Wizards Update: All-Star Edition

Wall all star

All-Star rosters will be released tonight, and while Wizards point guard John Wall will likely be selected, he’s borderline at best, and wouldn’t make the team if I was making the picks. I’ve looked at the numbers several different ways — total production, per game production, per minute production — and Wall remains just on the fringes of the All-Star roster.

This is in no small part because of the fan vote, which picked the starters in each conference. In the East,  at least according to my analysis, Dwyane Wade, Paul George and Carmelo Anthony are undeserving of All-Star status — even as reserves. This pushes all guards down one spot, and all front-court players down two. In my analysis, the next guard up for the East: John Wall. The next front-court guys: Greg Monroe and Al Horford.

In the West, the only poor choice was Kobe Bryant, who received a career achievement honorific. The next deserving front-court player was Blake Griffin, whose injury would have pushed to next man up Dwight Howard.

Here’s the way Player Production Average (my metric, see below) would divvy up the teams:

POS EAST WEST
G Kyle Lowry Stephen Curry
G Dwyane Wade Russell Westbrook
F Lebron James Kobe Bryant
F Paul George Kevin Durant
F Carmelo Anthony Kawhi Leonard
G Jimmy Butler Chris Paul
G Kemba Walker James Harden
F Paul Millsap Draymond Green
F Hassan Whiteside Anthony Davis
F Andre Drummond DeAndre Jordan
G Isaiah Thomas Damian Lillard
F Chris Bosh Derrick Favors

My guess is that Wall will probably be chosen over Walker and that Horford will make it over Whiteside. In the West, I’d anticipate Thompson over Lillard and Howard or Demarcus Cousins over Favors.

Those Mediocre Wizards

Talk about the Wizards potentially becoming trade deadline “sellers” inspired me to apply my “Real Trade Value” toy in an all-new way to measure the team’s pervasive mediocrity.

I haven’t written much about Real Trade Value, which is still a work-in-progress. RTV attempts to determine the trade value of each player in relation to the league’s MVP. In RTV, there’s accounting for age (younger players get a bonus; older players get a deduction), and total production and per minute production are given equal weight. So, RTV “likes” players who are young, productive and durable.

There’s no accounting (yet) for contract or position.

In RTV, the top value (this year it’s Stephen Curry) is set at 1,000. Other players are scaled beneath. The idea is similar to the NFL draft pick value sheet. A theoretical trade for Curry would cost 1,000 RTV points. Here are the players closest to each 100-point mark:

  • 1,000 — Stephen Curry
  • 900 — Kawhi Leonard
  • 800 — no one (here’s how outlandish Curry and Leonard have been: Curry’s RTV is 1,000; Leonard’s is 878; next closest is Westbrook at 721)
  • 700 — Russell Westbrook, Andre Drummond, Kevin Durant, Karl-Anthony Towns, Anthony Davis
  • 600 — Greg Monroe, Hassan Whiteside
  • 500 — Al Horford, Kevin Love, Derrick Favors, Paul George, Clint Capela, Chris Bosh
  • 400 — Zaza Pachulia, Mike Conley, C.J. McCollum, LaMarcus Aldridge, Enes Kanter
  • 300 — Ryan Anderson, Bismack Biyombo, T.J. McConnell, Jrue Holiday, Jeff Teague
  • 200 — Trevor Booker, Kyle Anderson, Frank Kaminsky, Jeremy Lin, Ramon Sessions
  • 100 — Mike Muscala, Jamal Crawford, E’Twaun Moore, Jameer Nelson, Kevin Martin
  • 0 — Vince Carter, Sasah Vujacic, Emmanuel Mudiay, Markieff Morris

Got all that? There’ll be a quiz later.

In terms of actual trade value, contracts and position almost certainly need to be included. But, for looking at franchise health — weighing productivity and health vs. age — it works reasonably well.

Here’s a table with the results, sorted by conference.

