Ernie Grunfeld

Wizards Roll With NBA’s Worst Bench

tire-fire

Wizards bench.

With an average starting unit and the NBA’s worst bench, the Wizards are lurching toward an inevitable appointment with the 2017 draft lottery — assuming team president Ernie Grunfeld doesn’t trade the pick for the next Markieff Morris in an all-out dash for 9th or 10th.

The disastrous bench was in the works at least a couple years, as the franchise’s top strategists laid plans to have loads of cap space for an offseason in which almost half the league would be able to sign a maximum salary free agent. Their subsequent moves to restock the roster seem to reflect one of the defining characteristics of the Grunfeld era: an elite ability to misdiagnose the source of the team’s problems.

Missing the playoffs in 2015-16, according to public statements by Grunfeld and team owner Ted Leonsis, was due to injuries, a bad bench and poor chemistry caused by having so many players in the final year of their contracts. And they shoveled some blame on the coaching as well.

In reality, the Wizards were affected less by injuries last season than most teams in the league, and their bench was about average. I’ll defer to those closer to the team on the cause of whatever chemistry problems existed, although it’s worth noting that multi-year contracts haven’t seemed to fix the issue.

What’s happening this year? Their starters are (like last year) about average, but their bench is a worst in the league catastrophe. They’re the Secretariat of bad benches.

So far this season, the Wizards starters — Wall, Beal, Porter, Morris and Gortat — have a minutes weighted Player Production Average (PPA) of 135. In PPA, average is 100, higher is better, and replacement level is 45. That’s slightly better than the league average starting group (PPA: 132 so far), and ranks 12th. Not elite, but not terrible either.

The bench’s minutes weighted PPA: 28. The average bench: 66. The second worst bench belongs to Memphis, and its PPA is 44. These are the only two teams with benches that rate below replacement level. To put this in perspective, Trey Burke’s PPA this season is 28. Kevin Seraphin, who ended his Wizards career with PPA scores of 35 and 38 would be an upgrade. Kwame Brown was never this bad in Washington. Even Ike Austin (remember him?) managed a 35 with the Bullets.

The gap between Washington’s starters and bench is the third largest, behind the Clippers who have the second best starting unit and fourth worst bench, and Golden State, which has the best starters and the sixth best bench. How good are the Warriors? They’re starting five has a PPA of 211 — 32 points better than Washington’s best player.

This is the team built by Grunfeld and Leonsis, and their cherished Plan. It’s a disaster — not because of injuries or bad luck, but because of a series of poor decisions.

Player Production Average

There is some good news. Wall is having the best season of his career, Porter is producing at an All-Star level, and Beal is healthy and productive.

Marcin Gortat’s production is down, but I don’t think it’s related to aging (I’ll write about this next time). Morris has been worse than expected. To the numbers…

PLAYER GMS MPG 11/8 11/21 PPA
Otto Porter 20 34.4 173 177 179
John Wall 18 35.9 168 167 171
Bradley Beal 17 34.7 66 92 131
Marcin Gortat 20 35.4 135 146 130
Danuel House 1 1.0 119 116
Sheldon McClellan 7 11.1 478 88 81
Markieff Morris 20 31.7 67 78 59
Marcus Thornton 19 19.5 31 41 50
Kelly Oubre 19 15.5 18 17 41
Tomas Satoransky 18 16.6 18 43 29
Trey Burke 16 11.6 -48 28 28
Andrew Nicholson 14 10.1 33 35 9
Jason Smith 19 11.6 -93 -42 -23
Ian Mahinmi 1 14.0 -98
Daniel Ochefu 3 2.7 -181 -119 -117
Advertisements

Wizards Remain Mediocre and Will Miss Playoffs for Second Straight Season

Oklahoma City Thunder v Memphis Grizzlies - Game Six

Yeah, I know the season is underway. Many teams have three games in the books; the Spurs already have four. This still serves as my Wizards preview, because while I’ve watched their first two contests (both losses), I’ve used nothing from the 2016-17 in the projection.

The approach this year is similar to the one I used for previous seasons: every player gets run through my statistical doppelganger machine, which spits out similar players from my historical database (similar production at similar age). There’s a process to weed out players with dissimilar career patterns — it makes no sense to compare a guy who stunk four years and suddenly had a terrific season to a guy like John Wall (for example) who’s been consistently quite good.

Once the list of “similars” is assembled, the system looks at the future of those players as a guide to the potential performance of the players being projected for the upcoming season. When the predicted performance (expressed in terms of Player Production Average — PPA for short) for each individual player has been completed, I estimate minutes (using an approach that must be similar to Kevin Pelton’s since the results were so similar). That gets translated into individual wins, which are totaled to team wins. Wins league-wide are capped at the number of wins available in a season (1230).

What’s new this year? Volume. For the first time, I projected the top 10-12 rotation players of every team. In previous seasons, I ran numbers for only the Wizards. This year — in a never-ending quest to make wrong predictions — I looked at everyone.

The Wizards

The Wizards spent two years hording cap space for an offseason in which nearly half the league would have sufficient room under the cap to pursue free agents with a maximum salary offer. The big prize was hometown hero Kevin Durant, who declined to even meet with the team. The team’s braintrust went after Al Horford (who signed in Boston) before managing to get Ian Mahinmi — a career backup coming off a career year who’s about to turn 30.

