Jeremy's Daily Jewels

Throughout this NBA season I’ll be sharing some interesting notes and quotes I come across while doing my research for the upcoming DFS slate in a new DGCourtroom.com feature called: Jeremy’s Daily Jewels.

Today I wanted to switch things up a little bit and present some statistics that I believe can really give us an edge on the competition when selecting our dfs lineups. We’re all aware that in sports, players are constantly going through hot and cold spells. Nowhere is this more evident than in basketball, and specifically when dealing with shooting percentages.

Regression to the mean is a statistical phenomenon that occurs when unusually large or small measurements tend to be followed by measurements that are closer to the mean(1).

In this article, we’re going to examine how this relates to NBA players and their shooting percentages. It will allow us to identify some players who have started off their season shooting at a percentage that cannot be sustained, as well as some players that started out in a funk and are due to turn it around.

First, we’ll analyze some players who have been shooting the rock significantly better than they did last season. These players’ prices are more than likely inflated right now across the dfs universe.

As with any form of analytics, it should be noted that there is context to every player on this list. For example, young guys like D’Angelo Russell or Terry Rozier could have simply just gotten better in the offseason. Whereas with a wily old vet such as DeMarre Carroll, it’s more likely to be an anomaly, or someone who’s on a hot streak.

Negative Regression Candidates (Overall Field Goal %):

image1.png

The column on the far right, labeled DIFF, represents the player’s current shooting percentage minus their final shooting percentage from last season (over time we want to target the negatives and avoid the positives).

The above chart identifies some guys that we’ll want to start avoiding over the next week or so as they come back down to Earth, or “regress to the mean.” If a player spends a week shooting 10% over their average, it follows that at some point they’ll spend a week shooting 10% below their average.

Now some guys can stay hot (or cold) for longer than a week. One strategy I’ll use for predicting when somebody is going to break out of a slump is by studying their game logs from the last time they broke out of a slump. Who was the opponent? Were any key players out? Was it the first road game after a long home stand?  

The opposite can also be true of a player, and these are the guys we’re going to want to start targeting. The next chart shows us some guys who’ve gotten off to a slow start to the season and that we can expect to start heating up soon. These are players whose prices are probably too low right now.

Positive Regression Candidates (Overall Field Goal %):

image3.png

I didn’t include any players who were within +/- 5% of their shooting percentage from last year because those types of fluctuations are fairly normal in basketball.

I’ve also compiled the same data on 3-point shooting percentages.

Negative Regression Candidates (3-Point Field Goal %):

image2.png

To give these 3-point percentages some context, I dug up the 5 players who had the largest 3-point shooting percentage increase from the 2014-2015 to the 2015-2016 NBA season. According to hangtime.blogs.nba.com, Kawhi Leonard was first with an increase of 9.4%. Second was Al-Farouq Aminu with an 8.7% increase. Third was Will Barton at 7.4%, followed by Kemba Walker at 6.7% and Jeff Teague at 5.7%. As I mentioned earlier, players who significantly increase their percentages from one season to the next tend to be young guys still adjusting to the NBA game.

Positive Regression Candidates (3-Point Field Goal %):

image4.png

If you take nothing else from this analysis, at least you can impress your friends by telling them all about regression to the mean!

(1) - Adrian G Barnett; Regression to the mean: what it is and how to deal with it, International Journal of Epidemiology.

Back2Back Watch:

Memphis and Dallas are playing their second game in as many nights.

Atlanta is on the first leg of a back-to-back.

Let’s Talk About Pace, Baby:

  (League rank as of 10/25)

(League rank as of 10/25)

Yuck!

Have a reaction to this article? I’d love to hear any feedback in the comments section below.

You can follow Jeremy on Twitter @zinneDFS