Last season, the Washington Wizards were executing the first phase of a reload strategy articulated by general manager Tommy Sheppard. They jettisoned veterans and snapped up youngsters with potential on the cheap while they waited for John Wall to rehab his torn Achilles.
The plan took a turn when Wall decided he wanted out and Sheppard was able to trade him to the Houston Rockets for former MVP Russell Westbrook, who wanted to leave Houston.
Other than the departure of Wall, who’d missed at least half the team’s games due to injury over the past three seasons, and the addition of Westbrook, the Wizards made only minor roster changes. They brought back the youngsters (except for Admiral Schofield), and used free agency to add depth in the form of backup center Robin Lopez and reserve guard Raul Neto.
The draft brought them Deni Avidja, a promising forward who’s already pushing for a starting role, and Cassius Winston, a point guard who might one day grow into a decent backup.
Last season was about development. This season, the Wizards want to win. Their offseason suggests they’re confident in the development of their youth because they’re running it back with the same group that had a .347 winning percent last season plus Westbrook.
The forecasts use my Player Production Average (PPA) metric. PPA is an all-around rating tool that credits players for things they do that help a team win, and debits for things that don’t — each in proportion to what causes NBA teams to win and lose. PPA is pace neutral and includes accounting for defense and the level of competition a player faces when he’s on the floor. In PPA, average is 100, higher is better and replacement level is 45.
Last season, I ran two forecasts: one using my Statistical Doppelgänger Machine and the other using a predicted PPA based on an age-adjusted career curve. I called that second approach “MILK” In honor of sports economist David Berri, who wrote that NBA players age like milk.
The final prediction wasn’t bad. Individual player forecasts were hit and miss, but the approach pegged overall team quality. I forecasted a 29-53 record over an 82-game season, which converts to 25.5 wins over 72 games. In the pandemic-shortened season, the Wizards won 25 games.
My forecast predicted a .354 winning percentage. They finished at .347. Pre-bubble, they were 24-40 — .375, which works out to 30-31 wins over an 82-game schedule.
Of course, any prediction of this nature needs a substantial amount of luck to be in the vicinity of correct.
This year, I ran the same two forecasting approaches and added two more — a simple weighted three-year average PPA and another that applies an aging adjustment to that weighted three-year average. I also ran a “best case” forecast using the highest predicted PPA from these various methods.
My final forecast blends each approach, except the “best case” scenario. I’ll include the “best case” record in the summary below.
Probably the toughest part of any forecast is projecting playing time. It’s impossible to predict injuries, and this year COVID-19 increases risk of players missing games. I used Five Thirty Eight’s forecasted minutes and then tweaked it based on having more team-specific knowledge (like Westbrook not playing in back-to-backs, and Bertans having a more prominent role in the rotation than they’re guesstimating).
- Last PPA = PPA last season
- DOPP PPA = forecasted PPA using the Doppelgänger approach
- MILK PPA = forecasted PPA using last season’s PPA and an age adjustment
- SIMP = forecasted PPA using a “simple” weighted three-year average PPA
- SAGE = forecasted PPA using a “simple” weighted three-year average and an age adjustment
- BLEND = forecasted PPA using an average of the four approaches above
Just for the heck of it, I’ve put a *** next to the forecast I think is most plausible for each individual. In most (but not all) cases, it’ll be BLEND.
In 2019-20, Beal emerged as one of the game’s better offensive weapons. His defense early in the year was atrocious, but improved considerably after he didn’t make the All-Star team. In my analysis, he almost deserved All-Star honors. His play improved before the league shut down and he ended up almost meriting All-NBA. At 27, Beal’s likely entering the “plateau” stage of his career, which is fine — he’s very good.
- Last PPA: 160
- DOPP PPA: 167
- MILK PPA: 158
- SIMP PPA: 154
- SAGE: 152
- BLEND: 158***
Westbrook has had an undeniably great career. I think he’s still going to be good to very good for another year or two, but he’s also 32 years old and players that age usually get worse. That’s reflected in the forecasts.