Their other roster moves were less inspiring: free agent deals for Andrew Nicholson and Jason Smith, and a trade for Trey Burke. They did manage to sign international guard Tomas Satoransky to a reasonable contract.

Here’s a quick look at what my projection system had to say about this year’s roster:

  • John Wall — Good news: Wall’s similars were a collection of very good players (albeit with a penchant for reputations that were better than their production). Bad news: half of the 10 most similar reached their career peak before age 26. More than half saw production declines following their age 25 season. Last season, Wall finished with a PPA of 144. Projected PPA: 130.
  • Bradley Beal — Beal’s persistent injury troubles overshadow what may be a bigger problem: his consistently mediocre play when he’s been on the floor. His PPA by season (average is 100 and higher is better): 92, 96, 99, 98. Players like Beal tended to peak at “decent starter,” not All-Star or All-NBA. The Wizards awarded him a max contract. Projected PPA: 108.
  • Otto Porter — Porter has improved during his career, and his future looks terrific (projected peak PPA would put him at All-Star level). But, the exercise in projecting the performance of individual players makes clear that it’s unwise to assume a young player will a) improve at all, b) that improvement will be linear, and c) that he’ll ever achieve imagined potential. Similar were useful defensive SF types who were also efficient on offense. But, there was no pattern of improvement after seasons most similar to Porter’s last year. So, Porter projects “about the same” as last year. Projected PPA: 127.
  • Markieff Morris — Last season, Ernie Grunfeld and Ted Leonsis swapped their first round pick in 2016 for Morris, who was deeply unhappy in Phoenix. What they got was a career mediocrity with little chance of getting better. The average peak of players like Morris (in Washington) last season was fairly low (acceptable starter level), and came (on average) at age 25.9. Morris is 27. Projected PPA: 95.
  • Marcin Gortat — The big man has been very good and consistent in Washington. He defied the decline I predicted for last season, and will have to do the same this year. At age 32, a drop in performance is probable — eight of the ten players most similar to Gortat declined the following season, and a ninth maintained. One oldster (Robert Parish) actually improved significantly in his age 35 season. I don’t anticipate something similar in Gortat’s age 32 season. Projected PPA: 147.
  • Trey Burke — The Wizards got him for next to nothing, which was the right price to pay. Burke started his career well below average, and has been less productive each year since. His comps were mostly backups who had short NBA careers. Surprisingly, Eric Maynor didn’t make the list. I’m actually predicting a modest improvement for Burke, although he’s unlikely to be close to what Ramon Sessions provided. Projected PPA: 67.
  • Tomas Satoransky — No comps for Satoransky since he didn’t play in the NBA last season. Although he has experience overseas, the NBA is the world’s most competitive sports league, and most players struggle to make the transition. Projected PPA: 65.
  • Kelly Oubre — The second year swingman seems to have abundant potential despite a horrific rookie season. Unfortunately, the history of players who performed like Oubre isn’t a pleasant one. Improvement was surprisingly modest (I double-checked the spreadsheet cells to make sure they were calculating correctly), and peaks were depressingly low. It’s worth mention that the same was true after Porter’s rookie year, although Porter had an injury. Projected PPA: 37.
  • Andrew Nicholson — The PF is coming off his best season (PPA: 81), which could mean he’s figured things out and is ready to become a useful backup, or…it could be the best he’ll ever play and he’ll recede to previous levels. His comps are useful backup types, and my projection suggests the latter. Projected PPA: 86.
  • Ian Mahinmi — When the Wizards whiffed on their other free agent targets, they turned to Mahinmi. It’s not exactly a bad contract under the league’s new financial realities, but it’s a #SoWizards kinda move. Mahinmi was a career backup who finally got a chance to start and responded with a career year. That’s good, right? Sure, except a) he’s going back to the bench in Washington (the team’s most productive player per possession the past few years (Gortat) plays the same position), and b) he’s about to turn 30. His “most similar” list is mostly journeyman centers. Some had high peaks, but few sustained it. What’s most likely is that he’ll be decent, but not nearly as good as he was last year. Projected PPA: 112.
  • Jason Smith — The decision to give Smith a multi-year deal was puzzling. He has a career PPA of 59, posted a 57 last season, and is 30 years old. It’s another #SoWizards move: no chance of meaningful contributions and no upside. It’s a nice lotto payout for Smith, though. Projected PPA: 50.

A potential wildcard: new head coach Scott Brooks. Previous coach Randy Wittman had his strengths, but would have ranked in the bottom third in the NBA. Brooks figures to be better, but the relevant research suggests the differences between professional coaches is pretty small. The exceptions are the very best and very worst coaches, but there’s a broad middle ground where coaches help a little or hurt a little, but don’t fundamentally alter their teams’ trajectories. While I think Brooks is an upgrade from Wittman, I also think they both occupy that middle ground.

Options

As I projected the entire league, I found that my process tended to push each team back towards the middle. The gap between the strongest team (Golden State) and the weakest (Phoenix) was about 26.7 wins. In recent years, the difference has been almost double that amount. So, I came up with an alternate method that ranked every team by their projected production, and then applied the average win total for that rank over the past five seasons.

