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1 NBA Comeback Clutchness: Real Or Just Noise? Sandy Huang and Toa

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1 NBA Comeback Clutchness: Real or Just Noise? Sandy Huang and Toa Lohe Introduction In his last NBA game, Kobe Bryant famously scored 60 points against the Utah Jazz to lead the Los Angeles Lakers to a 101-96 victory. The game was entertaining not just because Kobe scored lots of points but because of how he scored those points. Let us set the scene. With about three minutes remaining in the 4th quarter, the Lakers were down 10 points, and it seemed that Kobe would likely end his career with a loss despite having already scored 45 points. He, however, surprised us all by proceeding to score 15 straight points for the Lakers, a brilliant capstone performance to end a legendary 20-year career in the NBA.1 At the end of the night, Kobe reminded everyone of why many of us watch sports in the first place: to feel the emotional suspense of seeing people struggle against—and sometimes even overcome—seemingly improbable odds.2 This ability to overcome seemingly improbable odds is what we often nebulously call clutchness. Inspired by Kobe’s last game, our final project quantified the clutchness of NBA players. In particular, we were interested in situations in which a player’s team was either behind by 5 points (or less) or tied (but not ahead) in the last 5 minutes of the 4th quarter (or overtime). Let us refer to this particular subset of clutchness as comeback clutchness. In contrast to comeback clutchness is escape clutchness—when a player’s team is either ahead by 5 points (or less) or tied (but not ahead) in the last 5 minutes of the 4th quarter (or overtime). We made this particular distinction between comeback clutchness and escape clutchness because of both our assumption that there is a psychological difference between these two scenarios that significantly impacts how players perform and the fact the NBA does not provide data on situations where teams are only behind/ahead and not tied. Finally, one of the main aims of our project is to find out whether special comeback clutchness performances (e.g. Kobe’s last game) can be repeated or if their manifestations are just noise (i.e. random). Background Previous work on NBA clutchness has been done by 82games3 and Liberty Ballers4 (a SB Nation blog for the Philadelphia 76ers). The first study done by 82games focused on the most clutch players in terms of field goals attempted, points scored, effective field goal percentage, foul drawing ability, and free throw shooting. The second study done by 82games focused on plus- minus, win-loss record, rebounding, passing, and shot creation (based on unassisted field goals made per 48 minutes). The third study done by 82games focused on the difference between non- clutch and clutch moments, PER (Player Efficiency Rating), and opposing player PER. Lastly, the study done by Liberty Ballers focused on clutch shooting. None of these four studies, however, focused on comeback clutchness. 1 For the sake of Kobe’s mythology, let’s ignore the officiating shenanigans at the end (e.g. the Laker’s Julius Randle setting hilariously illegal screens on the Jazz’s Gordon Hayward). 2 Seth Partnow of VICE Sports more eloquently defined it as “[t]hat anticipation, the moment just before the roller coaster tips over the crest of the big drop [...] the thrill that keeps us coming back.” https://sports.vice.com/en_au/article/kobe-bryant-majored-in-drama-not-math 3 http://www.82games.com/clutchplayers.htm http://www.82games.com/clutchplay2.htm http://www.82games.com/clutchplay3.htm 4 http://www.libertyballers.com/2012/2/29/2832299/lebron-james-kobe-bryant-dwyane-wade-clutch-nba-playoffs-4th-quarter 2 Methods By using “Clutch Traditional Stats” 5 and “Clutch Advanced Stats”6 provided by the NBA, we formulated a comeback clutchness version of Justin Kubatko’s Win Shares statistic (i.e. the estimated number of wins a player produces for his team).7 Below are all the necessary conditions for a player’s stats to be included in our analysis: 1) The statistic is accumulated in the last 5 minutes of the 4th quarter (or overtime). 