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      "parent_permlink": "basketball",
      "author": "hooppress",
      "permlink": "can-you-measure-clutch-in-basketball-or-by-tifo-or-hooppress",
      "title": "Can You Measure CLUTCH in BASKETBALL? | BY TIFO | HOOPPRESS",
      "body": "![clutch.png](https://cdn.steemitimages.com/DQmVH9CgveDPt6xLKcqTa674vZXMchkosyCewVrjxo8GDzi/clutch.png)\n> photo from the atheletic.com | also image credit links are all at the bottom/end of this article\n<div class=\"text-justify\">\nThough experience tells us that “clutch” is real, it is devilishly hard to measure\nin any sport. But in basketball specifically, what does it mean to be clutch?\nA clutch player is thought to be someone that teammates can rely on, in the most pressurised\nof situations. So, presumably, helping a team win close games is a major indicator of “clutchness.”\nBut, here is where we run into our first big problem. Studies going back more than a decade\nhave found little in the way of evidence suggesting teams have any special ability, or lack thereof,\nto win close games. \n<br>\n<br>\n<br>\nClose games aren’t exactly coin flips. In this study, better teams win\nin clutch situations more frequently than worse teams. However, they win them at lower\nrates than “non-clutch” games. To isolate “clutch” as much as possible,\nThe Athletic defines the term fairly narrowly. Looking at team performance, they only count\ngames with a margin of three or fewer points at some time in the last two minutes of the\nfourth quarter. \n<br>\n<br>\n<br>\nhttps://res-1.cloudinary.com/ybmedia/image/upload/c_scale,f_auto,q_auto,w_700/v1/m/5/6/561b42ca83d665224bb8b05338995b1300e34f33/kobe2000finals.jpg\n<br>\n<br>\nUsing that definition, The Athletic looked\nat team records in games qualifying as clutch from 1996-97 to 2018-19 and compared them\nto performance in all other games within a given season. As mentioned above, teams that\nwere good at winning non-clutch games were generally better at winning these very close\n“clutch” games, but late/close situations evened the odds considerably.\nOver that span, a simple linear regression modeling clutch record based on broader performance\npredicts a team winning at a 60-win pace (73.2 win percent) in non-clutch games to a 47-win\npace (57.4 win percent) in clutch games. On the flip side, the model would predict that\na team winning 24.4 percent of non-clutch games (20-win pace) would jump up to 41.7\npercent (just over 34-win pace) in clutch situations.\n<br>\n<br>\n<br>\nSo for better teams, the lesson is that the best way to win close games is to not play\nclose games. Of course, every season a number of teams\ndramatically overperform and underperform their overall trends in “clutch” games.\nLast year, the Nuggets (54-28) and Clippers (48-34) won 5.8 and 5.5 more “clutch”\ngames respectively than would be predicted by their play in the remainder of games, while\nthe Thunder (49-33) ran five games under the simple model’s prediction.\nWhile it might be tempting to build a narrative about the character of certain teams based\non clutch performance, history suggests that to do so would be a case of being fooled by\nrandomness. Over the same 23-year sample, there is virtually no correlation between\nteams’ level of overperformance or underperformance in clutch games from one year to the next:\nTo restate, there is little evidence that teams have a particular ability or lack thereof\nto win close games that is consistent from one season to the next.\n<br>\n<br>\n<br>\nhttps://hoopshabit.com/wp-content/blogs.dir/307/files/2014/01/8086228.jpg\n<br>\n<br>\nOf course, given the size of the study, there are examples of teams that seem to always\nexcel or disappoint in these scenarios. Minnesota, had a worse clutch record than expected every\nseason from 2007-08 to 2014-15, while Memphis was at least three clutch wins above expectations\nfive of six years from 2011-12 to 2016-17. We can’t rule out there being something\nsystematic about these streaks of performance, and it is certainly enticing to note that\ntime period is the height of the Grit’n’Grind era for Memphis while those Wolves teams (and\nmore pertinently, Kevin Love in particular), were viewed as simply not having what it took\nto close out tight games. But as real as those factors might feel, they are not readily distinguishable\nfrom normal variance rather than something intrinsic to those teams.