Tag: Washington Wizards

Wizards Update: Is Wall A Top 5 PG?

Now in his fifth year, Wizards PG John Wall is having the best season of his career. He’s drawn accolades from observers around the league, and some Washington fans have even started wondering if he might be a fringe MVP candidate. The MVP talk and the “he’s the best PG in the league” assertions are premature, however. He’s terrifically productive, but there’s still room for significant improvement.

Put away the pitchforks and torches. While Wall isn’t quite where fans want to place him, this is really good news for the Wizards. He’s a phenomenal player whose best days are likely still in the future.

While Wall’s passing and offensive creativity elicits praise, his greatest contribution is on the defensive end. In the defense part of my metric (Player Production Average — PPA for short), Wall rates as the league’s best defensive PG. That’s not a typo. Number one. Top of the heap. Nobody better. That finding is echoed by ESPN’s Real Plus Minus stat. If the season ended today, he’d be on my first-team All-Defense ballot.

As head coach Randy Wittman told the Sports Junkies this morning, Wall has all the attributes of an outstanding defender — size, quickness, speed, strength, length. And while he’s rated as a good defender in my system in previous years, he’s made the defensive leap this season with suffocating on-ball pressure, hard close-outs on shooters, and impeccable timing in the passing lanes.

The Los Angeles Clippers, led by elite PG Chris Paul, struggled to get into their offensive sets early in Washington’s win last week because of Wall’s pressure. Consider this: Paul has 49 total turnovers this season. Six of them came against the Wizards.

By now you’re probably wondering: If Wall’s so great on defense and he’s such a great passer and the Wizards are winning, why don’t you agree he’s an MVP candidate? Why are you about to tell me he’s not a top five PG?

Which brings me back to a junk metric I created last season: Only Good Stuff. In its simplest form, OGS is points + rebounds + assists + steals + blocks.

Wall is among the game’s more active players when he’s out there. He produces lots of OGS — 7th most in the league, in fact. Here’s the top 10 in OGS:

  1. James Harden — 977
  2. Anthony Davis — 940
  3. Stephen Curry — 922
  4. Kobe Bryant — 917
  5. Lebron James — 917
  6. LaMarcus Aldridge — 869
  7. John Wall — 867
  8. Blake Griffin — 843
  9. Kyle Lowry — 361
  10. Damian Lillard — 835

That’s a pretty impressive group, and Wall sits second among PGs. But, it’s ONLY the good stuff. What if we look at the other side of the ledger — Only Bad Stuff (missed field goal attempts + 0.5 x missed free throw attempts + turnovers + fouls)? Well, Wall’s near the top of that list too — 6th most OBS. The bottom 10:

  1. Kobe Bryant — 502
  2. James Harden — 422
  3. Monta Ellis — 389
  4. Josh Smith — 387
  5. Carmelo Anthony — 384
  6. John Wall — 367
  7. Tyreke Evans — 365
  8. Kyle Lowry — 361
  9. Blake Griffin — 360
  10. Stephen Curry — 351

So, with Wall (and several other of the game’s outstanding players), lots of good AND lots of “bad.” What if we combine the two? Because the categories aren’t weighted based on how much they contribute to winning, let’s call this last category Unweighted Total Stuff (UTS) — OGS – OBS. Here’s the top 10:

  1. Anthony Davis — 687
  2. Stephen Curry — 571
  3. Lebron James — 559
  4. James Harden — 555
  5. Chris Paul — 523
  6. LaMarcus Aldridge — 523
  7. Marc Gasol — 512
  8. Tyson Chandler — 505
  9. John Wall & Damian Lillard — 501
  10. Blake Griffin — 484

Enough with the “stuff,” according to PPA (which is pace neutral, accounts for defense, and includes a degree of difficulty factor), Wall currently sits 8th among PGs on a per minute basis. Westbrook, Curry and Paul are clearly the top three. Lillard is next. Then it’s a tight group of Jeff Teague, Lowry, Mike Conley and Wall.

The scores of Wall’s group are close enough that I’d classify them as “about the same” and reasonable minds can differ on what order they should be in. I won’t argue if you want to push Wall to fifth, though I don’t see justification for ranking him higher at this point.

As mentioned above, Wall rates as the best defender — Lowry and Conley rate as average; Teague as a good-not-outstanding defender. However, Wall is the least efficient on offense among the top PGs by approximately 8 points per 100 possessions.

In TOTAL production, Wall currently sits 5th behind Curry, Paul, Lillard and Lowry. Kyrie Irving slips in ahead of Wall for fifth in per game PPA.

What can Wall do to improve? Shoot better and commit fewer turnovers.

How good has Wall been in December? His PPA for the month is 219 so far. If that was his PPA for the season, he’d rank 4th among PGs, ahead of Lillard, but still behind Westbrook, Curry and Paul.

To this week’s PPA update…

PPA is an overall rating stat I developed that credits players for things they do that help a team win and debits them for things that hurt the cause. PPA is pace neutral, accounts for defense, and includes a “degree of difficulty” factor based on the level of competition a player faces while on the floor. In PPA, 100 = average, higher is better and replacement level is 45.

PLAYER GMS MPG 10-Nov 18-Nov 24-Nov 3-Dec 8-Dec PPA
Marcin Gortat 19 30.2 181 186 170 175 179 178
John Wall 19 35.9 185 180 180 168 167 175
Paul Pierce 19 27.3 140 138 165 134 134 154
Rasual Butler 15 21.6 60 131 116 128 155 140
Andre Miller 19 12.4 72 69 92 103 102 101
Kris Humphries 18 22.0 46 87 90 82 109 100
Nene Hilario 13 33.2 108 102 68 67 83 94
Bradley Beal 10 24.6 122 63 69 94
Garrett Temple 17 17.0 121 112 96 100 98 91
Otto Porter 18 20.1 97 106 101 95 84 81
Drew Gooden 12 15.9 42 40 59 78 64 47
Kevin Seraphin 18 15.3 38 13 17 12 28 34
DeJuan Blair 6 4.6 -41 -40 -40 -74 -56 -47
Glen Rice 5 8.6 -120 -117 -117 -117 -114 -113

The Paul Pierce signing looks better and better. The last time Pierce was this productive was the 2011-12 season. His efficiency numbers have surged as the SF has found the Fountain of Youth. One potential warning sign is a slip in his defensive impact since the season’s opening weeks. After rating solidly above average earlier in the year, he’s down to average in my most recent update.

Andre Miller is another of the Wizards ancients who continues to perform well. The team plays dramatically different when he replaces Wall in the lineup (they slow by 10 possessions per 48 minutes), but they’re crazy efficient when he’s out there. It seems like every game is a masterclass for how to get to the rim despite running in slow motion.

Statistical tidbit: so far this season, Wall is averaging 14.8 assists per 100 possessions. Miller is averaging 14.4.

Beal and Nenê increased production after a couple rough weeks. I hope Wittman continues to use Nenê off the bench where he can face opponent reserves when Washington is on offense, and anchor a weak defensive second unit.

