The Best Defenders in the NBA this Season

What Have You Done for Me Lately?

The NBA is a right now league. Each game can change in a moment. Every season’s trade deadline brings about substantial team restructuring, and the offseason free agency and trade market has become an event unto itself. Change happens quickly, and the team that wins the championship is often the team that becomes the best version of itself at just the right moment.

Many of the most important questions deal with which player or team is the best right now. “What have you done for me lately?” is the unspoken question on the minds of everyone in and around the league. In previous posts, I’ve used the defensive matchup data at stats.nba.com to create a model for defensive performance since 2013-14. The entire dataset is now features prominently on the homepage, and you can pull any player card for any season from the Google Sheets tool.

But what about this season?

Continue reading “The Best Defenders in the NBA this Season”
 

Identifying the Best Defenders in the NBA Using Matchup-Based Defense

Featured

Defense is half of the game of basketball, but it has been difficult to gather information about the defensive capabilities of all the players in the league until very recent seasons. Due to the paucity of data about defensive performance and the limitations imposed by television broadcasting contracts, it was practically impossible to truly know who the best defenders were, night in and night out.

Offense, by contrast, is well-documented. The box score provides a good deal of useful information on individual offensive output, and even more granular data has been available throughout the 21st century by virtue of play-by-play data.

Continue reading “Identifying the Best Defenders in the NBA Using Matchup-Based Defense”
 

Beyond the Box Score

It is time to stop evaluating players based on statistical feats. The ubiquity of statistical data has brought with it a ready supply of historical comparisons. In today’s NBA, one can hardly turn around without running into a stat trumpeting a player as “the first player since MJ to have 18 consecutive games of 20-5-5”. Who can ignore the box score aggregators, with their perpetual lists of “top performances of the night” that are oriented mainly around points, rebounds, and assists? The basketball community is awash in counting stats-based evaluations, but it’s time to cut it out.

The comeuppance has been a long time coming, to be perfectly honest. Fans have long prized points, rebounds, and assists as basketball’s version of the “Triple Crown” – a trio of statistics that can combine to depict a player’s value. Such an outcome is to be expected, since those three statistics are usually the largest numbers in any box score; our eyes are drawn to big numbers. In The Book of Basketball, Bill Simmons concretized the method of measuring players by Points+Rebounds+Assists in constructing his all-time rankings, which certainly did nothing to cool the ardor of counting stat acolytes.

It Was Never a Good Idea

Adding together counting stats was a bad idea to begin with. Taking values that describe discrete events and adding them without modification is among the poorest methods of measuring a player’s impact. Every box score statistic (every statistic period, as a matter of fact) exists on a certain scale. While it is quite common for a player to score 10 points in a game, and somewhat common for a player to grab 10 rebounds in a game, it is decidedly uncommon for a player to register 10 steals in a game. The scale – or range of normal values – for steals is much smaller than the scale for points. Since points, rebounds, and assists each have their own scale, adding them is always going to privilege points above the other components.

Continue reading “Beyond the Box Score”
 

Can You Give Me Some Stats to Prove that Russell Westbrook Steals Rebounds?

          Properly valuing and evaluating rebounds has become something of a hot topic in recent years with Russell Westbrook averaging a triple double for three consecutive seasons despite being one of the smallest players in the history of the league to average 10 rebounds per game. Much of the discussion about his incredible feat has centered on whether or not it is the case that Westbrook’s rebounding numbers are inflated due to Westbrook taking a disproportionate amount of defensive rebounds which could be collected by other members of his team.

          Naturally, a lot of people are looking for stats to support the conclusion which they’ve already reached (thus the tongue-in-cheek title). I think we can analyze this question, within the context of a useful estimation of rebounding value for the entire league.

Continue reading “Can You Give Me Some Stats to Prove that Russell Westbrook Steals Rebounds?”
 

Who is Really the Best Defensive Center in the League?

As with the previous posts in this series which detailed the best defenders at each position, I start with the question “Who are the best defensive centers in the league?” In order to address the question properly when evaluating centers, however, it is necessary to answer a prior question. What is a center’s defensive role in the modern NBA? During some prior eras, the center could remain near the basket either defending a fellow behemoth on the low block or walling off the path of opposing drives. Rule changes constricted the scope of zone defense. Then, the 3-point shooting revolution caught even big men in its tantalizing web. For the first time in basketball history, forces conspired to pull centers away from the basket for good.

Continue reading “Who is Really the Best Defensive Center in the League?”
 

The Best Defensive Power Forwards in the NBA

Small ball is no longer the wave of the future – it’s the wave of the present. The 80’s and 90’s featured brawny, bruising power forwards who could soak up punishment in the post, clean the glass, and protect the paint as weak side shot blockers. In a game dominated by giants, power forwards were the centers’ sidekicks. Even the beginning of the 21st century saw the San Antonio Spurs’ “Twin Towers” follow the same frontcourt structure that had held sway throughout the league’s existence.