The Wizards project to be ninth team in the East, and 19th in the NBA. Don’t go betting the mortgage, because my approach produced some results that are at odds with my gut and with predictions made by others I respect, such as:

  • My system likes Chicago and thinks the Bulls could finish as a top four team in the East.
  • Orlando projects to make the playoffs (7th seed).
  • Milwaukee and Atlanta both project to be worse than the Wizards.
  • In the West, my system likes Oklahoma City, Minnesota, Utah and Houston more than Portland.

For the Wizards, the win total from my projection system: 41.0. From the average record by league rank approach: 37.5. Take your pick.

My prediction: 41 wins and 9th place in the East.

The Surprising Problem for the Wizards

wall frustrated

One of The Official Narratives of the 2015-16 Washington Wizards season is that point guard John Wall is terrific, but is getting sideswiped by a substandard supporting cast. Last month, The Washington Post’s Dan Steinberg lamented that, “The saddest thing here is that the Wizards might be in the process of sacrificing a year of John Wall’s prime.”

In Michael Lee’s excellent article at Yahoo!, Wall echoed Steinberg, saying: “I ain’t trying to waste a season.

Adam McGinnis and I touched on the subject during our podcast last week.

Alas, as is the case with many Official Narratives, there are problems.

  1. On a per-possession basis, Wall isn’t Washington’s most productive player. That honor goes to center Marcin Gortat. Because Wall plays five more minutes per game than Gortat, Wall leads the team in total production.
  2. Wall is not an elite player.
  3. The overall production difference between Wall (Washington’s top producer) and Gortat (second in total production) has been vastly overstated.
  4. The quality of Wall’s “supporting cast” isn’t bad.

Wall’s PPA (see below) is 148 this year. Among players with at least 500 minutes this season, he ranks 54th. Among point guards, he ranks 11th. Wall has had stretches of dominant play, but his performance continues to be plagued by the same bugaboos he’s had throughout his career: turnovers, poor shot selection and poor shooting. Gortat, by the way, ranks 29th in PPA.

Wall isn’t an elite player. For the past few seasons seasons (including this one, most of the year), he’s rated as a top 8-10 point guard and a top 40-50 player overall. That’s very good, but well short of the impact from elite point guards and elite players. He could be great — he was in December, for example. But his performance game-to-game is a mix of fantastic and horrible. Which averages out to very good, not elite.

The average PPA of top total producers for each team is 179 — 31 points better than Wall. Among those top 30 producers, Wall ranks 24th in per possession production — ahead of Carmelo Anthony, Rajon Rondo, Nerlens Noel, Gordon Hayward, Tyson Chandler and Jordan Clarkson.

The average top producer has provided 22.0% of his team’s production. Wall is about average at 21.8%.

The average gap between a top producer and his team’s “number two” is about 4.5%. For Wall and Gortat, it’s 2.7%. Want a player who actually fits The Official Narrative? Try New Orleans where Anthony Davis has a PPA of 189, provides 26.3% of his team’s production, and (at 13.2%) sports the biggest drop to his team’s second most productive.

Since you’re wondering, the top five in total production shares:

  1. Stephen Curry, GSW — 29.6%
  2. Russell Westbrook, OKC — 26.7%
  3. James Harden, HOU — 26.4%
  4. Lebron James, CLE — 26.3%
  5. Anthony Davis, NOP — 26.3%

And, here’s the top five in drop-off to “number two”:

  1. Anthony Davis, NOP — 13.2%
  2. Stephen Curry, GSW — 12.7%
  3. James Harden, HOU — 8.5%
  4. Kawhi Leonard, SAS — 8.3%
  5. Kyle Lowry, TOR — 8.2%

Wall and the Wizards are 20th.

That’s all fine, you might be saying, but The Official Narrative isn’t necessarily that Wall’s “Robin” sucks, it’s that the roster lacks depth. That lack of depth means Wall has to carry a heavier load than other franchise leaders. Unfortunately, this is also wrong.

For this question, I calculated minutes-weighted PPA (mwPPA) for each team — after deducting the production of its top player. mwPPA provides a handy way of measuring the relative quality of each team’s roster.

The league average “supporting cast” posted an mwPPA of 92. The Wizards rank 14th so far this season with a 93. Since you were wondering, here’s the top five in supporting cast mwPPA:

  1. SAS — 124
  2. GSW — 121
  3. ATL — 107
  4. OKC — 105
  5. BOS — 104

So, to recap:

  • Wall isn’t elite.
  • The gap between Wall’s total production and Gortat’s is smaller than average for a number one to a number two.
  • The Wizards “supporting cast” is mediocre, not terrible.

The real problem for the Wizards is in that first bullet. Their problem: they don’t have an elite player.

Player Production Average

The ratings below are from a metric I developed called Player Production Average (PPA). In PPA, players are credited for things they do that help a team win, and debited for things that don’t, each in proportion to what causes teams to win and lose. PPA is pace neutral, accounts for defense, and includes an adjustment based on the level of competition faced when a player is on the floor. In PPA, average is 100, higher is better, and replacement level is 45.

League-wide PPA scores through games played 3/14/16 are here.

