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Posts Tagged ‘LeBron James’

In the last post, we looked at the leaders in Expected Value (EV) on the defensive side of the ball for the 2010 playoffs. Not surprisingly, Dwight Howard was the winner there. Now let’s look at the offensive leaders in EV from the 2010 playoffs. There are three notable additions to the classic box score involved in that calculation:

“Help Needed” includes all of the points scored that were created by a teammate. I will have a post about it in the near future, but for now, think of Kobe Bryant driving down the lane and drawing hordes of defenders (an OC), setting up Andrew Bynum for an open dunk. In that case, Bynum’s dunk loses some value because it was created by another teammate. More on this in the future, though.

Here are the leaders in offensive EV from the 2010 playoffs, minimum 300 possessions played. All EV values are relative to league averge:

Offensive EV Leaders, 2010 Playoffs

As always, with playoff data, it’s important to remember particular matchups. Last year, Deron Williams dissected a soft Denver defense and then he made Derek Fisher look like an AARP member. Utah actually boasted the second best Offensive Rating in the playoffs — 114 pts per 100 possessions — but the defense let them down mightily. Here is the complete list of leaders in Offensive EV from the 2010 playoffs, minimum 300 possessions played.

Finally, we can combine the defensive and offensive components and view the overall Expected Value leaders from the 2010 playoffs:

2010 Playoffs, min 150 possessions; Def=Defensive EV; Off=Offensive EV

By just about any measure, Dwyane Wade had a fantastic series against Boston’s vaunted defense. LeBron James’ second round against Boston wasn’t quite as good (8.5 EV), but he tortured Chicago in the opening series. Of the three superheroes, Kobe had it the worst of against Boston, posting a 3.4 EV in the Finals.

For reference, the top series performances by EV from the 2010 playoffs (EV in parentheses):

  1. James vs. Chi (16.2)
  2. Gasol vs. Uta (12.8)
  3. Howard vs. Atl (12.5)
  4. Nelson vs. Cha (12.5)
  5. Wade vs.Bos (11.8)
  6. Bryant vs. Pho (11.8)
  7. Nash vs. SAS (10.8)
  8. D Will vs. Den (10.2)
  9. Dirk vs. SAS (9.3)
  10. James vs. Bos (8.5)

Paul Gasol had the highest EV of the 2010 NBA Finals (5.0). Here is the complete list of EV leaders from the 2010 playoffs, minimum 150 possessions played.

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If you missed the last post, it was an overview of Expected Value (EV). And while that approach is not a novel concept — check out this similar method — from what I gather, incorporating a large defensive component is. Most of the defensive numbers used are from my stat-tracking. As a refresher, the defensive component of EV includes:

So which individual players fare the best in this metric? Below are the top defensive players in EV from the 2010 playoffs, with defensive usage included as a reference for the size of a player’s role (minimum 30 defensive plays “used”):

2010 Playoffs; Minimum 30 defensive possessions used

Dwight Howard, not surprisingly, had the best playoffs on the defensive end according to this. It’s good to be cautious of how small-sampled the playoffs are, given that one or two games against a hot or cold shooting opponent could skew these numbers. Then again, half the all-defensive team is represented on the list above, and that doesn’t include reputable defenders like Joakim Noah, Luc Richard Mbah a Moute and Tony Allen.

Because the playoffs are not only small sampled in games, but in opponents, it’s always important to consider matchups. Which makes Allen’s performance — mostly versus Dwyane Wade, LeBron James and Kobe Bryant — that much more impressive.

For those wondering about Kevin Garnett and Tim Duncan, they both just missed the cut. Garnett, to me, emphasizes the single greatest challenge in measuring individual defense causally: his greatest strength is probably communicating where to be and what is coming at all times to those around him. Now that’s difficult to quantify.

Finally, here is the complete list of defensive EV from the 2010 playoffs for all qualifying players (min 30 defensive possessions “used”).

Author’s Note: All EV values are relative to league average.