TEAM CONF NBA RANK CONF RANK FRANCHISE HEALTH INDEX
BOS E 5 1 77
ORL E 6 2 75
ATL E 7 3 74
TOR E 8 4 74
CLE E 10 5 71
MIL E 12 6 70
IND E 13 7 69
CHO E 14 8 69
WAS E 19 9 65
NYK E 20 10 65
DET E 21 11 64
MIA E 24 12 62
CHI E 25 13 62
PHI E 27 14 59
BRK E 28 15 59
GSW W 1 1 100
OKC W 2 2 89
SAS W 3 3 84
UTA W 4 4 78
NOP W 9 5 72
DEN W 11 6 70
HOU W 15 7 69
LAC W 16 8 69
POR W 17 9 68
MIN W 18 10 67
SAC W 22 11 63
PHO W 23 12 63
DAL W 26 13 61
MEM W 29 14 52
LAL W 30 15 52

The last column is a “franchise health” index where the top team (Golden State) is set at 100 and other teams are scaled below. The Wizards rank 19th overall and 9th in the East. League average “index” score is 69, indicating they rate a little below average.

IF this measure has any predictive value at the team level (and that’s a HUGE “if” because I’ve done precisely zero research on that question), the Wizards have significant work ahead of them to upgrade the roster.

Player Production Average

The ratings below are a 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 01/27/16 are here.

PLAYER GMS MPG 11/10 11/22 12/3 12/13 12/21 12/30 1/6 1/13 1/27
Marcin Gortat 37 31.7 91 112 128 133 132 138 147 145 148
John Wall 43 35.7 153 129 136 168 157 157 149 144 142
Otto Porter 36 32.1 144 158 104 116 107 115 122 127 130
Jarell Eddie 11 6.9  –  –  –  –  – 153 119 113 110
Jared Dudley 42 28.7 36 92 90 85 98 103 100 105 99
Bradley Beal 22 32.9 128 108 96 87 87 86 85 86 98
Nene Hilario 22 18.4 58 90 80 74 79 78 79 88 92
Ramon Sessions 43 21.2 131 119 84 90 87 89 88 91 90
Garrett Temple 41 24.7 38 106 57 54 70 63 68 79 79
Kris Humphries 27 17.1 90 121 95 80 78 76 79 79 78
Gary Neal 35 21.1 23 49 64 75 78 74 75 78 71
Kelly Oubre 36 13.4 -103 -4 -40 -44 9 37 43 39 36
Drew Gooden 14 13.8 99 51 57 56 56 56 38 47 34
DeJuan Blair 26 7.9 -345 -129 -112 -45 -34 -38 -38 -28 -6
Ryan Hollins 5 9.6  –  – -40 60 59  –  –  –  –

The numbers aren’t too encouraging. Wall has followed up his Player of the Month December with a thoroughly meh January. If the Wizards are going to get back in contention for a spot in the playoffs, they need something closer to the December Wall than they’ve been getting.

Wizards Update: Level Best

It may seem strange to worry about the Wizards making the playoffs this season when they still have 49 games to play, but history suggests they’re already running out of time to turn things around and reach the postseason.

It’s likely going to take 45 wins to earn the eighth seed in this year’s East. With Washington at 15-18, simple math says they’ll need another 30 wins in their final 49 games. That means playing at about .600 level the rest of the way — basically at the level of a 50-win team (over an 82-game schedule).

This is possible and not unprecedented in basketball history. Teams have dramatically improved after a poor start. But not many of them. Teams that started a season like the Wizards were much more likely to remain at the same level than markedly improve. One of those teams (the 04-05 Denver Nuggets) made two coaching changes and played .800 ball (32-8) to finish the season with 49 wins. That record is a dreamworld best-case fantasy, though.

In the real world, last season’s Wizards actually began the year a 31-18 record in their first 49 games. That’s a .633 winning percentage, and if they could replicate it over the final 49 games of this season they’d end up with 46 wins and a berth in the playoffs. Last year in reverse has a patina of plausibility, which makes it seem more possible than the evidence indicates.

Unfortunately, there are several good reasons to think that quality of play is unlikely. Since that 31-18 start, the Wizards are 36-40 — 15-18 to finish 2014-15, 6-4 in the playoffs, and 15-18 this season. That’s the quality of a 37-win team across a BIG stretch (93% of a regular season). And it’s notably consistent.