While Westbrook was named All-NBA last season, it was the least productive season since year two of his career. It was also a third consecutive decline in production. If I was wagering on this, I’d pick a PPA for Westbrook between DOPP and SIMP.
- Last PPA: 126
- DOPP PPA: 129***
- MILK PPA: 79 (yikes)
- SIMP PPA: 139
- SAGE: 111
- BLEND: 114
Is Bryant a quality starting center or “just” a good role player? Fans, analysts, and the forecasting models can’t make up their minds. Three of my four statistical approaches think he’ll be very good this season. The doppelgänger method predicts a significant step back. I’m confident Bryant will remain an efficient scorer. While he showed significant defensive progress in the bubble and in preseason, I’m less confident in him at that end of the floor.
This is a big year for him and his future role with the team and in the league.
- Last PPA: 143
- DOPP PPA: 115
- MILK PPA: 165
- SIMP PPA: 154
- SAGE: 177
- BLEND: 153***
The plus/minus analysts think Hachimura stinks, but I disagree. His defensive awareness is poor, and he’s most comfortable offensively in the no-man’s land of midrange jumpers. And yet, he was near league average in PPA last season, even with a serious injury and a poor showing in the bubble. The doppelgänger approach predicts a relatively low peak for him, but if he follows a normal career arc, he should improve significantly this year. He’s going to miss the next three weeks with an eye infection.
- Last PPA: 95
- DOPP PPA: 110***
- MILK PPA: 124
- SIMP PPA: 95
- SAGE: 124
- BLEND: 113
Troy Brown Jr.
Wizards fans are divided on Brown. Some thing he’s “just a guy” others think he’s a good player with a chance to improve. Head coach Scott Brooks seems more in the “just a guy” camp — I’m on the “good player” side. It’s a little weird how firmly and early “we” categorize players. Brown is still just 21 years old and is entering his third season — both are times when players frequently make significant leaps in production.
- Last PPA: 96
- DOPP PPA: 113
- MILK PPA: 125
- SIMP PPA: 85
- SAGE: 145
- BLEND: 117***
Sheppard got Bertans for free in a trade last offseason and re-signed him to a five-year, $80 million contract this year. Bertans is one of the best shooters on the planet with limitations in other areas. Still, that shooting has enormous value and he at least tries on defense.
- Last PPA: 105
- DOPP PPA: 96
- MILK PPA: 103***
- SIMP PPA: 101
- SAGE: 99
- BLEND: 100
Smith was solid for the Wizards last season and might be again. He’s also at that age where a significant drop-off could come without warning. All four forecasting approaches predict a decline in performance and most of his doppelgänger comps declined. The Wizards hedged on him a bit by signing Raul Neto.
- Last PPA: 92
- DOPP PPA: 73
- MILK PPA: 58
- SIMP PPA: 81***
- SAGE: 51
- BLEND: 65
Avdija looked skilled, big and confident in preseason. He was productive too, which is always nice. It’s difficult to forecast rookies. They usually struggle in that first season, and even a promising preseason doesn’t mean regular season success. For rookies, I use a weighted average of the five most recent players taken in their slot. I think he’ll outperform that 9th pick average. If he gets to league average (100 PPA), it adds a win to the team’s forecasted wins (depending on playing time).
- PROJECTED PPA: 60
I don’t expect Robinson to play much unless the team has a rash of injuries or COVID-19 cases. The team has several better options at wing — Brown, Bonga, Garrison Mathews, Neto — who should be in line ahead of him. I know there’s a popular narrative that he broke out in the bubble, but it just isn’t true. The doppelgänger forecast is the most optimistic but still has him around replacement level.
- Last PPA: 24 (46 using just his time with the Wizards)
- DOPP PPA: 51
- MILK PPA: 27
- SIMP PPA: 21
- SAGE: 24
- BLEND: 31***
Wagner is an interesting mix — skilled performer who can shoot from range and has the ability to finish around the basket along with a penchant for dumb and overly aggressive fouls and mistakes. If he “gets it,” he could be a productive backup big man. If not, he’ll probably bounce around the league for a few years because he has enough talent to intrigue.