2) The player’s team is either behind by 5 points (or less) or tied (but not ahead). 3) The player has played in at least a total of 50 minutes. In order to normalize for the total number of minutes played by each player, we also calculated comeback clutchness Win Shares Per 48.8 To calculate Win Shares, Offensive Win Shares are added to Defensive Win Shares. Below are the details of calculating Offensive Win Shares and Defensive Win Shares: Player Points and Defensive Rating are already included in the player data provided by the NBA.9 Additionally, Team Minutes10 and Team Pace11 are already included in the team data provided by the NBA. Below is a table detailing how to calculate the other statistics: Statistic Calculation Player Possessions Player Pace12 ÷ 48 × Minutes Played × Usage Rate13 Team Defensive Possessions Opponent’s Total Points14 ÷ Team Defensive Rating15 × 100 League Points Per Possession Total League Points ÷ Sum of Each Team’s (Pace ÷ 48 × Minutes Played) League Points Per Game Total League Points ÷ (Total Minutes Played ÷ 48) League Pace Sum of Each Team’s (Pace ÷ 48 × Minutes Played) ÷ (Total Minutes Played ÷ 48) 5 Comeback clutchness traditional player filter for analysis of 2015-2016 season: http://stats.nba.com/league/player/#!/clutch/?CF=MIN*GE*50&Season=2015- 16&SeasonType=Regular%20Season&AheadBehind=Behind%20or%20Tied&PerMode=Totals 6 Comeback clutchness advanced player filter for analysis of 2015-2016 season: http://stats.nba.com/league/player/#!/clutch/advanced/?Season=2015- 16&SeasonType=Regular%20Season&AheadBehind=Behind%20or%20Tied&CF=GP*GE*10 7 http://www.basketball-reference.com/about/ws.html 8 Divide by the total number of minutes played and then multiplying by 48 9 See footnotes 5 and 6 10 Comeback clutchness traditional team filter for analysis of 2015-2016 season: http://stats.nba.com/league/team/#!/clutch/?Season=2015- 16&SeasonType=Regular%20Season&PerMode=Totals&AheadBehind=Behind%20or%20Tied 11 Comeback clutchness advanced team filter for analysis of 2015-2016 season: http://stats.nba.com/league/team/#!/clutch/advanced/?Season=2015- 16&SeasonType=Regular%20Season&AheadBehind=Behind%20or%20Tied 12 See footnote 6 13 See footnote 6 14 Comeback clutchness opponent team filter for analysis of 2015-2016 season: http://stats.nba.com/league/team/#!/clutch/opponent/?Season=2015- 16&SeasonType=Regular%20Season&AheadBehind=Behind%20or%20Tied&PerMode=Totals 15 See footnote 11 and Wikipedia: https://en.wikipedia.org/wiki/Defensive_rating 3 In addition to this first analysis of comeback clutchness, we also conducted subsequent analysis on the value of comeback clutchness, the difference between comeback clutchness and escape clutchness, the difference between comeback clutchness and regular performance, and the repeatability of comeback clutchness. The value of comeback clutchness was measured as the differential between comeback clutchness Win Shares Per 48 and regular season Win Shares Per 48. The difference between comeback clutchness and escape clutchness was measured by using F-tests and t-tests, and the same method was used for the difference between comeback clutchness and regular performance. Finally, the repeatability of comeback clutchness was measured as the year-to-year correlation. We did these analyses for every season since the 2001-2002 season and also looked at comeback clutchness plus-minus and PIE (Player Impact Estimate).16 Results Comeback clutchness for the 2015-2016 season: Top 10 Comeback Clutchness (WS/48) Bottom 10 Comeback Clutchness (WS/48) 1) Andre Drummond (1.10) 1) Isaiah Canaan (-0.92) 2) Stephen Curry (1.06) 2) Brandon Knight (-0.59) 3) Draymond Green (1.06) 3) Al-Farouq Aminu (-0.45) 4) Klay Thompson (0.90) 4) Mason Plumlee (-0.41) 5) Dirk Nowitzki (0.87) 5) Trevor Booker (-0.33) 6) LeBron James (0.85) 6) Damian Lillard (-0.29) 7) Deron Williams (0.79) 7) Rajan Rondo (-0.28) 8) Chandler Parsons (0.78) 8) PJ Tucker (-0.27) 9) Jeff Green (0.70) 9) Khris Middleton (-0.23) 10) Danilo Gallinari (0.69) 10) Robert Covington (-0.22) Value of comeback clutchness for the 2015-2016 season: Top 10 Differential (WS/48) Bottom 10 Differential (WS/48) 1) Andre Drummond (0.97) 1) Isaiah Canaan (-0.95) 2) Draymond Green (0.87) 2) Brandon Knight (-0.64) 3) Klay Thompson (0.76) 3) Mason Plumlee (-0.55) 4) Stephen Curry (0.75) 4) Al-Farouq Aminu (-0.54) 5) Dirk Nowitzki (0.73) 5) Damian Lillard (-0.46) 6) Deron Williams (0.71) 6) Trevor Booker (-0.45) 7) Chandler Parsons (0.67) 7) Rajan Rondo (-0.36) 8) Jeff Green (0.64) 8) Russell Westbrook (-0.36) 9) LeBron James (0.61) 9) Khris Middleton (-0.33) 10) Jeremy Lin (0.60) 10) Serge Ibaka (-0.32) 16 PIE’s explanation can be found here: http://stats.nba.com/help/glossary/ 4 Comeback clutchness for the past 15 seasons: Top 5 Players by Comeback Clutchness Win Shares Per 48 Season 1 2 3 4 5 2015-2016 Andre Drummond Stephen Curry Draymond Green Klay Thompson Dirk Nowitzki 2014-2015 Pau Gasol Joakim Noah Roy Hibbert Zach Randolph Jimmy Butler 2013-2014 Greivis Vasquez Mike Conley James Harden Dirk Nowitzki Damian Lillard 2012-2013 Chris Bosh Paul Pierce Jeff Green Ray Allen LeBron James 2011-2012 Andrew Bynum Joe Johnson Udonis Haslem Roy Hibbert Zaza Pachulia 2010-2011 Mo Williams Dirk Nowitzki Tyson Chandler Manu Ginobili Serge Ibaka 2009-2010 LeBron James Kobe Bryant Dirk Nowitzki Marc Gasol Chauncey Billups 2008-2009 Pau Gasol Dwight Howard Kobe Bryant Jason Terry Tony Parker 2007-2008 LeBron James Stephen Jackson Chris Paul Amar'e Stoudemire Jeff Green 2006-2007 Josh Howard Dirk Nowitzki Jason Terry Samuel Dalembert Jason Kapono 2005-2006 Keith Bogans Chauncey Billups Chris Kaman Rasheed Wallace Earl Boykins 2004-2005 Ben Gordon Chauncey Billups Tyson Chandler Kirk Hinrich Kenny Thomas 2003-2004 Kobe Bryant Shaquille O'Neal Reggie Miller Metta World Peace Gary Payton 2002-2003 Tony Battie Tony Delk Jason Terry Chauncey Billups Shareef Abdur-Rahim 2001-2002 Raef LaFrentz Ervin Johnson Dirk Nowitzki Ryan Bowen Antonio Davis Bottom 5 Players by Comeback Clutchness Win Shares Per 48 Season 1 2 3 4 5 2015-2016 Isaiah Canaan Brandon Knight Al-Farouq Aminu Mason Plumlee Trevor Booker 2014-2015 Tim Hardaway Jr.
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  • Individual Statistical Leaders

    Individual Statistical Leaders

    Tournament Individual Leaders (as of Aug 14, 2012) All games FIELD GOAL PCT (min. 10 made) FG ATT Pct FIELD GOAL ATTEMPTS G Att Att/G -------------------------------------------- --------------------------------------------- Darius Songaila-LTH........... 24 30 .800 Patrick Mills-AUS............. 6 116 19.3 Tyson Chandler-USA............ 14 20 .700 Luis Scola-ARG................ 8 106 13.3 Andre Iguodala-USA............ 14 20 .700 Manu Ginobili-ARG............. 8 103 12.9 Aaron Baynes-AUS.............. 21 32 .656 Kevin Durant-USA.............. 8 101 12.6 Anthony Davis-USA............. 11 17 .647 Pau Gasol-ESP................. 8 100 12.5 Kevin Love-USA................ 34 54 .630 Dan Clark-GBR................. 15 24 .625 FIELD GOALS MADE G Made Made/G Tomofey Mozgov-RUS............ 33 53 .623 --------------------------------------------- LeBron James-USA.............. 44 73 .603 Pau Gasol-ESP................. 8 57 7.1 Serge Ibaka-ESP............... 26 45 .578 Luis Scola-ARG................ 8 56 7.0 Nene Hilario-BRA.............. 12 21 .571 Manu Ginobili-ARG............. 8 51 6.4 Pau Gasol-ESP................. 57 100 .570 Kevin Durant-USA.............. 8 49 6.1 Patrick Mills-AUS............. 6 49 8.2 3-POINT FG PCT (min. 5 made) 3FG ATT Pct 3-POINT FG ATTEMPTS G Att Att/G -------------------------------------------- --------------------------------------------- Shipeng Wang-CHN.............. 13 21 .619 Kevin Durant-USA.............. 8 65 8.1 S. Jasikevicius-LTH........... 7 12 .583 Carlos Delfino-ARG............ 8 54 6.8 Dan Clark-GBR................. 8 14 .571 Patrick Mills-AUS............. 6 48 8.0 Andre Iguodala-USA............ 5 9 .556 Carmelo Anthony-USA........... 8 46 5.8 Amine Rzig-TUN................ 8 15 .533 Manu Ginobili-ARG............. 8 43 5.4 Kevin Durant-USA.............