Kevin Seraphin was up for a second straight week. His rebounding has improved the past couple weeks, though his offensive efficiency remains poor. Among the team’s regulars, he’s in a virtual tie with Miller as the least effective defender.

Wizards Update: Two Steps Forward, One Step Back

rasual

Over the past week, the Wizards rolled to convincing wins over the hapless Lakers and the not-awful Nuggets, and then lost a shoulda-won game against a middling Celtics squad. And, in the grand tradition of players having good games shortly after I rip them, Kevin Seraphin had probably his best game of the year against Denver.

Meanwhile, John Wall climbed into a tie with Rajon Rondo for having the biggest defensive impact for a point guard in my rating system. Wall shows up in my numbers as having the biggest defensive impact on the Wizards so far this season. Not bad for a guy who I still think has room for improvement on the defensive end.

Other positive defenders: Marcin Gortat, Nenê, Kris Humphries, and Garrett Temple.

The “about average” grouping includes: Otto Porter, Rasual Butler and Paul Pierce. Pierce, had gotten off to an excellent start defensively, but his individual performance seems to have slipped a bit over the past couple weeks.

Bradley Beal and Drew Gooden are in the “bad defensive impact” category so far. Kevin Seraphin and Andre Miller are defensive dumpster fires to this point in the year.

Below is the Player Production Average (PPA) update. PPA is an overall rating stat I developed that credits players for things they do that help a team win and debits them for things that hurt the cause. PPA is per-minute, pace neutral, accounts for defense, and includes a “degree of difficulty” factor based on the level of competition a player faces while on the floor. In PPA, 100 = average, higher is better and replacement level is 45.

PLAYER GMS MPG 10-Nov 18-Nov 24-Nov 3-Dec PPA
Marcin Gortat 19 30.5 181 186 170 175 179
John Wall 19 35.3 185 180 180 168 167
Rasual Butler 15 20.3 60 131 116 128 155
Paul Pierce 19 26.6 140 138 165 134 134
Kris Humphries 18 19.7 46 87 90 82 109
Andre Miller 19 12.6 72 69 92 103 102
Garrett Temple 17 20.2 121 112 96 100 98
Otto Porter 18 21.9 97 106 101 95 84
Nene Hilario 13 25.5 108 102 68 67 83
Bradley Beal 10 30.4 122 63 69
Drew Gooden 12 17.3 42 40 59 78 64
Kevin Seraphin 18 15.2 38 13 17 12 28
DeJuan Blair 6 5.7 -41 -40 -40 -74 -56
Glen Rice 5 8.6 -120 -117 -117 -117 -114

The first thing I wondered about when perusing the table above was the lack of change in Wall’s PPA. My feeling was that he had a terrific week. But, the game log shows that he shoot poorly (efg of just .395) and that he committed 14 turnovers.

Rasual Butler had another week of outlandishly good shooting. In non-shooting categories, Butler’s numbers are all within established career norms. So far in Washington, he’s shooting .579 from 2pt range (vs. a career average of .435), and .545 from 3pt range (vs. a career average of .364).

I know fans want to attribute this to The Wall Effect, but a) only about half Butler’s minutes have been with Wall; b) he’s shooting with outlandish accuracy (and more often) when Wall’s on the bench; and c) his shooting numbers in Indiana last season were also significantly better than his previous career norms.

Butler efg usg
with Wall .765 13.8%
w/o Wall .700 20.3%

It may simply be that Butler worked hard and improved his shooting late in his career. And, it may be that he’s ripe for a regression. Sample sizes are still small: just 304 minutes and 112 shot attempts so far this season.

I’d like to see the Wizards continue to start Humprhies and bring Nenê off the bench. The starting lineup doesn’t appear to have suffered with the change, which isn’t surprising considering how little Nenê was producing. I suspect Nenê’s production will improve going against bench bigs. And, bringing him off the bench, gives the coaching staff options at PF and C, which means they can drop Seraphin from the rotation.

Despite the loss to Boston, the week was a positive one for the Wizards. Good teams win games convincingly. They don’t necessarily have the best record in close games, because they often avoid close games in the first place. That Washington won three in a row (including the win against Miami) by double digits may be a marker of the team getting stronger.

Projection: Wizards Will Win 45 and Return to the Playoffs

Improvement from the Washington Wizards youngsters, and an infusion of frontcourt depth will be offset by missed time due to injuries and declines from the team’s older players to keep the team in the middle of the NBA pack for another year. However, the team could be a dangerous playoffs matchup if they’re able to enter the postseason healthy.

Below, I’m offering up projections done a couple different ways. The first is built on the similarity scores I’ve posted after the past week. This approach finds players in NBA history with similar production at a similar age, and then looks at what they did in subsequent seasons. Those findings are then applied to the Wizards roster and combined with a playing time estimate for each player.

For this estimate (and the other one, which I’ll get to later in this post), I’ve used my overall metric Player Production Average (PPA), which is calibrated to explain individual player contributions to winning and losing. PPA is pace neutral, accounts for defense, and includes a “degree of difficulty” factor based on the level of competition a player faces while on the court. In PPA, 100 = average, higher is better, and 45 = replacement level.

Statistical Doppelganger Projection

POS PLAYER MIN LAST SEASON PPA PROJECTED PPA PROJECTED kWins
PG John Wall 2812 139 156 9.0
C Marcin Gortat 2464 154 132 6.7
SG Bradley Beal 2325 96 112 6.1
SF Paul Pierce 1800 139 108 4.0
SF Otto Porter 1800 15 85 3.2
PF Kris Humprhies 1608 132 133 4.4
F/C DeJuan Blair 1450 97 97 2.9
PF Nenê 1430 102 90 2.7
PG Andre Miller 1165 86 65 1.6
G/F Glen Rice Jr. 1029 20 78 1.2
F/C Drew Gooden 1002 106 100 2.1
G/F Martell Webster 1000 77 74 1.5
POS TEAM 19885 107 110 45.4

MIN = projected TOTAL minutes for the upcoming season

Projected kWins = how many wins that player will contribute based on his projected PPA and projected total minutes.

Over the past few seasons, the Wizards’ front office has converted the team from being one of the league’s youngest to being one of the league’s oldest. Gortat, Nenê, Pierce, Gooden and Miller all figure to play prominent roles this season, and all are past 30. Well past 30 for Pierce and Miller.

Projections for Porter and Rice were difficult because they played so little last season. For both, I elected to throw out their rookie numbers and rely instead on projections based on the rookie seasons of the players they were most like from college. Using the rookie numbers would lower Porter’s projected PPA to 66 and Rice’s to 30. That would drop Washington’s projected win total 43.8.

Note that I didn’t include Kevin Seraphin, Garrett Temple or Rasual Butler in the above table. They’ll get some minutes along the way, but — barring several catastrophic injuries — none should see enough court time to have a major effect on the team’s fortunes. For those interested, this is what I project for the end-of-the-bench trio:

  • Garrett Temple: 33
  • Kevin Seraphin: 49
  • Rasual Butler: 55

I can hear the cockeyed optimists already: “Why do you just assume the old guys will get worse? What if they maintain for a year?” Quick answer (and one I’ve given before): athletes past 30 tend to two things — get hurt and get worse.

