It’s been a while since I’ve written anything in this space, but I’ve not forgotten it, and I’ve not stopped tinkering with some of the ideas I’ve tried to tackle here before. The idea I’d like to return to today is my enjoyment of simple, easy to calculate, transparent boxscore metrics.

In the past, I built off of an easy to calculate and understand linear weights metric (Alternate Win Score) to create Usage Adjusted Rating, which essentially tried to adjust AWS to credit heavier usage players for the greater degree of difficulty they generally encounter in getting points and remaining efficient. The results were pretty good and passed the laugh test. But calculating UAR and the subsequent variant blend with plus-minus (UARPM) that I developed was best done on season long numbers and well, there are much better one number metrics out there for analysis of season long data. Daniel Myer’s Box Plus-Minus (BPM) and ESPN’s Real Plus-Minus (RPM) being the best examples. So from here on, I’ll be retiring UARPM from the website.

But for broad strokes analysis of single games, the current best linear weights metric is probably Alternate Win Score. Some people like to use John Hollinger’s Game Score, since it’s readily available on Basketball Reference for every game. I wanted to improve upon AWS and Game Score and build a transparent, easy to calculate and understand metric to quickly analyze game to game performance.

To build my game score metric, I looked to Jerry Engelmann’s 14 year RAPM data set, since it is, to my mind, the best estimate of long run  +/- impact that’s in the public domain. After that, I ran a regression of the most basic boxscore stats (per 100 possessions) to get the coefficients or weights for my simple linear weights metric.

 

New Win Score

I tried to include personal fouls, but they were not statistically significant predictors of RAPM (+/-) at all. All of the other boxscore stats I picked were highly statistically significant with strong p-values. Then, I translated the coefficients so that they were weighted relative to points score (i.e., so that the coefficient or weight for points was equal to 1). The resulting weights for my simple game score metric are as follows:

PTs + .2*TRBs + 1.7* STLs + .535*BLKs + .5*ASTs – .9*FGA – .35*FTA – 1.4*TOV

If you want to translate this linear weights metric directly to a simple statistical plus-minus, you can just subtract the average performance league-wide from the player’s total. Per pace adjusted 36 minutes the average performance in the league currently is roughly 4.9. Here’s the top 25 in the league as of the games played January 16 per game, pace adjusted, with the per-minute average subtracted out, so as to make it roughly +/- impact per game:

PlayersPM/G
Anthony Davis7.1
Stephen Curry5.9
Chris Paul5.7
James Harden5.0
Kevin Durant4.3
Jeff Teague3.9
Jimmy Butler3.8
LeBron James3.7
Kyle Lowry3.5
Damian Lillard3.3
Russell Westbrook3.1
DeAndre Jordan2.9
Tyson Chandler2.8
Brandan Wright2.6
Kawhi Leonard2.6
Kevin Martin2.6
John Wall2.6
Mike Conley2.5
Klay Thompson2.4
Paul Millsap2.3
Marc Gasol2.3
Hassan Whiteside2.3
Derrick Favors2.2
Kyrie Irving2.1
Kyle Korver2.1

Those results definitely pass the laugh test. Anyway, I like this as another tool in the tool kit. I even won over noted one number metric skeptic Seth Partnow to use the metric for some broad strokes performance analysis.

Good enough for me!

If any of you have a good idea for a name for this new Win / Game Score linear weights metric, let me know in the comments or on Twitter: @NBACouchside.

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Through 4 games, Tom Thibodeau’s defense is outside of the league’s top 10 in points allowed per 100 possessions and that is, obviously, very surprising. Granted, Chicago is 11th in defensive efficiency, so they are barely outside of the top 10, but given that under Thibodeau the Bulls have finished 1st, 1st, 5th, and 2nd in overall defense in the last 4 seasons, it is a bit surprising to see them anywhere but the very tip top of the league’s defensive rankings, even at this early juncture.

More at: http://www.blogabull.com/2014/11/6/7162997/the-bulls-strange-inability-to-defensive-rebound

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The subject of this article might not seem the most timely, given that Pau Gasol just beat the stuffing out of the New York Knicks in the Chicago Bulls’s season opener, recording an efficient 21 point, 11 rebound night in just 29 minutes of play. In fact, this might all end up being a bit of nagging worry that doesn’t amount to much of anything at all. But although the Knicks’ interior defense is incredibly bad, there were some not so great signs for Pau’s prognosis in that game, ones that were also evident during the pre-season as well.