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I’ve talked about “guarded situations” before, but never from the perspective of an individual defender. We can use a “guarding situation” as a quick and dirty operational definition for looking at FG% against individual defenders. To reiterate the definition of a guarded situation:

  • The defender is trying to defend an offensive player without being impeded by a screen or helping on defense
  • The defender is challenging an offensive player at the basket by “engaging” in guarding them
  • The defender is double-teaming in a manner that actually impacts the opponent’s shot

The first situation has a gray area when players are screened out and then “re-engage” in guarding them (or switch on screens and pick up a new man). I look at the defenders stance and spacing from the offensive player to determine if he’s re-engaged: If the defensive player hasn’t had time to establish that position as he otherwise would have, he hasn’t engaged the offensive player again. (For eg, scrambling and lunging at a shot attempt from 4 feet away after being screened isn’t “guarding,” it’s more akin to closing out on a jumper shot.)

The second situation is fairly straightforward — Dwight Howard isn’t engaged in “guarding” a player by leaping across the lane at the last second, after a shot is taken, trying to block it. That’s the equivalent of a closeout on a jump shot, and for these purposes ignored (unless the shot is literally blocked). But when he’s standing in the lane and picks up the attacker coming toward the rim, he is now guarding the offensive player.

The last situation is simply to clarify that an incoming double-team is not an engaged double-team. If Dwayne Wade runs at a post player to double, he isn’t actually guarding him until he gets there. Engaged double- teams count as half attempts for each defender.

From that definition, we can look at how players shoot against defenders. The average guarded shot in 164 team games tracked this year is 40.6%. In last year’s playoffs, it was 39.6%, mostly due to the number of games played by good guarding teams like Boston (35.6% against), Orlando (36.6% against) and Los Angeles (38.0% against).

Here are the individual leaders from the 2010 playoffs in FG% against (min 30 FGA):

2010 Playoff Leaders FG% Against; Min 30 FGA's

There are some not-so-surprising names on that list. Players with good defensive reputations like LeBron James, Howard, Serge Ibaka and Kendrick Perkins. Although it’s always important to keep in mind that playoff samples are heavily influenced by the matchups from a series or two.

There are surprising names there too, perhaps most notably Tony Parker. After 26 FGA against this year, Parker’s opponents are shooting 50%. Ah, small sample sizes! Here are the leaders from games tracked in the regular season so far this year (min 30 FGA):

Min 30 FGA

Again, it might be surprising to see Jason Kidd’s name there, but he just missed the cut for the playoff leaders last year — 31.3% against. Even at his advanced age, he can still defend quite well, and I imagine his large frame and intelligent positioning make scoring on him more difficult than normal.

Another name that might stand out, other than Shannon Brown, is Derek Rose. I will have a post on Rose and the Bulls defense in the near future, but there is no doubt Rose’s athleticism has made him a really solid defender at the point guard position.

Included here is the complete list of qualifying players in FG% against from 2010 playoffs.

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82games just updated its numbers for the 2011 season, and of particular interest is Miami’s performance in clutch situations (5 point game or closer in the final 5 minutes). As far as I know, no one publishes team stats for these situations.

In lieu of that, we can ballpark a team’s clutch performance by looking at the team leaders in clutch minutes. Included is the percentage of clutch minutes that player has played for his team, and the player’s overall plus-minus for the season for comparison.

From 82games.com through 3/05/11

So it’s not like Miami is crumbling or lost down the stretch of these games. They are actually about 15 points better than opponents over the course of a game using this criteria. More surprisingly, Miami’s offense with James on the court (95% of its clutch minutes) boasts an Offensive Rating of over 120. By comparison, the Lakers ORtg with Bryant is just under 109. Boston’s with Pierce is 108.5. Chicago’s with Rose 108.

Hmm. Maybe Miami’s clutch problem is against elite teams only? The Heat have played 12 competitive games against the eight best teams this year (with a 2-10 record in those games). In the final two minutes of those games, Miami’s average point differential is -0.2. Basically dead even.

In the final five minutes of these games their average point differential is -2.4. That’s -29 over 60 minutes of play; Finally some evidence of close-game failures. But even 79% of that difference comes from two games against Orlando in which the Magic bombarded Miami down the stretch (in the November 24 and February 3 games). Here’s the Heat’s complete breakdown against the top-8 by section of the game:

It’s fair to say that Miami’s struggles down the stretch are overblown. With the exception of one incredibly specific, small-sampled criteria: The final 10 seconds of games when trailing by three or less. According to an ESPN graphic posted after the game, Miami is just 1-18 shooting in such scenarios.