PLAYER GMS MPG 11/10 11/22 12/3 12/13 12/21 12/30 1/6 1/13 1/27 2/11 3/1 3/14
Marcin Gortat 60 30.2 91 112 128 133 132 138 147 145 148 151 172 169
John Wall 66 35.9 153 129 136 168 157 157 149 144 142 146 153 148
Otto Porter 59 30.1 144 158 104 116 107 115 122 127 130 130 134 126
Jared Dudley 65 27.7 36 92 90 85 98 103 100 105 99 104 106 98
J.J. Hickson 6 7.5  –  –  –  –  –  –  –  –  –  – -14 96
Bradley Beal 42 30.6 128 108 96 87 87 86 85 86 98 108 94 94
Nene Hilario 42 18.8 58 90 80 74 79 78 79 88 92 84 86 90
Alan Anderson 8 14.0  –  –  –  –  –  –  –  –  –  – 97 90
Ramon Sessions 66 20.3 131 119 84 90 87 89 88 91 90 89 88 85
Markieff Morris 14 26.0  –  –  –  –  –  –  –  –  –  – 41 58
Garrett Temple 64 25.4 38 106 57 54 70 63 68 79 79 69 59 56
Jarell Eddie 21 4.7  –  –  –  –  – 153 119 113 110 86 68 51
Kelly Oubre 53 10.7 -103 -4 -40 -44 9 37 43 39 36 29 22 25
Drew Gooden 28 10.6 99 51 57 56 56 56 38 47 34 31 26 22
Marcus Thornton 3 15.0  –  –  –  –  –  –  –  –  –  –  – -6
Ryan Hollins 5 9.6  –  – -40 60 59  –  –  –  –  –  –  –
Kris Humphries 28 16.6 90 121 95 80 78 76 79 79 78 76  –  –
Gary Neal 40 20.2 23 49 64 75 78 74 75 78 71 70 69  69
DeJuan Blair 29 7.5 -345 -129 -112 -45 -34 -38 -38 -28 -6 -15  –  –

Randy Wittman vs. Analytics

wittman grimace

Yesterday, Wizards head coach Randy Wittman appeared Sportstalk 980’s “Sports Fix” with Kevin Sheehan and Thom Loverro (as transcribed by the Washington Post’s Dan Steinberg) and provided a treasure trove of comments worth some analysis.

Let’s unpack a bit, shall we?

Writes Steinberg:

The Wizards have their own special history with the [analytics]. There were critics throughout much of the 2014-2015 season who wanted Randy Wittman’s Wizards to play a smaller, faster, more three-point-friendly game, and who sometimes used numbers to make their case. Owner Ted Leonsis, at least in one blog post, seemed sympathetic with their cause.

ESPN the Magazine gave the Wizards a mediocre “analytics” rating, writing that “Washington lags in terms of applying the lessons of analytics to its shot chart even in the midst of the team’s best season since 1978-79.” The Wizards went smaller in the playoffs and found some success. After the season ended, the Wizards held an “analytics” scrimmage, and Leonsis defended the franchise’s use of analytics. And by the start of this season, they were debuting a faster “pace and space” offense that seemed more aligned with modern NBA thinking.

A very fair and cogent summary of the Wizards’ recent history with statistical analysis. The thing that makes me twitch is the notion that “analytics” said the Wizards should play faster. The numbers I track indicated that a) playing fast hadn’t helped the team in recent years, b) that if anything the Wizards were slightly better in slower-paced games, and c) that playing fast or slow or in-between is a bad goal because it doesn’t mean anything. There’s no prize for having a lot of possessions.

During 2014-15 (and the several preceding seasons where stat guys made similar points), the lesson from the numbers was that the Wizards could benefit by exchanging two-point jumpers for threes, at-rim attempts and free throws — to the extent possible. The team’s “go fast” approach was a leap of faith unsupported by the numbers.

From Steinberg:

At least one local critic — ESPN 980 host Kevin Sheehan — has pointed the finger at the “analystics”-inspired change.

“I wouldn’t be surprised if we find out down the road that this small lineup pace-and-space style of play was forced on Randy Wittman and his staff,” Sheehan said recently, “forced on them by some advanced-analytics stats geek who convinced the technological visionary who owns the team that this team was stuck in yesteryear, that this team was stuck in old ways of playing basketball that weren’t going to work anymore:

Hey Ted, Ted, I’ve got this logarithm that I wrote, it’s really cool stuff, I got the idea from an app that I created for sci-fi movies and it’s really gonna work in the NBA, bad twos, you can’t take those anymore, you’ve got to take threes, you’ve got to space and pace, you’ve got to go small, you’ve got to play a stretch 4, this is the way of the future, Ted, this is the way you’ve got to do it. And Ted said to Randy ‘Hey Randy, what do you think about this pace and space and stretch 4s and shoot more threes and it worked in the playoffs and we almost made it to the Eastern Conference finals.

“Jesus!” Sheehan concluded. “This whole thing all season long is just a blown opportunity. A major blown opportunity. I would love to know what Ted is thinking right now.”

If Washington has a stat goober who told them the numbers said they should play fast, he should be fired. Second, the space part of the new offense has probably helped a bit. Last season, the team ranked 22nd in offensive efficiency, 1.9 points per 100 possessions below league average. So far this season, they rank 18th — about 1.0 points per 100 possessions below average.

This is a fairly small effect, which at least one stat goober expected before the season. The Wizards weren’t the only team to apply the lessons of statistical analysis, defenses have been adapting, and games generally come down to overall talent and execution. And the team has middle-of-the-road talent.

Washington’s real problem, of course, has been defense, which has nothing to do with pace or space. Last year, they ranked fifth overall defensively, 2.6 points per 100 possessions better than average. This year: 17th, about a half point per 100 possessions below average. Over the past two seasons (individually or combined), there was no relationship between pace and defensive efficiency.