But, let’s say the “Ancients” are able to do this season what they did last year. In that event, Washington’s projected win total would climb to 48.5. Which would be hella fun.

On the other hand, there are scenarios where there are more injuries than expected, younger players don’t make anticipated improvements and/or older players decline more steeply. That gives a potential “bottom” of 40.7 wins.

Simple Rating System Projection

POS PLAYER MIN LAST SEASON PPA SRS PROJECTED PPA PROJECTED kWins
PG John Wall 2812 139 143 8.3
C Marcin Gortat 2464 154 144 7.3
SG Bradley Beal 2325 96 111 5.3
SF Paul Pierce 1800 139 117 4.3
SF Otto Porter 1800 15 63 2.3
PF Kris Humphries 1608 132 133 4.4
F/C DeJuan Blair 1450 97 135 4.0
PF Nene Hilario 1430 102 102 3.0
PG Andre Miller 1165 86 108 2.6
G/F Glen Rice 1029 20 82 1.7
F/C Drew Gooden 1002 106 118 2.4
G/F Martell Webster 1000 77 102 2.1
G/F Rasual Butler 0 63 81 0.0
C Kevin Seraphin 0 35 53 0.0
G Garrett Temple 0 24 54 0.0
POS TEAM 19885 107 117 47.9

The guys over at Basketball-Reference have up Simple Rating System projected stats for everyone who played in the NBA last season. Go here for an explanation. They don’t estimate minutes, which I can understand because it’s frigging hard to do.

The SRS approach is more optimistic than the one I used — at least at the bottom line. SRS generally predicts less of a decline for older players, but also not as much improvement from the younger ones. The SRS approach would suggest the Wizards will win 48 games this season — with a low end prediction of 43 and a high of 52.

Here’s a table comparing results from the two approaches:

POS PLAYER DOPP PPA SRS PPA DOPP kWINS SRS kWINS
PG John Wall 156 143 9.0 8.3
C Marcin Gortat 132 144 6.7 7.3
SG Bradley Beal 112 111 6.1 5.3
SF Paul Pierce 108 117 4.0 4.3
SF Otto Porter 85 63 3.2 2.3
PF Kris Humprhies 133 133 4.4 4.4
F/C DeJuan Blair 97 135 2.9 4.0
PF Nenê 90 102 2.7 3.0
PG Andre Miller 65 108 1.6 2.6
G/F Glen Rice Jr. 78 82 1.2 1.7
F/C Drew Gooden 100 118 2.1 2.4
G/F Martell Webster 74 102 1.5 2.1
G/F Rasual Butler 55 81 0.0 0.0
C Kevin Seraphin 49 53 0.0 0.0
G Garrett Temple 33 54 0.0 0.0

DOPP PPA = projected PPA using the Statistical Doppelganger approach

SRS PPA = projected PPA using the Simple Rating System numbers published by Basketball-Reference

DOPP kWINS = projected individual wins contributed using the Statistical Doppelganger approach

SRS kWINS = projected individual wins contributed using the Simple Rating System numbers published by Basketball-Reference

Final Word

In the end, I’m using my own projection system. Last year, I projected the Wizards would win 43 — they won 44, albeit not exactly in ways that I expected. I’ve refined my projection system (I hope), although I’m hoping the team outperforms my prediction by a wide margin.

While still lacking an elite producer, the Wizards could be a tough out in the playoffs when rotations shorten and there’s more rest between games (especially in the first round). If they can get there healthy, of course.

I’m projecting the Wizards will win between 41 and 48 games this season. Final projection: 45 wins and the fifth seed in the Eastern Conference playoffs.

Wizards Doppelgangers: Bump and Bruise

NBA: Preseason-Washington Wizards at Chicago Bulls

So far, I’ve used my Statistical Doppelganger Machine to find “most similar” players in NBA history for the following:

Next through the machine: Bump (Kris Humphries, DeJuan Blair and Kevin Seraphin), and Bruise (Martell Webster).

For those interested, I discuss the method a bit in the first post. Basically, the Machine looks for most similar production at a similar age.

First up: Humphries.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Kris Humphries PF 2013-14 28 BOS 100 132 146
Chris Wilcox PF 2010-11 28 DET 90 121 165
Lawrence Funderburke PF 1998-99 28 SAC 89 120 120
Mark Strickland F/C 1997-98 27 MIA 89 111 111
Tom Owens PF/C 1977-78 28 POR 89 126 149
Taj Gibson PF 2011-12 26 CHI 89 105 105
Antonio McDyess PF 2006-07 32 DET 88 115 175
Marcus Camby C 2002-03 28 DEN 88 131 212
Will Perdue C 1994-95 29 CHI 88 140 140
Loy Vaught PF 1992-93 24 LAC 87 99 131
Clarence Weatherspoon PF 1999-00 29 MIA 87 108 168

What Humphries did last season generates a nice list of solidly productive role playing bigs, which is about what I’d have expected. The group’s average peak performance is 147 — for Humprhies it’s 146. Average peak age for this group was 26.5 — Humprhies appears to have peaked at 25. I say “appears” because Humphries, of course, is still going.

In the seasons after those shown here, the similars were a mixed bag of ups and downs. As a group, they were steady. This suggests that Humphries may be in the “plateau” portion of his career production arc. (That arc typically follows a trendline of improving production early in a player’s career to a peak between ages 25 and 28, a plateau until the early 30s, and then decline.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
DeJuan Blair PF 2013-14 24 DAL 100 97 145
Dennis Rodman* F 1986-87 25 DET 90 84 180
Craig Smith PF 2006-07 23 MIN 90 87 91
Matt Geiger F/C 1993-94 24 MIA 89 87 153
Gary Trent PF 2002-03 28 MIN 88 103 133
Channing Frye PF 2007-08 24 POR 88 77 118
Jerome Whitehead C 1982-83 26 SDC 88 104 128
Alan Henderson PF 1996-97 24 ATL 88 67 116
Robert Traylor C 2003-04 26 NOH 88 79 143
Greg Ballard SF 1978-79 24 WSB 88 114 157
Ivan Johnson PF 2011-12 27 ATL 88 73 83

I very much like seeing Dennis Rodman’s name on the list, although this is the pre-RODMAN Rodman. This was actually Rodman’s rookie season, and while he rebounded well, he wasn’t yet the outlandish board man he’d later become. This Rodman was even willing to shoot the ball now and then — he used roughly 19% of his team’s possessions while on the floor (average is 20%).

The rest is kind of an odd group at first glance. There are physical, burly types like Smith, Trent, Traylor and Johnson, and more finesse types Frye, Henderson and Geiger.

You may be wondering what Frye is doing on this list at all. But, this isn’t the stretch-4 Frye, this is the PF/C type in his second to last year in Portland. He had just 10 three-point attempts that season with the Blazers. Two years later, he’d hoist 392 for the Suns.