Is it plausible that the Heat will continue to shoot 6% in these situations for the remainder of the season and the playoffs? Unlikely. Right now, they’re on the (extreme) wrong side of variance in a small sample size (18 shots).

That doesn’t mean there aren’t legitimate problems in South Beach. Only, they have a lot less to do with close games and a lot more to do with size and depth. Which, of course, were the original problems in the first place when they cleaned house in the offseason.

The Heatles aren’t losing these games in the final seconds. They are losing them in the 3rd quarter (and into parts of the 4th). And there’s no reason to believe that isn’t a direct result of playing three on five most of the time.

Miami was thin enough heading into the season before Udonis Haslem’s injury. It has now logged over 1000 minutes at center from Juwan Howard and Erick Dampier. Combined age: 73. (Yes, they still play basketball.) Mike Miller has played 500 disappointing minutes returning from injury.

Miami’s biggest problem heading into the playoffs this year isn’t the end of close games – that issue has been greatly exaggerated, and it will improve with experience and, statistically, by default. The Heat’s biggest problem is the same one they’ve had all season: size and depth.

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A poster on the realgm forums named Nonemus recently wondered how everyone’s favorite triumvirate of wings, Kobe Bryant, LeBron James and Dwyane Wade, have stacked up against elite teams in the playoffs. Some of the numbers are worth examining here, namely how these three have performed against defenses separated by quality. Are any of them bottom-feeders? Do they equally suffer against the best defensive teams? Has one played a disproportionately large amount of games against amazing defenses?

First, we need to define elite defenses. Since the rule changes in 2005, only 41 teams have posted a defensive rating of 104 or lower. Which means, on average, a 104 DRtg is about the 6th best defense in the league and roughly three points better than average. Certainly a fair cutoff point with which to work. Similarly, let’s call “solid” defensive opponents those with a DRtg between 104 and 107 (roughly better than average), and “bad” defenses having below average Defensive Ratings (lower than 107).

Using that distinction, it turns out Dwyane Wade has played the majority of his playoff games against elite defenses (68% of all games versus such teams). LeBron has played 42% against top defenses and Kobe 38%. Below are their statistics, per 36 minutes, broken down by defensive quality. (GmSc is their Game Score).

Fittingly, Bryant and James show improvement the easier the defensive foe. Wade, however, has some surprising results. His performance versus elite D and non-elite D isn’t too different. (Note, those six games against “solid” defenses are from the 2006 Finals against Dallas.) He quite clearly outperforms the other two against elite defensive teams, even ramping up his three-point % and assists.

LeBron’s history against elite defensive teams is a tale of two players. In his first 15 games against such opponents, James struggled mightily, to put it mildly. He was dreadful, posting a 45.9% TS percentage and averaging over four turnovers per 36 minutes. Hide the women and children.

Below are his splits — the first 15 games are against 2006 Detroit, 2007 San Antonio and the first four games against Boston in 2008:

So James has been a different player against top defenses since game 5 against Boston back in 08, scoring and shooting better than he has even against solid defenses and posting a monstrous Game Score that tops Wade’s or Bryant’s GmSc against even the weakest defenses. The lesson, as always, is that LeBron James has been really good for the last few years.

Here is how each player’s series looks visually, measured using Game Score. The x-axis is a team’s defensive rating and y-axis the players average GmSc for the series:

The coefficient of correlation between Game Score and Opponent Defensive rating is as follows for each player:

  1. LeBron .582
  2. Kobe .561
  3. Wade .409

Which implies that LeBron’s Game Score by series is the most heavily influenced by opposing defense and Wade’s is the least affected. That is, the more positive correlation suggests that as the defense is worse, the performance better. That bottom-feeding trend is the strongest in LeBron’s case, and can be seen above with all his data points in the upper right quadrant.

All of this begs the question: Is it better for performance to vary according to defensive strength, or better to remain consistent regardless of opponent quality? In his only two series against bad defensive teams, Wade shows no appreciable improvement. LeBron and Kobe feed off bad defenses, to a certain degree.