In addition, the team’s scoring differential through that 49-game stretch suggested they weren’t quite as good as their record. Scoring differential analysis indicated a 28-win team during that stretch — about the level of a 46-win team over an 82-game schedule, not the 51-win level suggested by their 31-18 record. At 33 games last season, the team was 22-11 — about three wins ahead of their expected win total. The difference wasn’t an indication that the Wizards “knew how to win” or had become “clutch,” it was a signal that the team wasn’t as good as their record.

And here’s where things get even more worrisome for the 2015-16 edition of the Wizards: their scoring differential says they’re the quality of a 13-win team through their first 33 games. Their won/loss record is running about two games ahead of their expected wins. This is a sign of weakness. Widely perceived as under-performing, the team is actually playing even worse than their already bad record. Their winning percentage is that of a 37-win team over an 82-game schedule. Their scoring differential suggests they’re playing at the level of a 32-win team. Another way of looking at it: they’re 19th in winning percentage, and 22nd in scoring differential.

The task ahead of them is not impossible. They could improve, and they are just 2.5 games from the eighth seed. But it’s time for some urgency. It’s time for them to start playing at a higher level and to string together wins. Because with every additional loss, the goal of making the playoffs this season becomes less and less probable.

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 01/06/16 are here.

PLAYER GAMES MPG 11/10 11/22 12/3 12/13 12/21 12/30 PPA
John Wall 33 35.7 153 129 136 168 157 157 149
Marcin Gortat 30 31.2 91 112 128 133 132 138 147
Otto Porter 30 32.2 144 158 104 116 107 115 122
Jarell Eddie 5 11.6 153 119
Jared Dudley 32 27.8 36 92 90 85 98 103 100
Ramon Sessions 33 21.3 131 119 84 90 87 89 88
Bradley Beal 17 36.5 128 108 96 87 87 86 85
Kris Humphries 27 17.1 90 121 95 80 78 76 79
Nene Hilario 13 17.0 58 90 80 74 79 78 79
Gary Neal 25 22.1 23 49 64 75 78 74 75
Garrett Temple 31 22.8 38 106 57 54 70 63 68
Ryan Hollins 5 9.6     -40 60 59 59 59
Kelly Oubre 26 13.4 -103 -4 -40 -44 9 37 43
Drew Gooden 7 11.6 99 51 57 56 56 56 38
DeJuan Blair 18 8.4 -345 -129 -112 -45 -34 -38 -38

Wall’s season has been…odd. He was mediocre through the first month of the season, posting a PPA of just 94. When the calendar shifted to December, he abruptly transmogrified into an All-NBA caliber point guard, posting a December PPA of 202. Then in January, he’s posted three straight crummy games, and has a PPA of just 86. His wildly vacillating performance level gives ample ammunition to fans who believe he should be starting the All-Star game (look at the sensational play in December), as well as those who think other players are more deserving (look at the bad first month of the year). In PPA, he’s a borderline All-Star candidate — fifth among guards in the East (minimum 750 minutes), but with frontcourt players rated ahead of him.

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.

Wizards Update: Just the Numbers

four

As Dean Oliver first wrote, there are four key factors that determine who wins and loses in the NBA. In order of importance: shooting, rebounding, getting to the free throw line and turnovers. So far this season, the data suggests that variation in efg differential accounts for about 44% of variation in scoring differential; rebounding accounts for 26%, getting to the free throw line about 18%, and turnovers about 11%.

How are the Wizards doing? They’re 25th in efg differential, 24th in rebounding differential, 9th in turnover differential and 10th in free throw differential. All that combines to rank 23rd in average scoring margin, which means they haven’t played even as well as their 19th ranked winning percentage might suggest.

At this point, Basketball-Reference forecasts the Wizards to win about 36 games and indicates the team’s odds of winning the draft lottery (2.5%) are about the same as them making the playoffs this season (2.4%).

While the team embarked on an effort to play faster, the results through 25 games indicates they may still benefit by slowing down. The defense appears to be largely unaffected by pace, but the numbers suggest the team may be a bit more efficient in slower-paced games. The effect is small, but at this point the team needs every advantage it can get.

rtg by pace

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 12/20/15 are here.