The average peak PPA for this group was 132 at age 25.6. Blair’s best season was a 145 as a rookie, but he’s just 25 years old this season. This group of similars was a mix of improvement and decline in the year following the one shown.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Kevin Seraphin C 2013-14 24 WAS 100 35 95
Stanislav Medvedenko PF 2002-03 23 LAL 90 17 84
Mark Alarie PF 1987-88 24 WSB 88 42 77
Keith Lee F/C 1986-87 24 CLE 87 55 77
Bill Martin SF 1985-86 23 IND 86 34 34
Greg Foster F/C 1990-91 22 WSB 86 36 42
Malik Allen PF 2006-07 28 CHI 86 35 76
Channing Frye PF 2008-09 25 POR 86 27 118
Melvin Turpin C 1986-87 26 CLE 86 50 130
Josh Powell PF 2008-09 26 LAL 86 29 61
Brad Lohaus F/C 1987-88 23 BOS 85 49 93

I know there’s a lot of hope that Seraphin may finally have a breakout season. Even before looking at his comps, I’d have recommended betting against that “breakout.” This list only solidifies that recommendation.

To me, Seraphin is a reflection of how brutal the NBA can be. He’s one of the better basketball players in the world — top 600, easy. Maybe top 500. But, he hasn’t been good enough to be a bona fide NBA player.

No matter what slice of time I examine, I keep finding the same problems with Seraphin’s play: too many turnovers, too few rebounds, rampant fouling. That was true, even during his “good” stretch a few years ago when he performed at about the level of an average NBA player. Since then, he’s been awful. The league’s least productive center two years ago. The second least productive center last season.

This group of similars can be characterized as peaking early (age 24.8) and low (average peak PPA: 81). The best of the group was Mel Turpin. That Frye season was his last in Portland, and the worst of his career.

The good news is that most of these players improved the season following the one that appears on the list. The bad news: the average improvement wasn’t much.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Martell Webster SF 2013-14 27 WAS 100 77 114
Keith Bogans SG 2007-08 27 ORL 95 81 89
Morris Peterson SF 2003-04 26 TOR 90 86 111
Richard Jefferson SF 2011-12 31 SAS/GSW 90 93 162
Rasual Butler G/F 2006-07 27 NOK 90 61 89
Pat Garrity SF 2002-03 26 ORL 89 79 89
Matt Carroll SF 2007-08 27 CHA 89 59 105
Brandon Rush SG 2010-11 25 IND 89 66 106
Quentin Richardson SG 2008-09 28 NYK 89 82 123
Gordan Giricek SF 2003-04 26 ORL 88 71 99
Ryan Gomes SF 2009-10 27 MIN 88 83 119

Webster will be out for a significant chunk of the season after back surgery during the summer. His list of similars is an unsurprising mix of role-playing G/F types. This group’s average peak was at age 26.7 — Webster is 28 and appears to have peaked at 26 (his first year in DC). The average peak PPA was 110 — barring a miraculous recovery, Webster’s was 114.

The guys on this list tended to decline a bit the following season, though not much. Assuming Webster gets healthy, it’s reasonable to expect him to play about as well as he did last season.

Just for those who might be interested, here are the “similars” for Trevor Ariza and Trevor Booker, the team’s significant free agent losses:

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Trevor Ariza SF 2013-14 28 WAS 100 145 145
Nick Anderson SG 1995-96 28 ORL 93 151 164
Bryon Russell SF 1998-99 28 UTA 88 128 128
Bryon Russell SF 1999-00 29 UTA 88 127 140
Hersey Hawkins G/F 1995-96 29 SEA 88 148 173
Kerry Kittles SF 2003-04 29 NJN 88 136 179
Hersey Hawkins SG 1994-95 28 CHH 88 148 173
Brent Barry SG 1999-00 28 SEA 87 132 183
Dan Majerle SG 1992-93 27 PHO 87 133 135
Wesley Person SG 1997-98 26 CLE 87 150 150
Rashard Lewis PF 2007-08 28 ORL 87 138 165
PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Trevor Booker PF 2013-14 26 WAS 100 123 123
Gustavo Ayon PF 2011-12 26 NOH 90 134 134
Luc Mbah a Moute PF 2011-12 25 MIL 90 106 106
Chucky Brown PF 1995-96 27 HOU 90 117 117
Kent Benson C 1983-84 29 DET 89 119 137
Ben Poquette PF 1981-82 26 UTA 89 100 106
Rasho Nesterovic C 2006-07 30 TOR 89 120 140
Tyrone Corbin SF 1988-89 26 PHO 89 110 126
Nenad Krstic C 2009-10 26 OKC 89 107 118
Jason Thompson PF 2011-12 25 SAC 89 130 130
Olden Polynice C 1991-92 27 LAC 89 114 127

And finally, here’s the “All-Sims” team, so to speak. The method here is to take the guy from the top of each player’s list:

POS Wizards Similars
PG John Wall Kemba Walker
SG Bradley Beal Brandon Jennings
SF Paul Pierce Toni Kukoc
PF Nenê Danny Manning
C Marcin Gortat Bill Laimbeer
BENCH
PG Andre Miller Rod Strickland
SG Martell Webster Keith Bogans
SF Otto Porter Lance Stephenson
PF Kris Humphries Chris Wilcox
C DeJuan Blair Dennis Rodman
G/F Glen Rice Jr. Scott Padgett
G/F Rasual Butler Steve Kerr
C Kevin Seraphin Stanislav Medvedenko
THE DEPARTED
SF Trevor Ariza Nick Anderson
PF Trevor Booker Gustavo Ayon

Wizards Doppelgangers: The Enigmas

otto porter

In case you missed them, I’ve done two installments using my Statistical Doppelganger Machine to look at the player seasons most similar to Wizards (similar production at similar age):

Here’s a look at low-minute Wizards for whom finding comps was challenging because of their scant playing time: Otto Porter, Glen Rice Jr., and Garrett Temple.

Let’s start with the guy likely to play the biggest role for the team this season: Porter.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Otto Porter SF 2013-14 20 WAS 100 15 15
Lance Stephenson SG 2011-12 21 IND 87 14 116
Cory Joseph SF 2011-12 20 SAS 86 18 94
Jumaine Jones SF 2003-04 24 BOS 86 24 98
Quincy Pondexter SF 2010-11 22 NOH 86 38 67
Shawne Williams SF 2006-07 20 IND 85 39 53
Kareem Rush SG 2002-03 22 LAL 85 3 53
Brandon Bass PF 2005-06 20 NOK 85 37 116
Kevin Martin SG 2004-05 21 SAC 84 32 162
Kedrick Brown SF 2002-03 21 BOS 84 44 97
Gerald Henderson SG 2009-10 22 CHA 84 36 99

Wizards fans know Porter had what amounts to a lost rookie season. He missed training camp with a hip injury, barely played, and was terrible when he did play. When I post my projections Wednesday, I’ll go through a couple different ways I dealt with predicting his performance, but the exercise today is NBA similars.

