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:

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.

on February 10, 2011 at 1:02 am |RavenredYou invite the wrath of the Kobinators with such cavalier disregard. 🙂

Be interested to know whether this holds true at a team level as well (i.e. if Kobe shoots well, does that mean the Lakers do, or…)

The pro-Rose crew on RealGM tend to take that path (“Rose is the only offensive option on that team!!!!@!”), and tracking the efficiency of a team against their nominal star might confirm that hypothesis (at least for the Bulls).

on February 10, 2011 at 9:57 am |ElGeeHey raven – I’d like to think I invite the wrath of everyone with such cavalier disregard. 😉 The next parts look at team performance — if those 2 posts don’t quite answer your question, let me know and I’ll consider another follow up. Perhaps a Rose post is long overdue anyway.

There’s some interesting data regarding Allen Iverson that could be similar to Rose’s situation in Chicago. (I’m impressed with what I’ve seen from Rose this year, for the record…although I’m not entirely sure what to make of him yet.)

on February 10, 2011 at 11:19 am |ElGeeSomeone asked about Kobe 2006-2010 (the same time period of Wade and James). Here are his numbers from 06-10 with Stdev in parens:

FG%: .459 (11.1%)

Pts: 29.8 (10.3)

Gmsc: 21.0 (8.9)

TS%: .565 (11.8%)

on February 12, 2011 at 9:24 am |ElGeeSomeone also asked about Iverson for these same numbers.

Iverson’s breakdown in 591 G:

> 60% TS: 18.8%

< 50% TS: 45.0%

—

Mean (StDev)

FG% 42.0 (10.3%)

ppg 29.2 (9.1)

GmSc 19.2 (9.0)

TS% 51.3 (10.3%)

His team win% was +.211 when he was over 60 and just -.178 under 50. Particularly interesting since his mean game score is lower than everyone else's but his StDev higher.

on February 14, 2011 at 9:12 am |Variance, Volume and Elite Wings, Part II « Back Picks: Fleeting Sports Thoughts[…] « Variance, Volume and Elite Wings, Part I Variance, Volume and Elite Wings, Part III […]