In the playoffs, teams can expect to encounter difficult defenses on the path to a title. Since the inception of the three-point line in 1980, only five teams with an SRS over 6 had a defensive rating over 107. And 58% of those 6+ SRS teams qualified as “elite,” with a DRtg of 104 or lower. Which means in this case, Dwyane Wade may provide a distinct advantage on the game’s biggest stage.

Here is a complete list of each players series against elite defenses in the playoffs since 2005.

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When I was growing up, a “closer” was a term reserved for baseball pitchers. Specialists with strange facial hair who were only used when their teams protected narrow leads and needed three outs to finish the game.* Then a closer became someone with enough machismo to finish real estate deals. Kyra Sedgwick turned out to be The Closer. And finally, it devolved into a basketball term.

*I never understood the decision not to use closers when teams were behind by a run. Why opt for a lesser pitcher simply because a save opportunity wasn’t available?

In the NBA, a “closer” refers to star players who play well down the stretch of close games. Give them the ball, and they will guide a team to victory. Simplify the game and ride the best player to victory.

In other words, the best closers are the best offensive anchors at the end of tight games. So naturally, unless there is a drastic difference between normal performance and late-game performance, the best closers will be the best overall offensive players in the game.

Some people believe that clutch performance varies wildly in professional sports. That pro athletes are wired differently, some live for big moments and others shrink in them. And there is quality reasoning behind that thinking. So, when something like this starts rolling, it’s hard to stop its momentum:

It didn’t stop there. Mark Jackson kept calling Kobe Bryant the best closer during game coverage. Skip Bayless has echoed it. This informal 2009 poll of players agreed that Kobe was the King of Clutch.

Kobe’s shortcomings in such situations have been extensively documented. The meme floating around that he’s the de facto best closer/clutch player in the league is actually less erroneous than its evil twin, the Un-Clutch meme. That has been slapped on undeserving players like Karl Malone and Kevin Garnett before, and now it follows LeBron James.

Only LeBron James is plenty clutch. Actually, he’s the best closer in basketball. And it’s not even really close.

In the first batch of clutch numbers I crunched from 82 games, looking at the final 5 minutes of 5-point games or closer, LeBron practically lapped the field. In 477 minutes of closer duty from 2008 to 2010, LeBron’s Cavs were +27.2 per 36 minutes. That is mind-boggling, given that the best NBA teams in history are about +9 per 36 minutes. It’s even more superhuman when one considers how they’ve completely crumbled as a team without James.

He managed to score, rebound and distribute down the stretch of close games while shooting 10% better than league average in eFG%. Holy Superman, Batman! Frankly, he looks like the best player in NBA history based on his closer line.

The next set of numbers looked at playoff performances in such situations. Again, James showed the same pattern: his scoring, shooting and assist numbers spiked. Of the players examined in that post, only one other (Carmelo Anthony) improved his playoff shooting in the clutch, and only Steve Nash averaged more assists. Of course, LeBron scored at nearly double Nash’s rate.

It’s almost as if most of LeBron’s value is disproportionately unleashed at the end of close games. He is, in many ways, the ultimate closer.

Yet the indestructible meme following LeBron is that he’s not a closer.

Some argue that he’s too unselfish at the end of games. But he actually shot the ball more frequently than anyone from 2008-2010, including Kobe Bryant. He has attempted 69 attempts in the final 24 seconds of close games according to this ESPN study, which is about 10 per year. Again, more than anyone on the list.

Even his free throw shooting is refined when he’s closing. 81% on 187 free throw attempts from 2008-2010, up 6.3% from all other situations. He made 20 consecutive late-game free throws this year before missing one two weeks ago. The last time 82games ran “super clutch” numbers (final 2 minutes of a 3-point game), LeBron was in video-game land.

Last week, Kevin McHale opined on NBATV that Miami should have LeBron be a distrbutor down the stretch and let Wade be the team’s closer. Skip Bayless loves to slam his ESPN desk and note how Wade is a great closer and LBJ isn’t.*

I don’t know what it will take to kill those ideas. I suspect the way to destroy the Un-Clutch meme is to win a championship. Hopefully, In the meantime, this is a start.