Continue reading “The Best Defensive Power Forwards in the NBA”
 

The Best Defensive Small Forwards in the NBA

In the last installment of this series, we evaluated the best defensive shooting guards. We noted that the shooting guard group is crucial in the modern NBA due to the advantages gained by employing versatile defenders capable of stopping opponents of different sizes and skill sets. The same rationale applies for the players in the “small forward” bin using basketball-reference.com’s play-by-play position designations. When compared with the previous group, the main difference is that the small forwards are larger. (perhaps we should start calling them “big wings”?)

Wings, whether they are categorized as “shooting guards” or “small forwards,” exhibit greater spread in the defensive load they carry than other position groups do.

While the median values are relatively consistent across positions, wings have a wider distribution than other positions. Raw defensive load for wings can range from very high (>15 ppg) to very low (<6 ppg). Other positions, especially interior defenders, have much more compressed distributions.

Continue reading “The Best Defensive Small Forwards in the NBA”
 

Who Are the Best Defensive Shooting Guards in the League?

The NBA changes as rapidly as the seasons, and the league is heading toward a greater and greater reliance on versatile perimeter players. The prevalence of 3-pointers, combined with the emergence of bigger primary ball handlers replacing some of the smaller “point guards” of previous eras, has resulted in a single mandate for NBA defenses: to find defenders who are big enough and quick enough to guard anyone.

Continue reading “Who Are the Best Defensive Shooting Guards in the League?”
 

Who are the Best Defensive Point Guards in the NBA?

Rankings are among the most popular exercises for most NBA fans, and also among the least efficient ways to evaluate data. The enduring appeal of rankings and lists owes to their relationship, however tangential, with the big questions: Who is the best? Which player is better? How much better or worse would a team be if they replaced this player with that one? Every fan, analyst, scout, coach, and executive needs to be able to answer these questions.

The problem with rankings is not the questions they address, but the biases implicit in ordinal numbering. Our brains are trained to think that the difference between 12 and 17 is the same as the difference between 18 and 23, and that all these values are on a different order of magnitude from single digit numbers. When we transfer these assumptions to rankings of the “Top 50 Players in the NBA” or something similar, we start with false presuppositions. There is not an identical difference in value between each pair of contiguous players on any player ranking. Even a hypothetically perfect, pie-in-the-sky ranking that ranked players in the exactly correct order would still need something besides the ranking to indicate the players’ true value relative to their peers. Our habit of using ordinal numbers to rank players blinds us to the shape of the data.

As a result, both league insiders and outsiders spend an inordinate amount of time debating questions such as “Is Kevin Durant the second-best player in the league or the eighth-best?” “Is Paul George a top 5 player, a top 10 player, or a top 15 player?” What really matters is how much a player contributes to wins by helping put points on the board (on offense) and keep points off the board (on defense). If the 6th ranked player in the league and the 16th ranked player are nearly identical in terms of their contribution to team success, it makes little sense to lay so much weight on their difference in the rankings.

What a valuable ranking system can tell us is how much value a player generates, relative to the rest of the population. In answering the question posed in the title of this article, I will attempt to provide enough context for the reader to be able to comprehend the shape of the data. As such, let’s start with refining the question itself:

Who are the best defensive point guards in the league?

Continue reading “Who are the Best Defensive Point Guards in the NBA?”
 

Steals Don’t Mean Squat

If there’s one thing we know about defensive statistics in the NBA, it’s that steals don’t mean squat. James Harden was second in the league in steals per game last year, and Andre Drummond was eighth. This was not merely an illusion created by the two playing lots of minutes, as both ranked within the top 20 in the league in steals per 36 minutes. In 2016-17, Manu Ginobili and T.J. McConnell were first and second in the league, respectively, in steals per 36 minutes. Steph Curry and Nerlens Noel were both in the top seven in the league in 2015-16, while the same two players along with Pablo Prigioni all ranked in the top eight in the league the previous season. Andray Blatche was eighth in the league in steals per 36 in 2012-13. The illusion extends back as far as steals go in the statistical record.

Jason Getz-USA TODAY Sports

The Real Reasons Why Steals Don’t Mean Squat

          These examples are merely anecdotal evidence, though; what really makes steals unreliable indicators of defensive performance are the many different chains of events which can lead to a player being credited with a steal in the box score. Many of those sequences involve plays made by teammates of the player who gets credit for the steal. Any observer can recognize these plays when they happen: tipped passes, saves on balls headed out of bounds, instances in which an on-ball defender pokes the ball away from the dribbler and another defender grabs the loose ball, traps, double teams, errant passes caused by pressure on the ballhandler, etc. Sometimes a steal is the result of a phenomenal play by one defender, but oftentimes a steal is the result of one player disrupting the offense and another player recovering the ball. Steals create an immediate problem of attribution; the player who gets credit for the steal is not always the player who truly created the turnover.

Continue reading “Steals Don’t Mean Squat”