PLAYER GAMES MPG 11/10 11/22 12/3 12/13 PPA
John Wall 25 35.1 153 129 136 168 157
Marcin Gortat 22 30.2 91 112 128 133 132
Otto Porter 24 32.3 144 158 104 116 107
Jared Dudley 24 26.9 36 92 90 85 98
Ramon Sessions 25 19.7 131 119 84 90 87
Bradley Beal 17 36.5 128 108 96 87 87
Nene Hilario 12 17.4 58 90 80 74 79
Gary Neal 23 22.4 23 49 64 75 78
Kris Humphries 20 18.1 90 121 95 80 78
Garrett Temple 23 18.0 38 106 57 54 70
Ryan Hollins 5 9.6 -40 60 59
Drew Gooden 6 12.8 99 51 57 56 56
Kelly Oubre 18 9.3 -103 -4 -40 -44 9
DeJuan Blair 14 9.5 -345 -129 -112 -45 -34

As I’ve been writing seemingly for years now, the Wizards continue to lack elite production. Click over to the full league numbers and you’ll find 11 players with at least 500 minutes who have a PPA of at least 200. Wall ranks 10th among point guards, but in a virtual tie with Reggie Jackson and Rajon Rondo.

This isn’t Wall’s “fault” exactly, he’s a very good player. But he needs more help than he’s getting. Beal ranks 24th among shooting guards, Porter 16th among small forwards, Gortat 18th among centers, and Dudley 31st among power forwards.

Wizards Update: A Silver Lining

As if the 2015-16 Wizards season wasn’t crummy enough, the team released news over the weekend that Bradley Beal would miss at least a couple weeks with yet another stress reaction in his leg. While this was a bummer of a development — especially when combined with Beal’s fourth consecutive season of pedestrian production — I’m writing today not to induce depression, but to give hope.

Wizards point guard John Wall began the season well: after a strong performance against the Spurs, Wall’s PPA (see below) sat at a heady 184 — not an MVP candidate, but probably in the conversation for All-NBA, and definitely All-Star level.

And then, for some reason (possibly a previously undisclosed ankle injury) his production tanked. After four consecutive good-to-great games to start the year, eight of his next ten games rated below average in PPA. In two of the games (at Boston and home against Toronto), Wall rated a net negative; a scary place for the team’s star. After posting a -70 vs. the Raptors, Wall’s PPA for the season stood at a slightly below average 96.

And then…the calendar switched to December and Wall abruptly began playing like an MVP candidate. In the eight games since that -70, Wall has produced a PPA of 300 or better four times, and another three better than 200. His lone dud was a 74 against Phoenix.

Wall’s PPA for October and November was 96. In December: 278. For context, here are the top five full-season PPA scores on record:

  1. Lebron James, MIA, 2012-13 — 282
  2. Stephen Curry, GSW, 2014-15 — 277
  3. Lebron James, CLE, 2008-09 — 275
  4. Michael Jordan, CHI, 1990-91 — 268
  5. Lebron James, CLE, 2009-10 — 267

Now, even posting a 278 the rest of the way won’t get Wall into this year’s MVP conversation because Curry’s PPA is another 70 points better, but still. Wall has been playing great the past couple weeks, and seems to be turning his season around. That’s a genuine reason for optimism.

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 12/03/15 are here.

PLAYER GAMES MPG 11/10 11/22 12/3 PPA
John Wall 22 35.0 153 129 136 168
Marcin Gortat 19 29.6 91 112 128 133
Otto Porter 22 33.0 144 158 104 116
Ramon Sessions 22 19.0 131 119 84 90
Bradley Beal 17 36.5 128 108 96 87
Jared Dudley 21 26.5 36 92 90 85
Kris Humphries 17 17.6 90 121 95 80
Gary Neal 20 22.0 23 49 64 75
Nene Hilario 12 17.4 58 90 80 74
Ryan Hollins 5 9.6 -40 60
Drew Gooden 6 12.8 99 51 57 56
Garrett Temple 20 17.6 38 106 57 54
Kelly Oubre 15 6.9 -103 -4 -40 -44
DeJuan Blair 12 8.5 -345 -129 -112 -45

If I could have one Christmas present for the Wizards, it’d be a starting quality power forward.

