This week’s mailbag features your questions on the best Achilles recoveries, superstar ejections, and more.
“If you were to pick five players to make your all-time defensive team, who would it be?”
I’m not going to do an all-time defensive team because it’s difficult, if not impossible, for me to evaluate players before at least the mid-1970s. Before that, there were no meaningful individual defensive statistics, and obviously I never saw those players play. Instead, here is my defensive team since 1990, with a couple of ground rules:
1. We’re talking about building a team for a season, not a single game or possession, so I’m not going to choose star players with high defensive peaks when motivated who weren’t as valuable over the course of the season.
2. Since it’s a team, players have to play their typical position.
3. We’re importing the prime versions of these players to 2017, so they should be capable of playing a modern style of game. This naturally favors current players over those who peaked in the 1990s.
With those rules noted, my team:
Point guard: Chris Paul
Ideally, I’d probably like someone taller than 6-foot at point guard. But Paul is plenty capable of switching and defending bigger players — he has defended Kevin Durant for extended periods in the playoffs — and his quick hands, pattern recognition and relentless pursuit of a competitive advantage earn him the nod over Patrick Beverley, Jason Kidd and young Gary Payton.
Shooting guard: Tony Allen
Despite my first rule, Michael Jordan is very much a candidate for this spot. But if we’re talking purely defensive value, I’m going with Allen, who is the only guard in the top 20 in career defensive box plus-minus. His relentless effort and energy make Allen first team on my team.
Small forward: Scottie Pippen
I’m giving Pippen a narrow edge over Kawhi Leonard, one of two small forwards (Metta World Peace is the other) to win Defensive Player of the Year in this timeframe. Pippen can defend all five positions for us and is ideal in a switch-heavy defense.
Power forward: Draymond Green
As much as anyone, Green benefits from the modern focus of my team. As good as Tim Duncan and Kevin Garnett were at power forward in their prime, they’re considered primarily as centers here. Green is more capable of defending smaller modern 4s who are comfortable beyond the arc.
Center: Ben Wallace
Naturally there’s no shortage of candidates at center, including the aforementioned two combo big men (one of whom, Duncan, I once argued was the best defender in modern history in terms of career value), plus Dikembe Mutombo, Hakeem Olajuwon and many more. Yet it’s Wallace who has the three greatest seasons in modern history by defensive box plus-minus and three of the top five by defensive RPM (the other two are outlier seasons by Shawn Bradley and Jason Collins). Wallace led perhaps the best defense I’ve ever seen, the 2003-04 Detroit Pistons, and though he’s been retired for five years, his athleticism would fit perfectly in the modern game. So he anchors my all-defensive team.
“Achilles’ ruptures being one of the toughest injuries to come back from, I was wondering how are you viewing Rudy Gay’s performance pre- and post-injury?”
— Michael Avidan
Gay’s performance has been shockingly good. Entering this season, without accounting for the Achilles injury, my SCHOENE projection system forecast a .490 player win percentage for Gay — slightly worse than league average (.500, naturally). Thus far, Gay has actually posted a .549 win percentage, which would be the second best of his NBA career after a .567 mark in 2014-15 with the Sacramento Kings.
I’ve identified 18 players who returned from a ruptured Achilles to play at least 250 minutes the following season. On average, these players saw their win percentage fall 8 percent short of their SCHOENE projection. (That’s a little bit less of a decline than we see with ACL injuries, which typically cause players to fall about 9 percent short of their projection.) While Gay isn’t the first player to beat his SCHOENE projection after a ruptured Achilles, he’s on pace to outperform it by more than anyone in the group.
Playing power forward more frequently with the San Antonio Spurs has probably helped Gay to some extent. He’s shooting inside 3 feet at the second-highest rate of his NBA career, per Basketball-Reference.com, and his rate of 2-pointers from beyond 16 feet is far and away his lowest ever. Additionally, Gay’s rebound percentages are career highs at both ends. At the same time, Gay hasn’t suffered any decline in his steal and block rates, which typically are worse after an Achilles rupture. So even aside from the more favorable role, Gay appears to have come back from his injury remarkably well.