More at: http://bballbreakdown.com/2014/10/31/pau-gasol-beat-up-the-knicks-but-might-be-slowing-down/

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This post was guest-written by Sam Phelps. 

When a person mentions the name Vince Carter to a typical NBA fan, they immediately think of insane dunks and highflying acts in general. He was one of the most exciting and popular players in the NBA during his prime, and he might just be the most impressive dunker to ever play the game. At 37 years of age, that Vince Carter is not going to the Memphis Grizzlies. However, people in fantasy basketball are very intrigued about what he could possibly bring to the table to make this team a legitimate title contender.

Memphis is lifted by the mantra of “Grit and Grind” for the last few years, and that could be for better or worse. Simply put, Memphis has been able to have success in the last few years by playing solid defense and finding some of the ways to win. Their biggest issue has been scoring consistently, but Carter is somebody who can definitely bring some value to the team right away.

Carter has done what very few players in NBA history have been able to. He has transformed his game into something that is much more perimeter oriented. He is one of the best shooters in the game right now, even if the average fan still thinks of him as a guy who can only drive. People in fantasy basketball were very impressed with the scoring ability with the Dallas Mavericks, and now he is going to get even more looks with Memphis.

By the time his new three-year contract worth $12 million plays out, Carter will be 40 years of age. He seems to be a bit rejuvenated now that he relies less on attacking the rim and taking punishment in the paint. As long as he can spot up and shoot while still having enough athleticism to keep defenses honest, he’s going to have success. This is the perfect fit for him in Memphis, and they will get more production out on the perimeter than they did a season ago.

In the very crowded Western Conference, Memphis continues to get overlooked. If they can play well and peak at the right time, Carter could make the difference between them being an average contender and then being a legitimate contender.

 

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[Ed. note: This piece originally ran on July 23, 2014 on a site where all traces of my former presence, along with that of all of the other members of the team, has been wiped away. I didn’t want it to disappear from the internet, so I’m reposting it here, where I have control over what happens to it.]

I am dumber than I like to think that I am. From time to time, it’s important to remind myself of this. This article is me doing just that. 

It is often easy when writing about sports to fancy yourself just as qualified as anyone else, including say general managers and talent evaluators, to say whether a player might be bad, average, good, or great. This is, for the most part, harmless, and in some cases, it is possible to outperform the average or bad general manager, if you’re pretty good at scouting talent (like all of the armchair GMs among us would like to believe we are). But this attitude can morph into the worst kind of narcissistic hubris, and well, make you (and when I say “you,” understand that I mean “me”) come off as a bit of an ass. Now, front office types do not have a corner on the market for knowledge about the game, and this should not read like an argument or claim that they do. What I’m wrestling with is that none of us has a perfect understanding of the game, and we’re all learning new things every day we’re lucky enough to watch the world’s other beautiful game. It’s easy to be blind to that. It’s so easy, especially in the super overreactionizer that is Twitter, to have a strong reaction to something and spew it out without really stepping back to question your own assumptions.

It’s quite hard to challenge those assumptions regularly; it’s so much easier to allow them to calcify and constrict my thinking. It requires no effort at all to fall back on my default setting: I know this and that and this too about basketball. But, then, every once in a while, I get to take a moment and breathe and really think, and what I always come back to is this quote from Socrates:

I know one thing: that I know nothing.

It is probably the most important sentence I’ve ever heard about the nature of knowledge. I should always be striving to learn and understand better. Whenever I decide I know something, I’m lost, because I’ve stopped learning.