The list of similars was something of a pleasant surprise. It’s basically a list of players who had a disastrously bad season and then (for the most part) went on to become contributors. That said, “contributors” is a broad term. As a group, Porter’s similars tended to peak young (average age 23.4) and low (average peak PPA: 88). But, they all improved the following season — generally by a bunch.

And, the list includes Kevin Martin, who’s been a good player for nearly a decade, and Lance Stephenson who became an above average performer this season — and is likely to continue improving.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Glen Rice Jr. SG 2013-14 23 WAS 100 20 20
Scott Padgett PF 1999-00 23 UTA 90 20 96
Will Barton G/F 2012-13 22 POR 87 28 60
Quincy Douby SF 2006-07 22 SAC 86 34 34
Orlando Johnson SG 2012-13 23 IND 85 60 60
Reggie Jackson G 2011-12 21 OKC 84 32 101
Bostjan Nachbar SF 2003-04 23 HOU 84 24 84
Ronnie Price G 2006-07 23 SAC 84 40 54
Thabo Sefolosha SG 2006-07 22 CHI 84 31 129
Nolan Smith G 2011-12 23 POR 84 10 10
Kevin Brooks SF 1992-93 23 DEN 84 18 34

While Porter’s comps were somewhat comforting, it’s difficult to say the same about Rice’s. Like Porter’s list, Rice’s similars tended to peak early (average age: 24.0), but even lower (average peak PPA: 62). But, Will Barton and Reggie Jackson are both still works in progress. And, a few more had a productive season or two in which they helped their team, and one (Sefolosha) became a decent role-playing starter.

All that said, Rice played just 109 total minutes last season. The players who performed like him (similar age, similar production) isn’t a list all-time greats, but that shouldn’t be expected from a second round pick. There’s little reason to think Rice will be unable to work himself into being a contributor.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Garrett Temple G 2013-14 27 WAS 100 24 60
Rick Carlisle G 1985-86 26 BOS 89 28 28
Pace Mannion SF 1987-88 27 MIL 88 30 61
Pace Mannion SF 1983-84 23 GSW 88 32 61
David Wingate SG 1994-95 31 CHH 88 32 89
Dudley Bradley SG 1985-86 28 WSB 86 60 102
Jason Hart PG 2005-06 27 SAC 86 13 119
Ronnie Price PG 2012-13 29 POR 86 14 54
Randy Brown PG 1995-96 27 CHI 86 50 86
Royal Ivey PG 2006-07 25 ATL 86 38 38
Reece Gaines PG 2003-04 23 ORL 85 11 20

Temple may have been the most difficult player to project because so many of the guys who produced like he did last season didn’t have a follow-up year. In other words, the league took a collective look at players like Temple, and decided to sign Someone Else.

Players like Temple peaked low (average peak PPA: 65) and fairly young (25.5). Two of the 10 most similar got significantly worse the following season, four got better, and four stayed about the same. The list certainly doesn’t offer much hope for improvement.

Later today: Bump and Bruise.

Wizards Doppelgangers: The Ancients

nene fights

In the classic mode of a franchise finished with rebuilding, and ready to repeat their overwhelming success of the previous season, the Washington Wizards went out this offseason and got older. Yes, I’m sure they’d much prefer if we all thought of it as adding “veterans,” and that’s a fine way of looking at it, if you like.

Understand, I’m not against “veterans,” I’m just aware of the reality that athletes over 30 years old typically do two things: get hurt and get worse. Hopefully, Father Time will give the Wizards a reprieve until the summer of 2016 when Kevin Durant is a free agent.

It could happen.

Last week, I ran the Wizards young backcourt (John Wall and Bradley Beal) through my statistical doppelganger machine. Today, let’s look at the oldsters Washington has added in recent years: Nenê, Marcin Gortat, Paul Pierce, Andre Miller, Drew Gooden and Rasual Butler. (Please take a look back at that link above for notes about the method.)

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Nenê PF 2013-14 31 WAS 100 102 176
Danny Manning PF 1996-97 30 PHO 90 107 157
Clifford Robinson PF 1997-98 31 PHO 90 131 143
Ruben Patterson SF 2006-07 31 MIL 89 126 165
Mickey Johnson PF 1983-84 31 GSW 88 83 145
Elton Brand PF 2009-10 30 PHI 87 100 224
Christian Laettner PF 1997-98 28 ATL 87 127 146
Jermaine O’Neal C 2008-09 30 TOR/MIA 87 93 166
Matt Harpring SF 2005-06 29 UTA 87 105 161
Frank Brickowski C 1992-93 33 MIL 87 117 123
Antoine Carr PF 1992-93 31 SAS 87 106 109

The good news is that these doppelgangers were pretty good players. Nenê had the second highest peak PPA behind Elton Brand’s 224. He also peaked about a year later than the average for this group. Frank Brickowski and Clifford Robinson each peaked past 30.

But, Nenê’s production has slipped the past couple years, as has his availability, and there isn’t much reason to think he’ll regain something close to that peak performance. His comps offer an ideal optimist vs. pessimist test: five of his ten most similar players performed better the following season, give performed worse.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Marcin Gortat C 2013-14 29 WAS 100 154 186
Bill Laimbeer C 1986-87 29 DET 93 154 175
Mike Gminski C 1989-90 30 PHI 90 129 170
Bill Laimbeer C 1988-89 31 DET 90 144 175
Dave Robisch C 1979-80 30 CLE 90 132 132
P.J. Brown PF 1998-99 29 MIA 89 127 150
Bill Laimbeer C 1985-86 28 DET 89 156 175
Billy Paultz C 1977-78 29 SAS 89 164 164
Tom Gugliotta PF 1999-00 30 PHO 89 147 176
Maurice Lucas PF 1981-82 29 NYK 89 149 149
Luis Scola PF 2008-09 28 HOU 88 143 143

Obviously, Gortat isn’t really an “ancient.” He’s just 30 years old, he’s played relatively few minutes for a player his age, and he’s a fitness fanatic. But, eight of the ten most similar seasons to the one Gortat posted last year were followed by a less productive season.

If I throw out the two least similar seasons from Laimbeer, each of the 10 seasons most similar to Gortat last season were followed by a season that was less productive. Bright side here: it’s not like these comps became catastrophic failures. In general, they remained productive…just not quite as good.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Paul Pierce SF 2013-14 36 BRK 100 131 173
Toni Kukoc PF 2002-03 34 MIL 85 113 164
Vince Carter SF 2012-13 36 DAL 84 107 200
Chris Mullin* SF 1997-98 34 IND 84 156 182
Sam Perkins PF 1996-97 35 SEA 84 119 147
Bob Lanier* C 1983-84 35 MIL 83 152 138
Chris Mullin* SF 1998-99 35 IND 83 168 182
Sam Perkins PF 1994-95 33 SEA 83 132 147
Sam Perkins PF 1995-96 34 SEA 82 114 147
Chucky Atkins PG 2006-07 32 MEM 82 111 111
Terry Porter PG 1998-99 35 MIA 82 114 211

Gotta say that Pierce’s set of doppelgangers may be the weirdest assemblage of players I’ve gotten from The Machine. I think the challenge here is that not very many players even last to age 36 (plus), so the pool is shallow. Note that Pierce’s most similar player has a Sim Score lower than the 10th most similar for Wall, Beal, Nenê and Gortat. In other words, the list above are kinda similar, but not super close.