Appearing on Sheehan and Loverro’s show, Wittman had this to say (courtesy Steinberg):

“I’ve got to coach the team. Analytics haven’t won a ballgame. You’ve got to take what you have and put guys in position that they can best succeed at. And there are some things with numbers that help that, but if you see some of the number sheets that we have, it would drive you crazy. But you know what, that’s the world we live in. You can fight that, but that does you no good. Listen, I’ve been in the business 32 years now. We had analytics back in the ’80s, alright? We had numbers. Plus-minus, and guys playing with certain guys, and that’s never changed. It’s just now, for whatever reason … Hey, it’s good for some people. Because guys have gotten a lot of jobs because that of word.”

A few thoughts. “Analytics” is the study of what wins and loses basketball games. “Analytics” are drawn from the actual games. They’re not made up. When done well, they reveal what’s really happening on the floor, pinpoint what’s important, help coaches and players identify advantages and disadvantages that can be discerned in the numbers, but might escape the naked eye. Analytics are a tool to help coaches and players perform their jobs better, and (hopefully) win more games.

Wittman’s comments suggest the Wizards have some serious internal problems, though — and NOT because he’s resistant to “analytics.” The telling statement is “…if you see some of the number sheets that we have, it would drive you crazy…”

A head coach should not be getting buried with sheets of numbers. He’s a basketball coach, not a statistical analyst. Like many busy people, when presented with an overload of information, he’s going to ignore most of it, seize on a few things he thinks he understands, and then go with what his experience tells him is the right strategy.

The proper role for a statistical analyst is to crunch the numbers, perform the analysis, and then communicate the findings in a way that coaches and decision-makers can understand. If Wittman is being driven crazy by the data, then the analysis department is failing. It sounds like the Wizards may be missing the crucial ability to communicate the findings of their analysts.

Also worth considering is the kind of numbers and information being analyzed and presented. It has become fashionable in recent years to break players into their component skills and seek to construct a roster as if completing a puzzle.

Based on comments made by GM Ernie Grunfeld, the Wizards are big into this kind of analysis. Symptoms include statements such as: the team needs to add “shooting” or “defense” or “rebounding” or “ball handling” or “length” or…you get the idea. As if “shooting” can be “added” to a lineup.

This approach has been borrowed from other sports like football or baseball, where specialists can be extremely valuable. This is much less true in a flowing game like basketball. “Adding” a shooter to the lineup means “subtracting” another player from the floor. Whatever specialty a player is put on the floor to perform, the team gets his whole game — offense and defense. So while it’s worth analyzing what guys are good at doing, it MUST be coupled with analysis of his overall impact on the game.

From Steinberg:

“And not to try to get you into trouble, but it’s been sort of a season-long question for Wizards fans, and I’m a big one,” Sheehan said. “And that is how on board were you with sort of this space-and-pace and pace-and-space and going small?”

“Well, I didn’t have big decisions to make,” Wittman said, “because after the roster was put together with the guys that left and the additions that we had, I had nobody that could back up Marcin [Gortat] at the 5 spot. Kevin Seraphin left and I had nobody there. I thought what was best for our team was to take Nene out of the starting lineup and play him more at 5 than at 4. And that was more just because of the makeup, and we had success with it.”

Good question from Sheehan. Wittman’s answer is…interesting. I agree with his point that the roster construction left him with few lineup choices. I’m baffled by his comment about Seraphin because the big fella was terrible with the Wizards and has been even worse with the Knicks.

From Steinberg:

Wittman said he’s sympathetic with armchair coaches, because he does the same thing when he’s watching baseball or football. But he noted with some amusement that last year critics said his team was playing too big, and this year other critics say his team is playing too small. He said he would run out of minutes if he started a big lineup but then also used Nene as his second-string center, but added that a bigger lineup could be used in a shorter playoff series. And he said this year’s changes have both helped Washington’s offense and hurt its defense.

“There’s no question about it, [it] hurt our rebounding a little bit as well,” he said. “And that’s an important factor for us because we want to run. If you don’t rebound the ball, you can’t run.”

The first part of this struck me as a strawman. Statistical analysis suggested the team would be better off taking fewer two-point jump shots, and that the team could probably benefit by adding a stretch-four. That doesn’t mean “playing smaller” — at least not to me.

I disagree with Wittman that the changes are what hurt the defense. And the rebounding really hasn’t suffered much at all. Last season, the Wizards were third in defensive rebounding at 77.3%. This year, they’ve fallen to tenth, but their defensive rebounding percentage is still a robust 77.0%. More teams than ever are opting to emphasize getting back on defense rather than going for offensive rebounds.

If it’s not rebounding, what’s causing the decline in Washington’s defense? Answer: an inability to make opponents miss. Like last year, the team still does a good job keeping opponents out of the paint (fifth best at preventing opponent at-rim attempts; down from third best last year). However, opponent efficiency on at-rim and three-point attempts has improved. That could be about playing smaller lineups (taller players tend to force lower opponent shooting percentages), but it could be something else such as less effective close-outs on three-point attempts, and/or random variation.

Bottom line: bad analytics didn’t sabotage the Wizards — at least not at the coaching level. What’s hampered them this year is the reality that they have very average talent across the board.

