Morey\u2019s overarching thesis is that traditional methods of measuring performance were incomplete and misleading, consequently he has sought to use digital technology to collect more data AND <\/strong>to better understand what that data means.<\/em> Morey seeks to use data to better enable the decisions that \u201cbasketball guys\u201d make, providing new frameworks for evaluating performance.<\/p>\n How did we get here?<\/strong><\/p>\n Traditional basketball stats were generic and often misleading. For example, players who compiled lots of points and rebounds were heralded without deeper thought as to how much those gaudy statistics translated to overall effectiveness. As new digital technologies emerged and exponential computing power became democratized, people like Morey and Billy Beane<\/a> started paying attention. With Morey as GM, the Houston Rockets were the first team to install SportVU, an Israeli missile-tracking technology that uses tiny webcams installed in stadium rafters to record the x\/y coordinates of each player thousands of times per game. Morey and his staff aggregate the immense data from SportVU into all types of statistics: how far a player runs, how efficiently they shoot from each spot on the court, how many times they dribble, etc. Every team in the NBA now uses SportVU, but few are as adept at making sense of it as Morey. The Rockets also use wearable devices such as embedded accelerometers<\/a> to track player movement.<\/p>\n <\/p>\n A New Basketball Business Model = <\/strong>new <\/strong>methods of evaluating player and team performance<\/strong><\/p>\n The Rockets use\u00a0the data as a lens through which to look at how a player performs. For example:<\/p>\n Player A averages 20 points and 10 rebounds per game, with a 50% shooting efficiency. While player B averages 16 points and 7 rebounds and makes 45% of his shots. Player A is significantly bigger and ostensibly a better athlete.<\/p>\n Which player would you take? \u00a0Player A, right?<\/p>\n Advanced metrics might show you that player B is a more impactful contributor. What if player B\u2019s true shooting percentage is higher than player A\u2019s, his defensive efficiency superior, his rebound rate better?<\/p>\n Two 性视界 PhD\u2019s have also recently made their contribution to basketball analytics<\/a>. Alexander Franks and Andrew Miller used player-tracking data and regression models to create a new metric for defensive evaluation.<\/p>\n For Morey and the Rockets, evaluation isn\u2019t about raw totals, it\u2019s about weighing the impact of each action a player takes.<\/em><\/p>\n New Operating Model: How Morey and others used digital tools to reimagine how teams and players should play<\/strong><\/p>\n As new metrics pour in, managers, coaches and players have reimagined the way the game should be played on court. The 2015 NBA champion Golden State Warriors have embraced a \u201cpace and space\u201d strategy, spreading their players out and taking many shots in high efficiency areas (particularly corner 3-point shots). The Warriors\u2019 Stephen Curry is an example of a player who has taken to heart information on the efficiency of a 3-pointer over a 2-pointer (albeit maybe not intentionally). As the 2016 NBA Most Valuable Player, Curry took more threes in a single season than any NBA team did from 1980-1994.<\/p>\n <\/p>\n Morey has taken a more extreme approach. Using deep analysis to identify that the three most efficient shots were three-pointers (specifically from the corner), layups (near the basket), and free throws, Morey has steered his team to only take shots from those areas, and prohibiting \u201cmid-range\u201d shots (which have the lowest efficiency). Furthermore, Morey has built the team around the unique talents of James Harden, who\u2019s natural style fits Morey\u2019s strategy perfectly.<\/p>\n <\/p>\n <\/p>\n \u00a0 How has this worked out?<\/strong><\/p>\n Overall, Morey\u2019s teams have been competitive but not great. That said, almost all NBA teams now employ similar strategies to the Rockets (including the 2015 Champion Warriors).<\/p>\n Critics of Morey and the \u201cnerds\u201d point to the formulaic rigidity of analytics as improper for running a basketball team. Morey has been criticized for ignoring things like team chemistry when assembling a roster. He famously used a high draft pick on a player with anxiety disorder because the data said he was one of the best players in the draft (that player is now out of the NBA). Furthermore, in the 2016 NBA Finals the Cleveland Cavaliers beat the Golden State Warriors, despite the fact that the Warriors were superior in every advanced metric.<\/p>\n These results are not a referendum on the use of analytics, but just further proof that a great organization will not rely too heavily on either the art or the science. Statistical models are built on probabilities of voluminous events, and thus give great insight into what the best options for a basketball team (or business) are. That said, statistics cannot yet account for the vicissitudes of human performance or the intangibles of the game.<\/p>\n Daryl Morey does not think that he can build and coach basketball teams based purely on what the data tells him, but he does believe that traditional basketball minds have been looking at the game incorrectly.<\/p>\n Morey is doing what any good manager should do when their business meets digitization \u2013 he is asking questions. For Morey, it is not about the data, it\u2019s about what the data means.<\/strong> He isn\u2019t replacing the \u201cbasketball guys,\u201d he is just making them smarter.<\/p>\n <\/p>\n <\/p>\n <\/p>\n Endnotes<\/p>\n <\/p>\n Information with real power comes in a variety of forms: both in the stereotypical form of databases and spreadsheets and analysts and predictive models, but also in the form of expertise and experience acquired only via a lifetime of playing and coaching the game. –\tDaryl Morey, Grantland, 2011.<\/p>\n","protected":false},"author":1967,"featured_media":20642,"comment_status":"open","ping_status":"closed","template":"","categories":[],"class_list":["post-20616","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/digitization-challenge-2016\/","yoast_head":"\n![\"curry\"](\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/Curry-300x173.png\")
<\/a><\/p>\n![\"picture1\"](\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/Picture1-21-300x222.jpg\")
<\/a><\/p>\n![\"hardenchart1415_1152\"](\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2016\/11\/hardenchart1415_1152-300x222.jpg\")
<\/a><\/strong><\/p>\n\n
\nThe best organizations bring that all together.<\/p>\n