Though experience tells us that “clutch”
is real, it is devilishly hard to measure in any sport. But in basketball specifically,
what does it mean to be clutch? A clutch player is thought to be someone that
teammates can rely on, in the most pressurised of situations. So, presumably, helping a team
win close games is a major indicator of “clutchness.” But, here is where we run into our first big
problem. Studies going back more than a decade have found little in the way of evidence suggesting
teams have any special ability, or lack thereof, to win close games. Close games aren’t exactly
coin flips. In this study, better teams win in clutch situations more frequently than
worse teams. However, they win them at lower rates than “non-clutch” games.
To isolate “clutch” as much as possible, The Athletic defines the term fairly narrowly.
Looking at team performance, they only count games with a margin of three or fewer points
at some time in the last two minutes of the fourth quarter.
Using that definition, The Athletic looked at team records in games qualifying as clutch
from 1996-97 to 2018-19 and compared them to performance in all other games within a
given season. As mentioned above, teams that were good at winning non-clutch games were
generally better at winning these very close “clutch” games, but late/close situations
evened the odds considerably. Over that span, a simple linear regression
modeling clutch record based on broader performance predicts a team winning at a 60-win pace (73.2
win percent) in non-clutch games to a 47-win pace (57.4 win percent) in clutch games. On
the flip side, the model would predict that a team winning 24.4 percent of non-clutch
games (20-win pace) would jump up to 41.7 percent (just over 34-win pace) in clutch
situations. So for better teams, the lesson is that the
best way to win close games is to not play close games.
Of course, every season a number of teams dramatically overperform and underperform
their overall trends in “clutch” games. Last year, the Nuggets (54-28) and Clippers
(48-34) won 5.8 and 5.5 more “clutch” games respectively than would be predicted
by their play in the remainder of games, while the Thunder (49-33) ran five games under the
simple model’s prediction. While it might be tempting to build a narrative
about the character of certain teams based on clutch performance, history suggests that
to do so would be a case of being fooled by randomness. Over the same 23-year sample,
there is virtually no correlation between teams’ level of overperformance or underperformance
in clutch games from one year to the next: To restate, there is little evidence that
teams have a particular ability or lack thereof to win close games that is consistent from
one season to the next. Of course, given the size of the study, there
are examples of teams that seem to always excel or disappoint in these scenarios. Minnesota,
had a worse clutch record than expected every season from 2007-08 to 2014-15, while Memphis
was at least three clutch wins above expectations five of six years from 2011-12 to 2016-17.
We can’t rule out there being something systematic about these streaks of performance,
and it is certainly enticing to note that time period is the height of the Grit’n’Grind
era for Memphis while those Wolves teams (and more pertinently, Kevin Love in particular),
were viewed as simply not having what it took to close out tight games. But as real as those
factors might feel, they are not readily distinguishable from normal variance rather than something
intrinsic to those teams. So, if it is hard to describe a team as consistently
clutch, what about players? Given the primacy of stars in the NBA, surely the best of the
best can be shown to rise to the moment, right? Much as with teams, the precise definition
of clutch can skew the analysis, so it is important to be specific. So, going back to
the 2004-05 season, The Athletic looked at every shot taken with the chance to tie or
take the lead with under 30 seconds remaining in the fourth quarter or overtime.
The first thing to note is this has proven to be an incredibly difficult situation for
players as evidenced by an overall average of 29.8 FG percent on these “hero shots”
as we’ll call them. Exactly why efficiency drops so much in these situations is a discussion
unto itself. A brief theory is that the constraints of these moments remove much of the element
of deception. The defense will usually have a pretty good idea of both who will take the
shot (the offensive team’s best perimeter player) and when they will take it as dictated
by time and score. This low overall efficiency is the first blow
against the tradition of castigating players who fail to score in these scenarios. Much
like a baseball player hitting .350 is cause for celebration, consistently shooting 35
percent on game winners would place a player among the best ever.
Consistency is a key word there. Only seven players have taken even 100 “hero shots”
since 2004-05, and conveniently for debate purposes LeBron James and Kobe Bryant are
tied for most attempts at 128. As with a team’s clutch record over a season tending towards
a number predicted by their non-clutch play, some players have hit more or less frequently
than that roughly 30 percent historical average. But as attempts increase, overall accuracy
on game-winning shots regresses heavily towards that mean: Plotting in some names, it’s hard to discern
much of a pattern in which players are above or below that 30 percent line, though it is
revealing how heavily attempts in this situation skew towards perimeter players. While we do not have the data to fully explore
the circumstances of pre-tracking era games, it seems likely that the players in the top
left corner (such as Tim Duncan and Anthony Davis) are not getting the same mix of shots
as those with more voluminous attempts. Naturally, finishing off a putback or dump-off from a
teammate at the rim is a considerably easier attempt, even in the most pressure-packed
moments, than breaking down a set defense by oneself. But unless the entire coaching
profession is completely incompetent, those easier shots are exceptions rather than the
rule. Much as with teams that overperformed, it
is tempting to point to players such as Dirk Nowitzki and Chris Paul and suggest there
is something inherent about their games that make them uniquely clutch. And that might
be true. Those two, along with Carmelo Anthony and Joe Johnson, rather famously subsisted
on the sort of pullup two pointers that tend to be the result of the late-game isolations.
So it might stand to reason that these players are better equipped to come through than others
given they were operating in their normal comfort zones.
However, consider the overall distribution of “extra” makes for players with at least
20 “hero” attempts over that span: While this distribution is not proof that
performance in these late-game scenarios is essentially a 70/30 weighted coin flip, it
is pretty much what it would look like if it were.
This is not to say that “clutchness” doesn’t exist, but it’s more of a qualitative factor
than something for which there are precise parameters.