Overall, this is a terrific group of players that tended to peak young (around age 25-26 — Pierce peaked at 24), but had long-lasting careers. As would be expected for a group of mid-30s athletes, most declined the following season. However, most remained decent players for another year or two.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Andre Miller SG 2013-14 37 TOT 100 89 172
Rod Strickland PG 2003-04 37 ORL/TOR 90 81 176
Terry Porter SF 2001-02 38 SAS 88 87 211
Mark Jackson PG 2002-03 37 UTA 86 66 181
Don Buse PG 1983-84 33 KCK 86 96 148
Toni Kukoc SF 2004-05 36 MIL 85 84 164
Muggsy Bogues PG 1998-99 34 GSW 85 111 153
Maurice Cheeks PG 1992-93 36 NJN 85 89 180
Rod Strickland PG 2002-03 36 MIN 85 95 176
Gary Grant PG 1997-98 32 POR 84 108 115
Rickey Green PG 1991-92 37 BOS 84 57 157

Miller’s comps are an interesting assemblage of good-to-great players. I was surprised to see Muggsy Bogues make the list, primarily because I’d forgotten the 5-3 Bogues played so many seasons. Just about everyone on this list had a good career, but…as should be expected for a group this old — all 10 either declined or were out of the league completely the following season.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Drew Gooden C 2013-14 32 WAS 100 106 169
Nazr Mohammed C 2010-11 33 CHA/OKC 86 98 150
Chris Wilcox PF 2010-11 28 DET 86 121 165
Antonio McDyess PF 2006-07 32 DET 86 115 175
Joe Smith PF 2005-06 30 MIL 85 89 143
Nazr Mohammed C 2009-10 32 CHA 85 150 150
Antonio McDyess PF 2005-06 31 DET 85 91 175
Jermaine O’Neal C 2012-13 34 PHO 83 83 166
Chris Kaman C 2012-13 30 DAL 83 101 130
Frank Brickowski PF 1991-92 32 MIL 83 107 123
Chris Gatling PF 1995-96 28 GSW 83 82 131

For Gooden, I wonder whether these comps are particularly meaningful given that he was signed late in the season and played in fairly few games. This group basically split between those who declined the following season and those who got better. The net effect is that the group average was “about the same.” So, it could be a case of lather-rinse-repeat with Gooden this season — albeit with more total minutes.

PLAYER POS SEASON AGE TEAM SIM SCORE PPA SEASON PPA PEAK
Rasual Butler SG 2013-14 34 IND 100 63 89
Steve Kerr PG 1999-00 34 SAS 92 59 124
Jalen Rose SF 2006-07 34 PHO 89 72 117
Matt Bullard PF 1998-99 31 HOU 87 49 98
Jaren Jackson SG 2000-01 33 SAS 87 44 90
Anthony Bowie SG 1997-98 34 NYK 86 72 97
Eric Piatkowski SG 2004-05 34 CHI 86 79 121
Rashard Lewis PF 2012-13 33 MIA 85 60 165
Steve Kerr PG 2001-02 36 POR 85 64 124
Eric Piatkowski SF 2007-08 37 PHO 84 34 121
Eric Piatkowski SG 2005-06 35 CHI 84 16 121

Last up for today: the 15th man, Rasual Butler. You’ll notice this list is heavy on Eric Piatkowski, which isn’t exactly a great thing. Piatkowski hung around into his late 30s for some reason I don’t remember. Perhaps he had a contract that was being passed around. Perhaps he’s a really nice guy. There wasn’t much reason to keep him because of his on-court performance.

Otherwise, it’s mostly swingmen who peaked at the level of an average starter (Rashard Lewis excepted) and then declined. In limited minutes, Butler will probably play a little above replacement level this season. I’d have preferred this roster spot went to someone younger and with potential to improve.

Tomorrow: the rest of the roster.

Wizards 2014 Playoffs Wrap-Up

NBA Washington Wizards vs Chicago Bulls Play-Offs Game 4
Trevor Ariza dominated in the playoffs despite low-blow karate chop from Mike Dunleavy.

Just in time for the start of training camp, here’s a look back at the Wizards run in the playoffs this year. For those with short memories, Washington beat the Bulls in round one, and lost to the Pacers in round two. It was a good couple weeks for a franchise that’s been among the league’s worst the past several years.

I’ve finally gotten around to crunching the data to produce the Player Production Average (PPA) numbers. PPA is an overall rating metric I developed that credits players for things they do that help a team win, and debits them for things that don’t. It’s a per-minute stat that’s pace-neutral, accounts for defense, and includes a “degree of difficulty” factor based on the level of competition a player faces while on the floor. In PPA, 100 = average, higher is better, and 45 = replacement level.

Like any stat extracted from a small sample size, there’s a grain of salt factor. For example, Bradley Beal led the team with 458 playoff minutes — the cut when I look at regular season numbers is usually 500 minutes. Only 21 players reached 500 or more playoff minutes this year. That said, here are the numbers:

PLAYER GMS MPG RS PPA PS PPA
Trevor Ariza 11 37.0 145 193
Marcin Gortat 11 34.7 154 148
Bradley Beal 11 41.6 96 139
John Wall 11 38.2 139 82
Trevor Booker 9 16.2 123 75
Nene Hilario 10 32.5 102 49
Drew Gooden 10 14.6 106 37
Martell Webster 11 17.7 77 35
Andre Miller 11 9.8 86 12
Al Harrington 7 8.4 24 -22
Garrett Temple 10 .9 24 -33
Otto Porter 3 2.0 15 -49
Kevin Seraphin 4 1.5 35 -274

RS PPA = regular season

PS PPA = post-season

The numbers reflect Ariza’s tremendous playoffs performance. A 193 in the regular season would be worthy of All-NBA selection in most years. Among playoff performers with at least 100 total minutes, it ranked third overall behind Lebron James (263) and Chris Paul (211).

Gortat’s production improved as the playoffs went on. His first round PPA was a shade below average, but his play against Indy in round two pulled his full playoffs rating into the vicinity of his regular season performance.

The team’s only other above-average playoffs producer was Beal, who was terrific in round one (152) and solid in round two. A promising post-season debut for a talented kid who will still be among the league’s youngest players when he starts his third season in a few weeks.

The post-season wasn’t so kind to Beal’s backcourt partner, John Wall. In the first round, Wall’s overall production wasn’t overwhelming, but he thoroughly outplayed Chicago’s guards. Indiana did a better job of forcing him out of comfortable plays, and Wall struggled.

Now-departed Trevor Booker was solid in the first round, but played little in the second round. Friend of the blog Ben Becker wondered if Washington might have won against the Pacers if they’d played Booker instead of Gooden and/or Harrington. And, that’s definitely possible. The games were close and hard-fought, and the Wizards got next to nothing from Gooden and less than nothing from Harrington. Booker was fifth on the team in per minute production during the post-season, but 10th in round two minutes.