Is it just me or are stars getting ejected from games far more often than in prior years? #peltonmailbag
— Walter Matthews (@WMatthews14) December 5, 2017
According to ESPN.com’s data, there have been 18 ejections so far this season. Of those, 12 were for players who have previously been All-Stars, the criteria I decided to go with for a star player. While the overall rate of ejections is in line with recent seasons, a far higher percentage of them have been for established All-Stars. (I tried only to consider cases in which the player had been an All-Star before the season, so as to level the playing field with this year, since obviously some current players who haven’t yet been All-Stars will make it.)
Because we’ve played about 30 percent of the schedule so far, the 2017-18 totals project out to approximately 59 total ejections — a tiny bit higher than the average of around 56 over the previous five seasons — with 39 of them being to All-Stars. That would blow away last season’s high (during this timeframe) of 24. In fact, if my count is correct, there have already been more ejections for All-Stars this season than there were in the entire 2013-14 and 2014-15 seasons.
I’m not sure what to make of this trend, and as usual I’d assume random chance until we have reason to reject that conclusion, but the instinct that stars are getting ejected more certainly proves true.
@kpelton can you explain difference bw Win shares, PER and VORP? What is the best all encompassing stat?
— pwr (@pwr321) December 5, 2017
First, let’s note one key difference: Some stats (PER here) rate players on a per-minute basis, while others rate the value they’ve provided, factoring in playing time (win shares) and replacement level (VORP). Oftentimes, you’ll see the same stat used in both ways: Win shares per 48 minutes is a per-minute stat, as is box plus-minus (used to create VORP). Meanwhile, PER can be translated into EWA (estimated wins added), a value stat.
In addition to the three you mentioned, all available on Basketball-Reference.com, there are two other all-in-one metrics I consider: my own wins above replacement player (WARP) metric and ESPN’s real plus-minus (RPM), which is used to calculate RPM WAR.
RPM is unique among these stats because it incorporates plus-minus data, adjusted for teammates and opponents, while also utilizing box-score stats for stability. Even with them, RPM tends to be noisier than box-score stats, so it can fluctuate from season to season. (The version of RPM on ESPN.com incorporates only data from the current season; there’s also a multiyear version that I use for projections that is not quite as noisy but also tells us less about what has happened this season.) The upside is that RPM can capture skills that aren’t tracked in the box score, particularly on the defensive end of the court.
Box plus-minus was designed to replicate RPM using only box-score stats. (Specifically, it’s a regression that’s built to value component stats like offensive and defensive rebound percentages by how well they predict a player’s regularized adjusted plus-minus, the predecessor of RPM that uses only plus-minus data and no box-score stats.) Therefore, the weights on different stats are well-calibrated in box plus-minus, though the use of interaction terms — assists are multiplied by defensive rebounds, for example — can create problems when players like Russell Westbrook go beyond the historical norms for these stats.
WARP is probably most similar to box plus-minus. While it wasn’t built off a regression, I’ve also used adjusted plus-minus to calibrate WARP, adding value to 3-point attempts to account for how players with many of them tended to outperform their WARP in terms of team impact. The key difference is WARP doesn’t have any of the interaction terms in box plus-minus.
Those three are the stats I utilize the most because I think they’re the best at isolating player value. Because win shares attributes all of a team’s defensive performance to individuals, it tends to be more sensitive to team success than other all-in-one stats. On the other hand, PER puts relatively low value on defensive stats and does not account for team defense whatsoever, meaning it primarily captures offensive value. PER also tends to overvalue players with high usage rates at the expense of those who are more efficient.
Because of the varying strengths and weaknesses I’ve laid out, I think it’s useful to consider multiple all-in-one stats while using the eye test to help explain the differences between them and where they might not fully capture a player value. Do be careful, however, of looking at various stats until you find the one that confirms the conclusion you already wanted to draw.