Player Production Average

The ratings below are from a metric I developed called Player Production Average (PPA). In PPA, players are credited for things they do that help a team win, and debited for things that don’t, each in proportion to what causes teams to win and lose. PPA is pace neutral, accounts for defense, and includes an adjustment based on the level of competition faced when a player is on the floor. In PPA, average is 100, higher is better, and replacement level is 45.

League-wide PPA scores through games played 3/1/16 are here.

PLAYER GMS MPG 11/10 11/22 12/3 12/13 12/21 12/30 1/6 1/13 1/27 2/11 3/1
Marcin Gortat 53 31.0 91 112 128 133 132 138 147 145 148 151 172
John Wall 59 35.9 153 129 136 168 157 157 149 144 142 146 153
Otto Porter 52 30.5 144 158 104 116 107 115 122 127 130 130 134
Jared Dudley 58 28.4 36 92 90 85 98 103 100 105 99 104 106
Alan Anderson 3 16.0  –  –  –  –  –  –  –  –  –  – 97
Bradley Beal 38 31.0 128 108 96 87 87 86 85 86 98 108 94
Ramon Sessions 59 20.4 131 119 84 90 87 89 88 91 90 89 88
Nene Hilario 35 18.7 58 90 80 74 79 78 79 88 92 84 86
Gary Neal 40 20.2 23 49 64 75 78 74 75 78 71 70 69
Jarell Eddie 18 5.0  –  –  –  –  – 153 119 113 110 86 68
Garrett Temple 57 25.3 38 106 57 54 70 63 68 79 79 69 59
Markieff Morris 7 24.1  –  –  –  –  –  –  –  –  –  – 41
Drew Gooden 27 10.8 99 51 57 56 56 56 38 47 34 31 26
Kelly Oubre 48 11.2 -103 -4 -40 -44 9 37 43 39 36 29 22
J.J. Hickson 2 5.5  –  –  –  –  –  –  –  –  –  – -14
Kris Humphries 28 16.6 90 121 95 80 78 76 79 79 78 76  –
Ryan Hollins 5 9.6  –  – -40 60 59  –  –  –  –  –  –
DeJuan Blair 29 7.5 -345 -129 -112 -45 -34 -38 -38 -28 -6 -15  –

On a per minute basis, Gortat remains the Wizards’ top producer. Wall leads in total production because he plays more minutes.

Markieff Morris has had a rough start to his career in Washington, but should improve over time.

A Bit More on the Trade for Markieff Morris

markieff-morris

In talking with fans, I’ve pulled up all kinds of information about Markieff Morris. Here are a few observations that came mostly from examining the claims made by folks who support the acquisition:

  • 2014-15 was the best season of Morris career. He posted a Player Production Average (PPA) of 102 (see below for a brief explanation). Among the 81 players identified by Basketball-Reference as PF who received at least 500 minutes, Morris ranked 36th.
  • Morris ranked 17th among PFs in total production last season, which would sound better if I omitted mention that he was second in total minutes played.
  • Last season, among the 27 PFs who played at least 500 minutes and had a usage rate of 20% or higher (I had Morris at 22.0% last season), Morris ranked 24th in offensive efficiency.
  • In the defense part of PPA, Morris rated slightly better than average last season. Not a good defender, but not terrible either.
  • Among those 81 PFs last season, Morris ranked 62nd in rebounds per 100 team possessions. This season, Morris ranks 49th among 66 PFs with at least 500 minutes.
  • While his work on the boards is a weakness, Morris could actually improve Washington’s rebounding by taking minutes from Jared Dudley. It was a bad idea for the team to rely so heavily on Dudley — a poor rebounder at SF — as the team’s PF. Dudley is the worst rebounding PF in the league. He trails second worst Luc Mbah a Moute by more than a rebound per 100 team possessions.
  • Morris has played badly this year. Some trade supporters have mentioned Morris averaging 20.6 points and 7.6 rebounds per game in the month of February. Two primary problems here — first: the “month” is five games so far, which is to say Small Sample Size Theater; and second: Morris has scored more by shooting more. His offensive rating in those five “good” games was a below-average 102 points per 100 possessions, and his rebound rate was below average. Overall, Morris posted a PPA of 86 in February. Better than the season average by a bunch, but still below the league average.
  • There’s a false narrative circulating that Morris saw his production drop last season (2014-15) after the Suns traded away their backcourt. His PPA was 147 15 games into the season. It bounced around in the 120-130 range, but trended down for the next 30 games. His PPA fell below 120 in the 48th game of the season — January 30 — and continued to decline from there. As of the last game BEFORE the trades, his PPA was just 103. With his new teammates the rest of the way, his PPA was 101. He finished the season with a PPA of 102.

markieff 2014-15 rolling ppa

Player Production Average (PPA) is a metric I developed in which players are credited for things they do that help a team win, and debited for things that don’t, each in proportion to what causes teams to win and lose. PPA is pace neutral, accounts for defense, and includes an adjustment based on the level of competition faced when a player is on the floor. In PPA, average is 100, higher is better, and replacement level is 45.

History Hates This Year’s Wizards

USP NBA: WASHINGTON WIZARDS AT DETROIT PISTONS S BKN USA MI

NBA history has a few things to say about the Wizards, but not much of it is encouraging. Washington could radically improve — there are teams that started similar to the Wizards and got better — but the most likely outcome is a losing record, a trip to the lottery, and the possibility of a coaching change.