Who Are The Biggest Liars In Politics?

trump

Donald Trump: Biggest liar in politics?

A conservative friend told me today that he couldn’t possibly vote for Hillary Clinton because she is a “serial liar.” Another voiced agreement, saying, “The Clintons are some of the biggest liars in the history of American politics.”

At first this felt like one of those unmeasurable assertions. Except…there are fact checking websites like, PolitiFact. Others exist, but PolitiFact publishes a handy table providing a numerical breakdown of each person and organization it’s fact checked.

PolitiFact rates claims they’ve fact checked in one of the following categories:

– True
– Mostly True
– Half True
– Mostly False
– False
– Pants on Fire

To create a measure of political truthiness, I combined the first two as “truth” and the last three as “liar”.

Here are the TRUTH leaders from my self-selected group of news makers, according to the information published by PolitiFact (percentage of claims made by each individual that have been rated true or mostly true by PolitiFact):

  1. Bernie Sanders 53%
  2. Hillary Clinton 51%
  3. Barack Obama/Jeb Bush (tie) 48%
  4. Rand Paul 47%
  5. Chris Christie 40%
  6. Joe Biden 39%
  7. Marco Rubio/Sean Hannity/Mitch McConnell 38%
  8. Rachel Maddow 37%
  9. Scott Walker 34%
  10. Harry Reid 33%
  11. Paul Ryan 32%
  12. Mitt Romney 31%
  13. John Boehner 30%
  14. Ted Cruz 22%
  15. Nancy Pelosi 18%
  16. Donald Trump 7%
  17. Rush Limbaugh/Chain e-mails 6%
  18. Ben Carson 4%

In other words, 53% of the claims and assertions made by Bernie Sanders have been rated as true by the journalists at PolitiFact — the highest level (by a hair over Clinton) in this group. And kudos to Donald Trump for being slightly more truthful than anonymous chain e-mails and Rush Limbaugh. Ben Carson, the most honest student at Yale, rated as the least truthful — just 4% of his claims were rated as “true” by PolitiFact.

On the LIAR leaderboard (percentage of claims made by each individual rated as Mostly False, False or Pants on Fire by PolitiFact):

  1. Obama 26%
  2. Sanders 28%
  3. Clinton 29%
  4. J. Bush 31%
  5. Biden/Paul 32%
  6. Christie 33%
  7. Rubio 40%
  8. Romney 41%
  9. Pelosi 43%
  10. Hannity 44%
  11. Ryan/McConnell 46%
  12. Walker 47%
  13. Maddow 48%
  14. Reid 52%
  15. Boehner 54%
  16. Cruz 66%
  17. Trump 75%
  18. Limbaugh 82%
  19. Carson 84%
  20. Chain e-mail 89%

If I make it into a ratio — TRUTH/LIAR, I get these results:

  1. Sanders 1.92 (truths per lie)
  2. Obama 1.86
  3. Clinton 1.78
  4. J. Bush 1.55
  5. Paul 1.47
  6. Biden 1.23
  7. Christie 1.22
  8. Rubio 0.94
  9. Hannity 0.86
  10. McConnell 0.82
  11. Maddow 0.77
  12. Romney 0.74
  13. Walker 0.73
  14. Ryan 0.70
  15. Reid 0.64
  16. Boehner 0.57
  17. Pelosi 0.42
  18. Cruz 0.33
  19. Trump 0.09
  20. Limbaugh/Chain e-mail 0.07
  21. Carson 0.05

So there you have it: the biggest liars in politics are Ben Carson, Rush Limbaugh, chain e-mails and Donald Trump.

In the interest of fairness, I’ll point out that the forgoing numbers don’t necessarily represent “lies” in the sense that each of these people knew they were saying something untrue in each of these instances. Some of these are likely factual errors.

In addition, the PolitiFact database includes only claims they fact-checked. Each of these people have made a gazillion claims, many of which could be true, false or something in-between. What’s presented by PolitiFact (and therefore by me) is analysis of claims that were controversial or iffy enough to indicate a need for third-party evaluation. (I use “third-party” intentionally because PolitiFact has been accused of having a liberal bias. That’s a subject for another day.)