*If pressed, here are my late-game offensive player rankings since 2003. Note Wade’s absence:

  1. LeBron James
  2. Steve Nash
  3. Kobe Bryant
  4. Manu Ginobili
  5. Chris Paul

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On Sunday, in an 85-82 win over Miami, Paul Pierce didn’t make a field goal. Zero hits in ten tries against LeBron James and the Heat. This might have seemed like a shocking result for a nine-time All-Star.

It wasn’t.

It was merely the low point in a longtime struggle against one of the game’s best perimeter defenders. (In Pierce’s defense, he was coming off of a bout with the flu, had a sprained wrist and left foot injury.)

In their last meeting of the 2006 season, Pierce scored 50 points against James and the Cavs. That was back when LeBron wasn’t a great defender. Since then, they’ve met 28 times in the regular season and playoffs. Pierce’s numbers per 36 minutes in those games compared with his regular season averages since 2007:

Besides the massive drop in shooting, Pierce earns fewer trips to the line and his rebounding declines as well. The result is a somewhat horrific four-year stretch against James in which Paul has averaged 16.6 points per 36 minutes on 50.5% True Shooting.

James has played on plenty of good defensive teams, so it’s not a solo effort by any stretch. Nor does he guard Pierce on every possession the Truth is in the game. But by cursory measures, Pierce struggles against LeBron more than anyone in the league. His second worst career FG% against a team, after Cleveland, is 41.7% against Minnesota.

This was never more apparent than in their 2008 series, in which Pierce was aggressive with LeBron on the bench and nearly invisible with James on the court. In the first six games, Pierce averaged 15.8 points per game on 47.7% TS. Some of his decline can be attributed to exerting so much effort guarding LeBron — something he does well — but LeBron clearly defends Pierce well too, using his size and strength to eliminate Pierce’s advantage over other wing defenders.

The Celtics finally unleashed Pierce in game 7 of that series by using a lot of screen and roll action into LeBron. Something to keep in mind with a probable playoff battle looming again this May.

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In the last post, I looked at nine of the most explosive wing scorers of the past 25 years. In a 40-point game, the ball has to go in the hole frequently, thus, TS% is quite good on average in such games. But what about removing scoring from the equation and simply looking at shooting volume?

High-Volume Shooting

Let’s use field goal attempts to examine what happens when these players shoot a lot, setting the cutoff at 30 or more FGA’s in a game. These are high-volume attempt games, in which efficiency counts more than lower volume games.

Returning to variance, here are the standard deviations for the same nine players in 30+ FGA games. “Stdev” is the standard deviation for the statistic to its left:

Again, LeBron James is a beacon of consistency, although he only shoots 30+ shots about once in every 20 games. LeBron also shoots the ball much, much, much better than anyone else when he shoots it this much. Note the ridiculous TS%.

So does that translate to team success? Actually, no. The ONLY player of these nine perimeter scoring-machines to see his team’s win% increase when he shoots the ball so much is…you guessed it, Allen Iverson. (Kudos if you actually guessed it.) Below are the results, along with frequency of 30-shot games and relative true shooting percentage (Rel TS%):*

This, despite Iverson having a break-even relative TS% (only Wilkins was worse relative to the league environment in such games). Which hits at the volume-efficiency tradeoff argument, because Iverson seems to be a player who can increase his volume — here, 95 of 561 games (16%) with over 30 attempts — and maintain similar efficiency to his normal standard. That’s not a ringing endorsement for Iverson as a team cog, but it certainly helps to justify his role and value in a system like Philadelphia’s.

On the opposite end of the spectrum is Kobe Bryant, whose teams suffer mightily when he shoots the ball a lot. And, unfortunately, he’s done this about every eight games in his career. Bryant’s relative TS% in such games is almost 3% off his normal average in the same time period, and his scoring varies greatly. (How many players have a 40-point difference between their two highest FGA games?)

This is further evidence that good players can shoot too much. All of these stars, except for Allen Iverson, see a drop in their team win% in high-volume attempt games. Some might cry chicken-and-egg; Are the star players suddenly shooting this much because the team is losing, or are they losing because of so much shooting? There is ample evidence that one player going rogue, or worse, forcing shots doesn’t help an offense in the first place. Being behind is no excuse to abandon ship and undertake a flawed strategy.

