion of levity. When we take W.E.B Du Bois’ famous spirals and redraw them using data on minority hiring into leadership positions in professional sports leagues, we’re suddenly left with a sinking put in our stomachs and more questions than we bargained for.

The best data visualizations are timeless in a way that crystallizes a certain zeitgeist, carrying forward lessons and advancing the entire field in a way that’s adaptable to any era. For me, who’s self-identity is so synonymous with basketball, the opportunity to examine the current state of sports through the lens of historical data viz is one that I just could not pass up. It’s an opportunity to take this unique intersection of straits and learn how to re-contextualize our modern world, how cross pollination between fields can advance the study of both, and simply just gain more of an appreciation for both sports and data art.

In this submission, I have attached visualizations that were both originally presented at Outlier 2021 as well as published on my personal social accounts. Please note that as these visualizations were originally presented publicly in 2021, some of the underlying data (such as in the remastered Du Bois spirals) is subject to have changed since then. The youtube video of my Outlier presentation linked to this submission goes in depth into my design process and explanation of the attached visualizations, but they're also briefly summarized here:

>Du Bois and Hiring in the NBA: This graphic uses the famous Du Bois spirals on Black Populations as a medium for elucidating the hiring of African Americans in the NBA relative to the player population in the league.

>Sunspots and Free Throws: This graphic uses the sunspot markings of Christoph Scheiner as a base for mapping samples of DeAndre Jordan's free throw misses (charted by their location of impact relative to the hoop) across a season.

>Napoleon's March Through the NBA Playoffs: As arguably the most famous data visualization in history, I would be remiss if I did not use Minard's Map of Napoleon's March to instead convey information about the Miami Heat's comeback victory in the 2013 Finals against the San Antonio Spurs, encoding score differentials, play descriptions, and win probabilities. (While the graphic denotes that I first created this piece in 2018, I did not publish it until the Outlier Conference in 2021).

>Michael Jordan and French Theatre (Bonus): This is a piece that actually was not shared at Outlier. Using the map on the earnings of Parisian theaters created for the 1889 World Fair by Cheysson and Simon, I wanted to project instead the scoring exploits of Michael Jordan during his career with the Chicago Bulls in a lead up to Netflix's Last Dance documentary.