This is all a bit abstract, so let me be more concrete. When the Chicago Bulls, my favorite basketball team, traded a bunch of assets to acquire Creighton star Doug McDermott, I basically had a Twitter meltdown. McDermott is probably one of the best shooters in the world on a team that was terrible at scoring last year, but all of my favorite statistic-based models cast lots of doubts about whether Doug could play at the NBA level. He didn’t pass very much, he basically never got blocks or steals, and his rebounding was merely decent. McDermott’s low block and steal rates and just okay rebounding made me worry about his athleticism, as those three stats have traditionally been pretty reliable at predicting which players will have the athleticism to hang in the league and those who won’t. The concerns about McDermott’s athleticism matched my own eye test concerns about him. So I decided I knew who Doug McDermott was as an NBA player before ever seeing him play in the NBA. I ignored people, like my friend Ricky O’Donnell of BlogaBull, who pointed out Creighton’s ultra-conservative defensive scheme as a reason for his low defensive counting stats. I scoffed off people who told me he was a good body position defender. I disregarded the common-sense idea that when you’re scoring as much as McDermott did and moving all over the court non-stop with literally five defensive players all aimed at stopping you, maybe defense takes a bit of a backseat. I stopped thinking and started ranting. I was lost.

The statistical models I love have had a pretty good success rate, especially when compared with the average general manager in the NBA, but they’re not infallible. There are plenty of misses, just as there are with any attempt to predict the future of very young men making the transition to a totally new atmosphere and level of competition. There are simply too many things we can’t know at the time of the draft which effect how well a player will do at the next level. How they played in college or internationally and their resulting counting stats is a big piece of that puzzle, but it is only part of it. I ignored that, too.

I watched Doug McDermott in summer league, and many of my concerns still linger. He probably won’t score as prolifically as he did in college and his lateral quickness is not great. But McDermott is so, so smart. He makes extremely quick decisions with the ball, which is a still undervalued skill and its value is multiplied exponentially by the threat he represents as a shooter and floor spacer, especially given his lightning quick shooting release. He’s going to bend defenses, just by virtue of these two skills. He’s also a much better passer and decision-maker than his low college assist totals would suggest. Additionally, McDermott is, as I was told, a solid body position defender, who will mostly funnel players towards his help defense- perhaps not coincidentally, the Bulls have two of the league’s very best help big men in Joakim Noah and Taj Gibson. Yes, McDermott will give up blow-bys to more athletic players and yes, that will be frustrating when it happens, but it won’t hurt as much as it might on another team because of those two big mobile guys behind him. Context matters very much in basketball, and well, maybe on draft night and after I didn’t think enough about the context in which McDermott will be operating. The defensive warts can be more easily hidden in Chicago than nearly anywhere else and his skill-set is a much needed one on any team, but especially for these Bulls.

Film Crit Hulk is one of my absolute favorite writers, and he has a tremendous piece which centers around a bit of advice given to him by the famed director, Quentin Tarantino. During a conversation in which a younger, perhaps less thoughtful Hulk ranted against a movie he “hated,” Tarantino told him, “Never, under any circumstances, hate a movie. It won’t help you and it’s a waste of time.” Tarantino went on to more fully explain that there is value and things to learn and enjoyment to be found even in the bombs or, for our basketball-watching purposes, busts. Tarantino finished his advice by saying of movies, “They’re gifts. Every f*cking one of ‘em.”

I am much less sure than I was about what sort of player Doug McDermott might be than I was on draft night. Part of that is a function of his summer league play, but a bigger part of it is me allowing myself to embrace that I don’t know nearly as much as I sometimes think and act like I do. What I do know is that regardless of whether he turns out to be a “bomb” or another “hit” for the Bulls front office, I’ll learn from watching him play. I’ll learn from seeing his struggles or successes and the how and why behind them. I’ll be entertained, as I always am, by the process. Doug McDermott is a gift, just like every player which I have the privilege to watch and root on.

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A Quick Prediction Post

A Quick Prediction Post


Posted By on Sep 22, 2014

I wanted to get this up now that it’s done. I may blow this out into a larger series with fuller explanations of how I arrived at these win totals, but the short version is that it was roughly the same method as last year’s xRAPM predictions, only using ESPN’s Real Plus-Minus (which is largely the same as xRAPM). I also ran the numbers through the actual schedule, so SOS is somewhat adjusted for. Unfortunately, I wasn’t able to include back-to-backs and their influence into the projections, but this should be a decent projection anyway.

TeamWins
OKC59
CLE59
SAS58
GSW58
MEM58
DAL57
LAC57
CHI51
MIA49
HOU49
WAS48
POR48
TOR48
PHX45
ATL42
IND41
MIN37
BKN36
NOP36
CHA32
ORL31
BOS31
DET30
DEN30
NYK30
MIL25
SAC24
UTA23
LAL20
PHI18

Enjoy responsibly.

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