Against the Pacers, the Wizards got good production from Gortat, and little else from the front-court. Using the trio of Nenê, Gooden and Harrington with so little court time for Booker may well have cost Washington a trip to the Eastern Conference Finals.

Similarity scores coming soon.

That Path to the Eastern Conference Finals

partingredsea08

In my last post, I alluded to a kind of parting of the seas for the Wizards in the Eastern Conference playoffs. The reasoning is pretty simple: the Wizards should be considered strong favorites over either the Pacers or the Hawks. That’s right, either.

If this was a “normal” NBA season, Washington would be a heavy underdog to the top seeded Pacers. But, if this was a “normal” season, the Wizards wouldn’t have been the fifth seed with 44 wins, Atlanta wouldn’t have been in the playoffs with a sub-.500 record, and Indiana wouldn’t have disintegrated over the last two months of the season (and wouldn’t have had to fight and claw to get to a seventh game against such a pedestrian opponent).

This is an abnormal season, though, and the weak Eastern Conference coupled with the stumble-bum Pacers at the top have given the Wizards their best chance of reaching the NBA’s final four since…1979.

That the Wizards would be favored vs. Atlanta is unsurprising. The Hawks weren’t much good during the regular season. They struggled after center Al Horford tore a pectoral muscle (again), and limped into the playoffs. The Pacers need a bit more explanation — which I provided nearly a month ago when I wondered whether Washington should tank for seventh so they could face Indiana in the first round.

If you want more detail, please click and read on that link. The upshot is this: since the All-Star break, the Pacers have been a very different team. They’ve actually had a negative scoring differential, which is something I don’t think I’ve ever seen for an extended stretch from a highly seeded team. Indeed, since the All-Star break, the Pacers have had the scoring differential of a 34-win team (over an 82-game schedule), just one game better than the eighth seed Hawks. Over that same time frame, Washington’s differential was that of a 52-win team.

Don’t go getting too excited about that differential: the Wizards played an incredibly easy schedule after the All-Star break. Still, it’s illustrative of the significant changes in the Eastern Conference. Since that All-Star break, the Wizards had the third best efficiency differential of the East’s playoff teams. The Pacers had the second worst.

So, what are the odds? Applying a combination of full season numbers, post All-Star break numbers, and playoff performance, I estimate Washington having the following chances of beating these possible Eastern Conference playoff opponents:

  1. Indiana — 64%
  2. Miami — 27%
  3. Toronto — 50%
  4. Chicago — 100%
  5. Washington — 0%
  6. Brooklyn — 67%
  7. Charlotte — eliminated
  8. Atlanta — 81%

The odds will fluctuate a bit after that seventh game, but the fundamental point remains: Washington is in a terrific position to reach the Eastern Conference Finals. Getting farther is a dicier proposition, especially if they end up facing Miami.

Round One Wrap-Up

The 4-1 first round win over the Chicago Bulls is done, but there are still a few points worth making. While there’s been some chatter about how flawed the Bulls are (including by me), Chicago actually looked pretty strong entering the post-season. It’s trademark defense was excellent down the stretch, and its offense was about average. The Eastern Conference team with the best efficiency differential after the All-Star break? The Bulls.

Washington’s first round victory wasn’t a case of getting a crappy opponent, it was a case of the Wizards outplaying a decent team. Give credit where it’s due: a big reason the Bulls looked so bad is that the Wizards were on their game.

Finally, here’s a look at the Player Production Averages (PPA) for the series. PPA is an overall rating metric I developed that credits players for things they do that help a team win, and debits them for things that don’t. It’s a per-minute stat that’s pace-neutral, accounts for defense, and includes a “degree of difficulty” factor based on the level of competition a player faces while on the floor. In PPA, 100 = average, higher is better, and 45 = replacement level. (Don’t pay much attention to the extreme scores at the bottom of the table — tiny sample sizes don’t mean much of anything.)

TEAM Player GMS MPG PPA
CHI Taj Gibson 5 30.8 210
WAS Trevor Ariza 5 39.0 193
WAS Bradley Beal 5 41.0 152
CHI Mike Dunleavy 5 32.6 139
WAS Trevor Booker 5 24.2 134
WAS John Wall 5 38.6 128
WAS Martell Webster 5 18.0 113
WAS Nene Hilario 4 35.8 107
CHI Joakim Noah 5 42.0 97
WAS Marcin Gortat 5 36.0 97
CHI Jimmy Butler 5 43.6 88
CHI Carlos Boozer 5 24.2 58
CHI Kirk Hinrich 5 33.4 22
WAS Andre Miller 5 10.4 10
CHI D.J. Augustin 5 28.2 5
WAS Kevin Seraphin 1 1.0 0
WAS Drew Gooden 4 9.0 -35
CHI Tony Snell 5 9.2 -47
CHI Nazr Mohammed 2 2.5 -189
WAS Al Harrington 3 2.3 -364
WAS Garrett Temple 4 0.3 -1889

Interesting that the most productive player in the series was Taj Gibson, who played just 30.8 minutes per game. Meanwhile, Chicago started Carlos Boozer and played him 24.2 minutes per game despite production that wasn’t much better than replacement level.

Also interesting to me is how the production numbers differ from popular perception. One “experts” poll named Nenê as Washington’s first round “MVP.” When it comes down to doing the things that cause teams to win, he rated sixth best for the Wizards — behind Ariza, Beal, Booker, Wall and Webster.

In total, eight players rated “above average” in this series. Six of those players wore Wizards uniforms. While Gibson was good throughout the series, the only other Bull above average was Dunleavy, and most of his production came in a single game.

Path Opening for Wizards to Make Deep Playoff Run

Ariza dominating

As enjoyable as the Wizards-Bulls series has been so far (for Wizards fans, at least), there’s a tangible feeling that Washington has drawn to an inside straight. (That’s a fancy poker way of saying they’ve gotten lucky.) Yes, I’m aware the Wizards have looked good in the playoffs — teams look good when they win.

I’m also aware that the “experts” at ESPN and TNT (and elsewhere) have declared this Washington as a near-perfect squad with “no weaknesses.” But, much (most?) of the commentary has been a veritable catalog of cognitive biases. Over the course of six months and 82 games, the Wizards were average. A perfectly average team playing against their schedule would be expected to win 43-44 games. They won 44. That’s not a team without weakness — it’s an average team.

In the playoffs, they’re beating the Bulls — a slightly better than average team overall this season, but also a team with a major flaw: one of the league’s worst offenses.

Meanwhile, the Indiana Pacers have continued their post-All-Star break swoon and are struggling to keep pace with the sub.500 Atlanta Hawks. The Wizards should be favored against either team in a second round matchup. Which would put Washington into the conference finals against (probably) the Miami Heat.

It’s the 2013-14 NBA Eastern Conference, where being meh is good enough because nearly everyone else is meh-er.