Coming full circle, as far as I know, there isn’t a single advanced metric that considers variance. Nor is there an advanced metric that takes into account team strength in matters like variance and volume. Means are beneficial, but wins are tallied after 48 minutes. It’s not like overall point differential — while a great predictor — determines playoff seedings. Perhaps we should look beyond averages and weigh consistency and team strength against those averages in individual player analysis.

*Relative TS% and win% difference are weighted by year. For eg, if half of one’s 40-point games were in a single season, that one season’s TS% and win% differential accounted for half the weight in both categories.

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In the last post, I examined different measures of variance in this generation’s Mt. Rushmore of wing players, LeBron, Kobe, Wade and Michael Jordan, all the while keeping in mind that it’s possible for inconsistent play to result in a few more wins on weak teams and fewer wins on good teams.

Of those four superstars, Kobe Bryant had the most games with “inefficient shooting” (under 50% True Shooting) and the fewest games with “efficient” shooting (over 60% True Shooting). However, we ignored the amount of shots he attempted when he was shooting poorly or shooting well. Turns out, all four players shoot more when they’re shooting poorly. And of the group, Dwyane Wade has the biggest increase in FGA’s per 36 minutes in his inefficient shooting games. In order of change in FGA’s per 36 from good games to bad:

  1. Wade +1.2 (17.6  in good shooting games to 18.8 in bad ones)
  2. Kobe +0.9 (19.1 to 20.1)
  3. Jordan +0.4 (21.7 to 22.1)
  4. LeBron +0.2 (18.7 to 18.9)

Before we focus on attempts any further, let’s first look at what happens when elite wings score a lot.

High Volume Scoring

There have been just nine wing players with at least 25 40-point games since 1987 (the beginning of Basketball-Reference’s game logs):

  • Michael Jordan
  • Dominique Wilkins
  • Allen Iverson
  • Vince Carter
  • Kobe Bryant
  • Tracy McGrady
  • Gilbert Arenas
  • LeBron James
  • Dwyane Wade

We have our four usual suspects and five more players who collectively amassed 35 All-Star game appearances and 26 All-NBA nods. Not too shabby. Here is the volume and frequency of 40-point games from this group during their prime scoring years:

Not surprisingly, the greatest scorer in NBA history, Michael Jordan, dropped 40 in nearly one in every five games during his prime years. Yikes. Although Jordan isn’t the most efficient of the bunch in such games. That would be Gilbert Arenas, who boasts nearly 70% True Shooting in his 40-pointers:*

As expected, all these players increase their efficiency in 40-point games. Although Kobe’s shooting numbers are surprisingly low, residing next to someone labeled as an inefficient “chucker,” Allen Iverson. So Iverson and Kobe must not be helping their teams win those big games as much as their contemporaries. Right?

Wrong.

It turns out that Iverson’s teams actually improved the most when he scored 40 or more!*

In Iverson’s 72 40-point games, Philadelphia’s win% improved by nearly 20%. That’s a startling contrast – about 16 extra wins over the course of a season. But why would Iverson’s teams improve so much when he has the lowest relative TS% of the lot?

If we buy the argument that AI’s 76er teams lacked a scorer who could create his own offense — certainly a reasonable stance — then Iverson’s scoring explosions shored up that offensive deficiency and buoyed them to victory more often than his run-of-the-mill 25 or 30-point nights, regardless of the drop in efficiency relative to his peers. (This somewhat echoes Paine’s Monte Carlo run.) Besides, AI’s shooting efficiency in such games is still significantly better than both the league average and his own career average.

There’s also further evidence here supporting the idea that weaker teams are helped more by big performances: Jordan played on the best teams in this time period (win% with MJ in the lineup of .713) and saw the smallest change in team W-L when going for 40. From 1990-1998, once Chicago ascended to elite team status, the Bulls were 68-20 when Michael went for 40 or more, for a .772 win%. Slightly worse than his team’s .779 win% (387-110) when he didn’t go for 40.

Tracy McGrady played on the second worst teams of these nine players (Arenas the worst). When McGrady was in Orlando (01-04) the Magic went 19-11 (.633) in his 40-pointers. 121-144 (.457) in his other games. Then he went to a better Houston Rocket team, and went 7-4 (.636) in 40-point games and 119-66 (.643) in other games.