Combing through the archives at Basketball-Reference produced 39 teams since 1985-86 that had an efficiency differential through their first 32 games similar to Washington’s -3.2. Records varied from a high of 17 (two teams) to a low of 10 (six teams). The group average 12.9 wins — trailing Washington’s 15, but right in line with their expected wins (based on scoring differential).

Some teams like the Wizards (to the same point in the season) went remarkably different directions. At the low end are the 2012-13 Magic, which started 12-20 and managed just eight wins the rest of the season.

At the other extreme are the 2004-05 Nuggets, which started 14-18, fired head coach Jeff Bzdelik, and then finished out the year on a 32-8 run after hiring George Karl. The Nuggets earned the 7th seed in the playoffs, and lost in the first round.

Just 10 of the 39 teams finished with a record of .500 or better. Only four finished the season with a positive schedule-adjusted scoring differential.

On average, the group finished with 33.8 wins and a schedule-adjusted scoring differential of -2.62. Teams like the Wizards did improve, but only by about 0.8 wins per 82 games. Ten teams made the playoffs, but only one (the 2001-02 Charlotte Hornets) could win a series.

Ten teams fired coaches mid-season, but there was no better/worse trend from the changes. Some teams got better after a coaching change; some got worse. Twelve teams made coaching changes after the season. Six teams fired coaches mid-season, AND made a coaching change after the season.

Teams like the Wizards on average:

  • Record: 33.8-48.2
  • Average schedule-adjusted scoring differential: -2.62
  • .500 or better winning percentage: 26%
  • Average conference finish: 10.3
  • Made playoffs: 26%
  • Won a playoff series: 3%
  • In-season coaching change: 26%
  • Post-season coaching change: 31%

Three teams were 15-17 after their first 32 games with an efficiency differential about the same Washington’s. Only one of those teams made the playoffs (the 1992-93 Atlanta Hawks). The Hawks finished 43-39, got the 7th seed, and lost in the first round. After the season, they replaced Bob Weiss with Lenny Wilkens and won 57 games.

The other 15-17 teams — the 2008-09 New Jersey Nets, and the 1994-95 Dallas Mavericks — finished with 34 and 36 wins respectively. Both missed the playoffs, and neither made a coaching change.

Barring significant improvement from the Wizards, the most likely outcome is 35-38 wins and a scoring differential of around -2.0. While Washington is only 2.5 games out of 8th place in the East, it will probably take 44-45 wins. And they have to pull ahead of four other teams in contention for that spot.

There’s still 50 games remaining in the season, so there’s definitely still time for the Wizards to turn things around and salvage the season. Unfortunately, it’s rare for teams that started a year like them to have a happy ending.

Wizards Update: Mediocrity, Naturally

Sports fandom involves some cognitive bias. We assign importance to patterns without real meaning, see signs in events that are essentially random. We hope for the best and steadfastly convince ourselves this is the time things finally work out for the good guys. Long-time Wizards fans are experts at this kind of thing. Our brains are wired for it.

For example, the Wizards won four games in a row before falling to the Clippers and Raptors. Winning streaks are usually interpreted as a sign that a team is good. They’re finding their groove, hitting their stride, getting a rhythm. Right?

Well, no, actually. Long streaks, like Golden State’s (or Philadelphia’s) to start the season provide meaningful information about the relative quality of those teams. But, for virtually every NBA team, including a  mediocre one like the Wizards, three- and four-game streaks are inevitable. According to the handy table in Dean Oliver’s 2004 book, Basketball On Paper, a team that wins half its games during an 82-game season has a 99.4% chance of winning four in a row at some point. Naturally, that .500 team has the same odds of losing four in a row. By their 28th game, the Wizards had accomplished both, plus an independent three-game winning streak.

A .400 team — one that would win about 33 games — has an 87% chance of winning at least four in a row during an 82-game season. Even a 25-win team has nearly a 50% chance of at least one four-game winning streak.

Sometimes randomness is fun, like Rasual Butler’s hot streak last season, or Gary Neal’s this year, or Garrett Temple’s binge of three straight games with at least 20 points. Other times, it’s not so fun, like Butler’s second half of the season, or any of Neal’s “non-hot” games, or the dud performances Temple produced in the games preceding and following the scoring outburst.

This is not meant to be a nihilistic “everything is random and therefore meaningless” screed. Some teams and players are better than others. But, the true quality of a team is found by what they do on average, over time.

The Wizards in recent years have been decidedly, consistently, mediocre. I can hear the arguing already: 46 wins last season; 44 wins the year before; trips to the second round of the playoffs both years. These are signs of the Wizards being a team on the rise that’s hoarding cap space for a run at a superstar, and they’ve had some bad luck with injuries this season. Maybe. But, more likely: fan-think.

In an 82-game season, how many games would a truly mediocre team win? The easy answer is 41. That’s exactly half, right in the middle. Therefore, 46 wins is five better than average, which means the Wizards were better than average. This isn’t wrong — just incomplete.

Let’s imagine a team that’s perfectly mediocre in quality. By the end of an 82-game season, it will score exactly as many points as its opponent. How many games will this mediocre team win? They might win 41, but they might win a few more or a few less. Their win total depends on how those points get distributed. Having a 50% chance of winning each individual game doesn’t mean a team will actually win half the games.