In many ways, the Wizards this season are a fascinating experiment in perception. On one hand, there’s a solidly average regular season and no top-end production. On the other hand, there’s a likely first-round win against the Bulls and a good chance they make a run to the Eastern Conference Finals.

Folks in the “they’re really not that good” camp can point to the historically weak conference and Indiana’s meltdown, which carved out the path. But…it’s not Washington’s fault their opponents suck. The only thing they can do is play their game and beat whoever’s put in front of them. Being average when others are bad might be a functional equivalent of being good.

For me, it’s clear that the Wizards are an average team that’s drawn a flawed opponent in the first round and has a very good chance of getting a flawed opponent in the second round as well. That said, being average this season and next is probably good enough to hang around in the playoffs for the next year or two before Washington’s older players decline and other teams rebuild sufficiently. Washington won’t be a realistic title contender (even if they make the Eastern Conference Finals), but it’ll be fun to see them playing in May.

In other words, have fun, but don’t go overboard revising conclusions drawn from six months and 82 games worth of data over a few weeks against a couple opponents. What would be cause for some revision? Beating the Heat and making it to the Finals.

At any rate, here are a couple looks at the Wizards-Bulls first round series through the first four games. First up, here’s Player Production Average. PPA is an overall evaluation stat I developed. It’s designed to credit players for things they do that help a team win and “debit” them for things that don’t — each in proper proportion. It’s a pace-adjusted, per minute stat that accounts for defense and includes a degree of difficulty factor based on the level of competition a player faces while on the floor. In PPA, 100 = average, higher is better and 45 = replacement level.)

Player TEAM G MPG PPA
Taj Gibson CHI 4 32.3 215
Trevor Ariza WAS 4 39.5 212
Mike Dunleavy CHI 4 32.3 168
Bradley Beal WAS 4 40.8 161
Martell Webster WAS 4 18.5 135
John Wall WAS 4 38.5 121
Trevor Booker WAS 4 24.5 99
Marcin Gortat WAS 4 36.8 86
Joakim Noah CHI 4 41.8 85
Carlos Boozer CHI 4 23.3 76
Nene Hilario WAS 3 34.7 74
Jimmy Butler CHI 4 43.8 70
Andre Miller WAS 4 10.8 63
D.J. Augustin CHI 4 29.5 43
Kirk Hinrich CHI 4 32.0 0
Kevin Seraphin WAS 1 1.0 0
Drew Gooden WAS 4 9.0 -33
Tony Snell CHI 4 10.3 -59
Nazr Mohammed CHI 2 2.5 -180
Al Harrington WAS 3 2.3 -346
Garrett Temple WAS 3 0.3 -1408

The top two producers have been Taj Gibson and Trevor Ariza. Mike Dunleavy’s high rating is largely a product of a single terrific game in a small sample size. Bradley Beal is having a good series. John Wall and Martell Webster have also been solid.

Folks have gotten excited about Nenê’s play, but the big man hasn’t really played all that well outside of game one.

Want to see why Chicago is struggling? Their only above average performers in these four games have been Gibson and Dunleavy. Noah, Boozer and Butler have been subpar. Augustin and Hinrich have been wretched — especially Hinrich who has given the Bulls 32.0 minutes per game of nothing.

Last, here’s a look at estimated wins added (call them eWins) for the series:

Player TEAM G MPG eWINS
Trevor Ariza WAS 4 39.5 0.68
Taj Gibson CHI 4 32.3 0.56
Bradley Beal WAS 4 40.8 0.53
Mike Dunleavy CHI 4 32.3 0.44
John Wall WAS 4 38.5 0.38
Joakim Noah CHI 4 41.8 0.29
Marcin Gortat WAS 4 36.8 0.26
Jimmy Butler CHI 4 43.8 0.25
Martell Webster WAS 4 18.5 0.20
Trevor Booker WAS 4 24.5 0.20
Nene Hilario WAS 3 34.7 0.16
Carlos Boozer CHI 4 23.3 0.14
D.J. Augustin CHI 4 29.5 0.10
Andre Miller WAS 4 10.8 0.05
Kirk Hinrich CHI 4 32.0 0.00
Kevin Seraphin WAS 1 1.0 0.00
Nazr Mohammed CHI 2 2.5 -0.02
Drew Gooden WAS 4 9.0 -0.02
Garrett Temple WAS 3 0.3 -0.03
Tony Snell CHI 4 10.3 -0.05
Al Harrington WAS 3 2.3 -0.05

This eWins approach uses total production to estimate each player’s individual share of team wins. It works reasonably well over the full season. For the series, it has the Wizards with a 2.4 to 1.7 eWins lead, which is reflective of a couple very close games (Washington’s overtime win in game two, and Chicago’s narrow game three victory.)

Wizards Slouching Toward the Playoffs

The numbers in the table below are this week’s Player Production Average (PPA) update. PPA is a metric I developed that credits players for things that contribute to winning and debits them for things that don’t — each in proper proportion. PPA is pace adjusted, accounts for defense and includes a degree of difficulty factor. In PPA, 100 = average, higher is better and 45 = replacement level. PPA is a per minute stat.

PLAYER GMS MPG LW PPA
Marcin Gortat 77 32.9 150 153
Trevor Ariza 73 35.7 151 143
John Wall 78 36.6 141 138
Trevor Booker 68 21.4 115 119
Drew Gooden 20 18.6 127 114
Nene Hilario 50 29.9 101 100
Andre Miller 24 14.4 104 91
Bradley Beal 69 34.7 89 89
Martell Webster 74 28.1 82 80
Jan Vesely 33 14.2 68 68
Kevin Seraphin 50 11.4 35 37
Chris Singleton 24 10.4 34 32
Garrett Temple 71 8.9 25 25
Glen Rice 11 9.9 20 20
Otto Porter 33 8.2 13 19
Al Harrington 30 14.9 13 8
Eric Maynor 23 9.3 8 8

Rough week for the Wizards, which is reflected in the individual numbers. On the positive side were Marcin Gorat, (who continues to have a good season), Trevor Booker (who many fans want removed from the rotation), and Otto Porter (who performed better, but still rates well below replacement level).

Even with a bad week, Trevor Ariza is having a career season. He gets a bit of a pass for the last few games — he’s been beset with the flu, and really shouldn’t have even been on the floor.

John Wall’s production fell for a third straight week. It’s been fashionable to celebrate Wall’s improvement and his ascendancy to All-Star status, but it’s worth noting that his 138 PPA this season is virtually identical to the 139 he posted last year.

Here’s a visualization of each player’s PPA through the season. Since this is basically a weekly rolling season average, the larger fluctuations at the beginning followed by a flatter line toward the end is to be expected. Note the fairly steady climb of Gortat’s PPA — he’s been playing better as the season has progressed. The production slip from Wall the past three weeks is also apparent.

Check out the steady production from Booker. Webster’s season-long decline is apparent in his graph.

Drew Gooden’s production has fallen steeply after a hot start. He may not be the godsend Wizards fans had hoped for. Andre Miller’s play has been up and down, but at least sorta trending up.

ppa trend