The same reasoning explains why LA has faired so well despite Kobe’s lower efficiency numbers; Many of Bryant’s games were in 03, and 05-07 when his team needed volume scoring. LA was 50-24 (.676 win%) in his 40-point games in those years, while going 112-119 (.485) in Kobe’s non-40 games. (In the other seasons, a .724 win% in his 29 40-point games and a .715 win% in all other games.)

So these players are helping bad teams with big scoring nights and not doing much for good teams with the same outbursts. Balance, it seems, is indeed better.

Yet we haven’t completely addressed the issue of what happens when players shoot a lot. That is the topic of Part III

*Relative TS% and win% difference are weighted by year. For eg, if half of one’s 40-point games were in a single season, that one season’s TS% and win% differential accounted for half the weight in both categories.

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Last June, Neil Paine over at Basketball-Reference examined consistent vs. inconsistent performances by Kobe Bryant and LeBron James vs. the Boston Celtics. Using one catch-all metric (statistical plus-minus), James and Bryant had similar average performances over the course of their series. But their game-to-game performances varied greatly; James was high-variance — some great games and some awful ones — while Bryant was steadier throughout. If we buy Neil’s simple Monte Carlo simulation, his findings were:

  • Good teams are helped more by a consistent player
  • Average teams are helped more by a consistent player
  • Bad teams are helped more by a high-variance player

This makes sense to a certain degree; Big performances by stars can boost bad teams to wins they otherwise wouldn’t have had, and the bad performances still result in losses they probably would have incurred anyway. In theory, the inverse would hold true for good teams and really bad performances by stars.

Last year’s NBA Finals aside,  Bryant is actually more high-variance than James using measures like points, FG% and GameScore. (GameScore is a rough measure of productivity for a single game.) Below is a comparison of variance between the best wings of my lifetime, Kobe (2001-2010), LeBron (2006-2010), Dwyane Wade (2006-2010) and Michael Jordan (1987-1998):

“Stdev” is the standard deviation of the statistic to its left. If we use a summary statistic like GameScore, LeBron wins the consistency battle handily. Jordan would place second by virtue of his ridiculous 25.3 average GameScore, then Wade and Kobe by the same logic.

If we focus on consistency of shooting and scoring, LeBron wins again. (LeBron outpacing the field is becoming a theme on this blog.) Of course, one could argue LeBron played with a weaker team from 2006-2010, so higher variance would be better when compared to Kobe and Jordan. But unlike Neil’s Monte Carlo run, LeBron’s averages are significantly higher than Kobe’s and Wade’s to begin with.

Kobe, not surprisingly, is higher variance with his FG% — easily the lowest of the lot — and in particular with his scoring performances. But only looking at standard deviations overlooks the importance of the averages. A lower average means more poor shooting games.

EDIT: Bryant’s GameScore standard deviation is 9.5 (mean 22.0) from 2005-2007 on his “weak” teams.

Another way to view consistency is by frequency of games, delineated in a specific range. For instance, we can call games over 60% True Shooting (TS) “efficient” shooting games and games under 50% TS “inefficient” shooting games.

Player Efficient Games (> 60% TS) Inefficient Games (< 50% TS)
Michael Jordan 41.4% 20.5%
LeBron James 40.1% 21.6%
Dwyane Wade 37.8% 26.7%
Kobe Bryant 35.3% 29.3%

Now Bryant’s shooting inconsistency can be seen more clearly. While James and Jordan have an efficient game twice as often as an inefficient one, Kobe shoots well a little more than 1/3 of the time, and shoots poorly a little less than 1/3 of the time. And, if we come full circle to the original claim about consistency helping good teams, that doesn’t bode well for Kobe Bryant’s impact on wins relative to his averages.

For those visually curious, and for the sake of consistency, here is the distribution of TS% for all games played in the respective time frames:

The frequency of games based on TS% for elite wings. Frequency (y-axis) is the percentage of games a player shot a given TS% (x-axis) for the following years: Jordan (87-98) Kobe (01-10) LeBron (06-10) and Wade (06-10).

Of course, none of this accounts for volume — in theory, players should shoot more when they shoot well, and shoot less when they shoot poorly. And that is the topic of the next post: high-volume scoring games.

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