The Boxscore Geeks Show: The Analytical Ari Caroline

The amazing Ari Caroline(@aricaroline), Chief Analytics Officer at Memorial Sloan-Kettering Cancer Center hops on the show to talk analytics, how healthcare and sports differ in data, and, of course, the draft!

As always, thanks to our amazing producer Brian Foster (@boxscorebrian)!

This Week's Poll

In discussing the stats, Ari brings up a player the eye test says should be good, but the numbers say is average. We delve into the stats and come away with a little optimism. Players have a lot of room for growth in the NBA, so what do you think?

Analytics: Healthcare vs. Sports

I've written about healthcare before. Of course, Ari's first question was why I didn't bug him first. He's said a thing or two about this himself.

Ari's work at Memorial Sloan-Kettering is unique. Having an analytics squad with access to as much big data on cancer research makes for attacking fascinating problems.

One key difference between sports and healthcare is how structured the data is. In sports, we have clearly defined tabular data, even for the new stats. In healthcare, you may have to infer a simple yes or no question from doctors' notes.

What NBA Player Qualities to Look For?

Here's a glimpse into Ari's mind. Here's his "draft board" for the top 100 Draft Express prospects.

A little background. Ari, like Dave, has developed a regression for analyzing the value of player boxscore stats. These line up very closely with the Wins Produced coefficients. A slight change Ari makes is to use a "continuous position curve", that is based on a player's skills. For the ultimate head scratcher: Joakim Noah is considered a small forward by Ari's measure based on the skills he brings to the table. This is not as surprising as you might think.

Using Ari's coefficients, we see their per 40 minute college numbers, and as a result, who teams should look at. As we discuss, this chart is by no means the final word. It's just a good starting point for teams to look.

The problem we notice is teams don't start here. They look at other factors that are less predictive of future NBA success. As Ari has pointed out, teams have a blindside to many stats. Oddly, they do seem to get how point guards should play.

"Can players learn to play better?" is a question we discuss. While this can happen, it's not as common as people think. Of course, this is referring to after players have been in the league awhile (see Westbrook and Melo). Incoming talent may have hope. For example, Michael Carter-Williams did not look that great in Ari's numbers last year. But, he showed some flashes of greatness this year. Who knows where he'll be by his contract extension.

In terms of "learning" to play in the NBA, Ari brings up Nik Stauskas. On Michigan he just could not get any steals. Is that a quality he might learn in the NBA? Certainly things like his shot selection and shooting efficiency look promising.

We drilled down the rabbit hole on advanced stats. For instance, should players be graded against their position for shooting percentage if they take a lot of shots? For instance, Russell Westbrook shoots above average for a point guard. However, he takes many more shots than the average point guard. Should those shots be "penalized" in evaluating Westbrook. On this subject, Ari has done work looking at the value of "stretching the floor" based on different position types.

Also, we discuss the position issue. Wins Produced will look at what the player is assigned. However, should we penalize players if a coach plays them incorrectly? Dirk Nowitzki is often used as a power forward. Of course, his skill set is such that it should be easy to play him next to a power forward more regularly.

Adreian Payne seems like a Kevin Love type player. Except, he just can't grab offensive boards. Ari's position adjustment still has him as a power forward. However, he's close to average because of his offensive boards. That definitely makes you wonder how Love can shoot so many threes and still crash the glass so well.

One note on all the players and analytics we discuss is how thin the margin for greatness is. A 60% True Shooting player compared to a 55% True Shooting Player is a big difference. However, that's only five baskets (give or take depending on their three point shooting) every hundred shots. That's really hard to notice. That's why it's important to be able to explain why a metric say a player is good or bad.

Ari notes that despite his size, D.J. Stephens could be a great talent in the NBA. He played well in limited minutes for the Bucks last season. Despite being listed as a guard-forward, he plays like a power forward. Turns out that can work! (See Charles Barkley and Dennis Rodman)

Khem Birch looks to be the best draft gem, and James Young looks like this year's draft mine. Of course, we don't know yet!

Shout Outs!

Every week we will like to thank people in the sports stats realms. This week's shout outs go to

  • Kenny Pickett (@KennyPickett), who has the coolest job description ever! Thanks Kenny for for catching a trivia flub I made. It turns out the 1984 and 1986 Celtics had multiple Finals MVPs. They had just played for other teams. Thanks for the catch!
  • R.C. Buford. After a great finals win and a well deserved Executive of the Year, we still think Buford's been getting ignored for too long. We love ya Buford!