For a simple randomness test, google up a coin-flipping simulator or flip a coin yourself. Just for kicks, I ran a coin-flip simulator on 11 sets of 82 trials, one set of 66 trials, and one set of 30 trials. Astute readers might notice the number of “trials” matches the number of regular season games the Wizards have played since Ernie Grunfeld became president.

Of the 998 trials, heads came up 516 times — 51.8% of the time. Variance, right off the bat. If “heads” equals “wins” (and it does here because it’s my blog), that works out to about 42.5 “wins” per 82 games.

Here are the “win” results from each set of the 82 coin-flip trials:

  1. 47
  2. 48
  3. 39
  4. 46
  5. 37
  6. 35
  7. 38
  8. 36
  9. 42
  10. 44
  11. 53

In other words, in a random test where each independent coin flip has identical odds of producing a win or a loss, there’s a low of 35 wins and a high of 53. For the heck of it, I ran the simulation again and got a cumulative “winning percentage” of .454 with a high of 43 and a low of 34. Remember: this is totally random. A perfectly mediocre team could see its actual win total vary significantly from .500.

Which brings me back to the Wizards. There are a few good measures of relative team strength besides record. Chief among these are scoring differential, and efficiency differential, which are basically the same thing, and those same measures adjusted by strength of schedule.

Those differential numbers (adjusted for strength of schedule or not) can be used to estimate how many games each team would be expected to win. Last season, for example, the Wizards’ scoring differential suggested a team that would win 42-43 games. Winning 46 felt good, but was probably more about random outcomes for a mediocre team. The playoff “runs” were hella fun to watch, but represent a small sample size that’s even more prone to random variation. In other words, us fans (and maybe folks in the league as well) overrate results from the first round of playoffs.

Let’s go back to Team Perfectly Mediocre, and let’s say they’ve met their match in the first round of the playoffs. We’ll call the opponent: the Toronto Raptors. Who’s going to win this festival of random mediocrity? It might be a closely-matched, 4-3 series, but maybe not. I replicated 10 seven-game series for Team Mediocre vs. the Raptors, and the “series” went seven games three times, and six games three times. It also had three consecutive “sweeps” and one five-game series. Remember: this is totally random.

Back to the Wizards. Since Grunfeld took over Washington’s basketball operations before the 2003-04 season, the team has been meaningfully worse than mediocre, even allowing for randomness. Under Grunfeld’s leadership — now in its 13th season — Washington has won 417 out of 998 regular season games. That’s a winning percentage of .418. Just to see, I ran the “perfectly mediocre” test of Grunfeld’s 998-game (so far) term with the Wizards 10,000 times and couldn’t come up with a variance close to Washington’s actual performance. This is a fancy way of saying the Wizards have been truly bad under Grunfeld.

Over the course of his 12 full seasons, the Wizards have compiled a record of .500 or better six times, but have managed a positive scoring margin just three times. Grunfeld’s teams in Washington have averaged 34.3 wins per 82 games — slightly outpacing the 33.9 predicted by scoring differential and the 33.3 predicted by adjusted scoring differential.

If the 998 games represented a single, massively long basketball contest, the Wizards have been outscored by 2,467 points with Grunfeld at the helm.

Player Production Average

The ratings below are a metric I developed called Player Production Average (PPA). In PPA, players are credited for things they do that help a team win, and debited for things that don’t, each in proportion to what causes teams to win and lose. PPA is pace neutral, accounts for defense, and includes an adjustment based on the level of competition faced when a player is on the floor. In PPA, average is 100, higher is better, and replacement level is 45.

League-wide PPA scores through games played 12/30/15 are here.

PLAYER GAMES MPG 11/10 11/22 12/3 12/13 12/21 PPA
John Wall 30 35.5 153 129 136 168 157 157
Jarell Eddie 3 12.7 153
Marcin Gortat 27 31.2 91 112 128 133 132 138
Otto Porter 27 32.0 144 158 104 116 107 115
Jared Dudley 29 27.4 36 92 90 85 98 103
Ramon Sessions 30 21.0 131 119 84 90 87 89
Bradley Beal 17 36.5 128 108 96 87 87 86
Nene Hilario 12 17.4 58 90 80 74 79 78
Kris Humphries 25 17.5 90 121 95 80 78 76
Gary Neal 24 22.1 23 49 64 75 78 74
Garrett Temple 28 21.5 38 106 57 54 70 63
Ryan Hollins 5 9.6     -40 60 59 59
Drew Gooden 6 12.8 99 51 57 56 56 56
Kelly Oubre 23 12.7 -103 -4 -40 -44 9 37
DeJuan Blair 18 8.4 -345 -129 -112 -45 -34 -38

The basic message in the numbers: Wall and Gortat need help. The Wizards don’t have starter-quality players at power forward, shooting guard or (arguably) small forward. Wall remains in the good-not-great range; Gortat’s production is still solid, but diminished significantly from last season.

The other basic message: Wall and Gortat need help fast. Teams in the East have improved, and it’s probably going to take 44-45 wins to make the playoffs. The Wizards are on pace for 38. To reach 45 wins, they’ll need to go 31-21 over their remaining games — about the pace of a 49-win team. Theoretically possible, but not very likely. Barring a major turnaround, the conversation about the Wizards in April won’t be about their matchup in the playoffs, but about their odds of getting the top pick in the draft lottery.