Shooting Performance - Clutch vs. Garbage Time
In this recent post, I laid out an approach for measuring clutch play in the NBA, using my win probability model as the underlying framework. In that post, I broke down a players win probability added (WPA) contributions into three components: expected WPA, clutch WPA, and garbage time WPA. The clutch WPA component measures the "excess" win probability added (or subtracted) a player has amassed due to performance in clutch situations.Under that definition, I found that the Rockets' James Harden has the most clutch WPA so far this season. However, for this post, I will take a different approach to measuring clutch play. Rather than focus on aggregate WPA contributions, I will measure shooting performance (i.e. eFG%) in both clutch and garbage time situations, and see how they vary for each player. Are there players that "elevate their game" when the stakes are higher?
Defining Clutch and Garbage Time
Previous attempts to define clutch play have been a bit on the kludge-y side (see NBA.com's "last five minutes, within five points" definition). A win probability model allows for a less arbitrary determination of when a game is in a clutch or garbage time situation (although it is still not without its own drawbacks).I define a clutch situation to be when the win probability added (WPA) of a given play is greater than the typical WPA for that type of play. To use an example from Friday night's double overtime game between the Heat and the Timberwolves: A turnover usually costs a team -2.1% in win probability. However, with 11 seconds to go and his team up by 1, Chase Budinger turned the ball over, dropping his teams's win probability by 10.8%. 10.8% is greater than 2.1%, so under my definition, this was a clutch situation (and I think most would agree).
Conversely, there's also "garbage time", which I'm defining as plays in which the win probability added is less than the expected WPA for that type of play. Take another game from that same night: the Warriors' 102-69 curb-stomping of the Kings. With 8:32 left in the third quarter, and the Kings down 29-68, Ray McCallum missed a pull up jump shot. A missed field goal typically costs a team -1.4% in win probability, but McCallum's miss only cost the Kings -0.1% (their win probability dropped from 0.7% to 0.6%). This would be classified as a garbage time play (and once again, I think most would agree).
Measuring Clutch Performance for the Top 25
The table below summarizes effective field goal percentage (eFG%) for the top 25 shooters in the NBA (according to field goal attempts). Shooting performance is shown for both clutch and garbage time, and the "Diff" column is the difference between a players clutch eFG% and garbage time eFG%.| Total | Garbage | Clutch | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Player | FGA | eFG | FGA | eFG | FGA | eFG | Diff | ||||
| Carmelo Anthony | 1,561 | 50.4% | 11 | 730 | 50.8% | 9 | 831 | 50.0% | 13 | -0.8% | 19 |
| Kevin Durant | 1,499 | 56.9% | 2 | 658 | 55.5% | 4 | 841 | 58.1% | 2 | 2.6% | 8 |
| DeMar DeRozan | 1,318 | 45.3% | 23 | 580 | 43.9% | 25 | 738 | 46.5% | 23 | 2.6% | 7 |
| LaMarcus Aldridge | 1,314 | 45.9% | 22 | 572 | 44.6% | 21 | 742 | 46.8% | 22 | 2.2% | 10 |
| Kevin Love | 1,285 | 53.0% | 7 | 656 | 54.2% | 5 | 629 | 51.7% | 9 | -2.5% | 20 |
| Blake Griffin | 1,275 | 53.3% | 6 | 585 | 52.2% | 7 | 690 | 54.2% | 4 | 2.0% | 12 |
| Stephen Curry | 1,266 | 55.8% | 3 | 530 | 58.1% | 2 | 736 | 54.2% | 4 | -3.9% | 25 |
| Paul George | 1,263 | 49.0% | 14 | 581 | 47.8% | 15 | 682 | 50.1% | 11 | 2.3% | 9 |
| Al Jefferson | 1,242 | 51.1% | 9 | 571 | 48.1% | 14 | 671 | 53.7% | 6 | 5.6% | 2 |
| John Wall | 1,238 | 48.3% | 17 | 510 | 46.7% | 17 | 728 | 49.4% | 15 | 2.7% | 6 |
| Damian Lillard | 1,226 | 50.4% | 11 | 556 | 50.8% | 9 | 670 | 50.1% | 11 | -0.7% | 18 |
| LeBron James | 1,202 | 61.1% | 1 | 516 | 59.9% | 1 | 686 | 62.1% | 1 | 2.2% | 10 |
| Josh Smith | 1,202 | 44.1% | 25 | 581 | 45.5% | 20 | 621 | 42.8% | 25 | -2.7% | 22 |
| Dirk Nowitzki | 1,180 | 54.4% | 4 | 539 | 56.1% | 3 | 641 | 52.9% | 8 | -3.2% | 24 |
| Kyrie Irving | 1,176 | 48.7% | 15 | 542 | 48.6% | 13 | 634 | 48.8% | 16 | 0.2% | 16 |
| Thaddeus Young | 1,169 | 49.1% | 13 | 589 | 50.3% | 11 | 580 | 47.8% | 19 | -2.5% | 20 |
| Monta Ellis | 1,159 | 47.1% | 18 | 467 | 47.0% | 16 | 692 | 47.1% | 21 | 0.1% | 17 |
| Klay Thompson | 1,144 | 52.3% | 8 | 562 | 51.5% | 8 | 582 | 53.0% | 7 | 1.5% | 13 |
| Rudy Gay | 1,099 | 48.4% | 16 | 495 | 46.2% | 19 | 604 | 50.2% | 10 | 4.0% | 5 |
| James Harden | 1,090 | 53.4% | 5 | 503 | 48.9% | 12 | 587 | 57.3% | 3 | 8.4% | 1 |
| Zach Randolph | 1,086 | 46.3% | 21 | 483 | 44.0% | 24 | 603 | 48.1% | 18 | 4.1% | 3 |
| Isaiah Thomas | 1,069 | 50.9% | 10 | 467 | 52.5% | 6 | 602 | 49.8% | 14 | -2.7% | 22 |
| Jeff Green | 1,067 | 46.5% | 20 | 527 | 44.4% | 22 | 540 | 48.5% | 17 | 4.1% | 3 |
| Kemba Walker | 1,065 | 44.8% | 24 | 459 | 44.4% | 22 | 606 | 45.1% | 24 | 0.7% | 15 |
| Bradley Beal | 1,049 | 47.1% | 18 | 487 | 46.3% | 18 | 562 | 47.8% | 19 | 1.5% | 14 |
For the most part, there doesn't seem to be dramatic differences in player performance between clutch and garbage time. In fact, according to the Fisher Exact Test, the only player on this table with a statistically significant difference in performance is, you guessed it,
Lebron James has slightly better performance in the clutch this season, but not by much. But, as you can see, Lebron really doesn't need to elevate his game during the clutch. He's good at his job, regardless of the situation. Stephen Curry is an interesting case, with poorer performance in clutch situations, despite a reputation for late game heroics. But a 54.2% eFG% in the clutch still puts him at #4 out of the top 25 on this list.
It's not really binary
As I mentioned, the clutch definition above still has some drawbacks, with one being that every single play is pigeonholed into either clutch or garbage time. A more realistic definition would allow for plenty of "normal basketball" situations that are neither clutch nor garbage. One way to achieve this would be to only define clutch if the WPA was in the top quartile, as opposed to just above average. I intend to explore this definition in a future post. Also on my to-do list is to examine the persistence of clutch play. Are there players that consistently elevate their game? Or are we just chasing statistical noise? Tune in next week for the dramatic conclusion.
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