\n<br>\n<br>\n<br>\nSo, if it is hard to describe a team as consistently clutch, what about players? Given the primacy\nof stars in the NBA, surely the best of the best can be shown to rise to the moment, right?\nMuch as with teams, the precise definition of clutch can skew the analysis, so it is\nimportant to be specific. So, going back to the 2004-05 season, The Athletic looked at\nevery shot taken with the chance to tie or take the lead with under 30 seconds remaining\nin the fourth quarter or overtime. The first thing to note is this has proven\nto be an incredibly difficult situation for players as evidenced by an overall average\nof 29.8 FG percent on these “hero shots” as we’ll call them. Exactly why efficiency\ndrops so much in these situations is a discussion unto itself. \n<br>\n<br>\n<br>\nhttps://images2.minutemediacdn.com/image/upload/c_fill,w_912,h_516,f_auto,q_auto,g_auto/shape/cover/sport/cleveland-cavaliers-v-los-angeles-lakers-5d1547183ee312957e000001.jpg\n<br>\n<br>\nA brief theory is that the constraints\nof these moments remove much of the element of deception. The defense will usually have\na pretty good idea of both who will take the shot (the offensive team’s best perimeter\nplayer) and when they will take it as dictated by time and score.\nThis low overall efficiency is the first blow against the tradition of castigating players\nwho fail to score in these scenarios. Much like a baseball player hitting .350 is cause\nfor celebration, consistently shooting 35 percent on game winners would place a player\namong the best ever. Consistency is a key word there. Only seven\nplayers have taken even 100 “hero shots” since 2004-05, and conveniently for debate\npurposes LeBron James and Kobe Bryant are tied for most attempts at 128. \n<br>\n<br>\n<br>\nAs with a team’s\nclutch record over a season tending towards a number predicted by their non-clutch play,\nsome players have hit more or less frequently than that roughly 30 percent historical average.\nBut as attempts increase, overall accuracy on game-winning shots regresses heavily towards\nthat mean:\nPlotting in some names, it’s hard to discern much of a pattern in which players are above\nor below that 30 percent line, though it is revealing how heavily attempts in this situation\nskew towards perimeter players.\nWhile we do not have the data to fully explore the circumstances of pre-tracking era games,\nit seems likely that the players in the top left corner (such as Tim Duncan and Anthony\nDavis) are not getting the same mix of shots as those with more voluminous attempts. Naturally,\nfinishing off a putback or dump-off from a teammate at the rim is a considerably easier\nattempt, even in the most pressure-packed moments, than breaking down a set defense\nby oneself. \n<br>\n<br>\n<br>\nhttps://a3.espncdn.com/combiner/i?img=%2Fphoto%2F2017%2F0207%2Fr179073_1296x729_16%2D9.jpg\n<br>\n<br>\nBut unless the entire coaching profession is completely incompetent, those\neasier shots are exceptions rather than the rule.\nMuch as with teams that overperformed, it is tempting to point to players such as Dirk\nNowitzki and Chris Paul and suggest there is something inherent about their games that\nmake them uniquely clutch. And that might be true. Those two, along with Carmelo Anthony\nand Joe Johnson, rather famously subsisted on the sort of pullup two pointers that tend\nto be the result of the late-game isolations. So it might stand to reason that these players\nare better equipped to come through than others given they were operating in their normal\ncomfort zones. However, consider the overall distribution\nof “extra” makes for players with at least 20 “hero” attempts over that span:\nWhile this distribution is not proof that performance in these late-game scenarios is\nessentially a 70/30 weighted coin flip, it is pretty much what it would look like if\nit were. This is not to say that “clutchness” doesn’t\nexist, but it’s more of a qualitative factor than something for which there are precise\nparameters.\n</div>\n\n<br>\n<br>\n<br>\n![fb cover.jpg](https://cdn.steemitimages.com/DQmbiCNsBYvxVgS3fDEMj1tNXbBHa5QBzWQBQFeHMEg2Ak1/fb%20cover.jpg)",
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