- Last PPA: 61
- DOPP PPA: 81
- MILK PPA: 70***
- SIMP PPA: 51
- SAGE: 59
- BLEND: 65
I’ve written a few times about my objections to using the MLE to sign Lopez. I understand the reasoning — led the league in boxing out, good at rim protection, his defense lowers opponent shooting efficiency — but a) he was really bad overall last season (38 PPA), and b) despite those relative strengths, his overall impact on team defense and rebounding has been marginal over the past several seasons. Best case, his box outs clear the way for teammates to get more rebounds and his veteran presence helps Bryant and Wagner improve their defense and rebounding. None of the forecast approaches think he’s going to help much on the floor this season.
- Last PPA: 38
- DOPP PPA: 21
- MILK PPA: 24
- SIMP PPA: 64
- SAGE: 40
- BLEND: 37***
Neto looked decent in preseason action, but it’s worth keeping in mind that he’s 27 years old, he’s played five NBA seasons and more than 3,000 minutes, and his best season so far is a 72 PPA last year. Remember, in PPA, average is 100. He’s a decent shooter and good defender and should play ahead of Robinson. If Smith slips, I could see Neto taking over backup duties as the season progresses.
- Last PPA: 72
- DOPP PPA: 65
- MILK PPA: 71
- SIMP PPA: 70
- SAGE: 69
- BLEND: 69***
Good defender who has 3&D potential if he can increase volume and improve a bit in accuracy. He could end up anywhere from starting to out of the rotation. Hachimura’s eye infection probably gets him some extra minutes early in the season. I buy into the idea that he’s more valuable as a starter than coming off the bench because his offensive deficiencies get papered over by Beal, Westbrook and Bryant. Bonga is just 21 years old, and players that young typically improve.
- Last PPA: 83
- DOPP PPA: 93***
- MILK PPA: 120
- SIMP PPA: 83
- SAGE: 120
- BLEND: 104
The only other player worth forecasting might be Garrison Mathews, who posted a 70 PPA in just 227 minutes last season. Projecting what he’ll do this season is hampered by two things: 1) the tiny sample size from last year, and 2) the fact that he probably won’t be in the rotation. For some reason, the Wizards seem to have him behind Robinson. Mathews has a projected PPA around 80 — I use “around” because of the uncertainty caused by the low playing time last season. He has potential to be an outstanding shooter, if he gets minutes.
It’s unlikely that the Wizards will be outright terrible this season. A lot would need to go wrong, such as Beal suffering a significant injury.
Unlike last season, the record matters. The Wizards want back into the playoffs, and I think chances are excellent they’ll at least make the play-in games. While improved from a year ago, they’re still likely behind the Milwaukee Bucks, Boston Celtics, Miami Heat, Philadelphia 76ers, Brooklyn Nets, Toronto Raptors and Indiana Pacers. That puts them in a mix with the Orlando Magic, Atlanta Hawks and Charlotte Hornets for 8th, 9th and 10th.
Here are forecasted wins using each of the approaches I described above:
- DOPP: 32.8 — .455 winning percentage — 82 games quality: 37 wins
- MILK: 33.4 — .464 winning percentage — 82 games quality: 38 wins
- SIMP PPA: 32.4 — .450 winning percentage — 82 games quality: 37 wins
- SAGE: 35.0 — .486 winning percentage — 82 games quality: 40 wins
Using the best-case forecast for each player gets the team to 37.7 wins. That would be a .523 winning percentage, about the quality of a 43-win team over an 82-game schedule.
These forecasting approaches produce a similar picture of the team’s overall quality. If things go just right and they get lucky, they could win 38-39 games and get as high as 7th in the East. If things don’t go as well, they could win as few as 29 games and even miss rhe play-in games.
Final Prediction: 33-39, which will land them 9th and give them at least one play-in game.