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Vincent Freeh, NC State University, presents at the 2016 HPCC Systems Engineering Summit Community Day.
Pro Football is the most popular sport in America and has been for 30 years. Because the action in football can be discretized into a series of plays, it is highly amenable to analysis. The basic level of analytics is "aggregation." It produces statistics such as total yards rushing that can be broken out by player, game, team, etc. This includes more elaborate formulation such as quarterback rating (which is a scalar produced from four stats) or third down conversion rate. Taking a cue from baseball's sabermetrics revolution, novel "statistical" analytics are appearing. For example, one can determine the probability of victory for a given game situation using models developed from outcomes from previous games. Football Outsider's DVOA (defense-adjusted value over average) is a preeminent example of creatively using statistical tools and techniques to concoct a statistic that normalizes differences in order to compare individual performance on a level field. The next level in this analytics evolution is "graphical" analytics, which enable discovering and comparing patterns in the data.
In collaboration with NC State University and LexisNexis Risk Solutions, we have developed an analytics solution on HPCC Systems leveraging ECL and KEL that looks at NFL data on the three aforementioned levels: aggregation, statistical, and graphical. During this session we will present a variety of interesting football analytics including our novel, graphical "play-call similarity" analytics that compares teams play calling, normalized to the game situation.
Vincent Freeh
Vincent W. Freeh is an associate professor of computer science at North Carolina State University. He received his Ph.D. in 1996 from the University of Arizona. His research focus is high-performance system software, with emphasis on filesystems, parallel and distributed systems, power-aware computing, and storage systems. Prof Freeh teaches courses in the above research areas as well as in compilers. He has more than 55 referred publications in numerous computer science conferences and scientific journals. He received an NSF CAREER Award and several IBM Faculty Development Awards. He was a captain in the US Army Corps of Engineers before entering graduate school for his MS.
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Game-Changing NFL Analytics with KEL
Vincent Freeh, NC State University, presents at the 2016 HPCC Systems Engineering Summit Community Day.
Pro Football is the most popular sport in America and has been for 30 years. Because the action in football can be discretized into a series of plays, it is highly amenable to analysis. The basic level of analytics is "aggregation." It produces statistics such as total yards rushing that can be broken out by player, game, team, etc. This includes more elaborate formulation such as quarterback rating (which is a scalar produced from four stats) or third down conversion rate. Taking a cue from baseball's sabermetrics revolution, novel "statistical" analytics are appearing. For example, one can determine the probability of victory for a given game situation using models developed from outcomes from previous games. Football Outsider's DVOA (defense-adjusted value over average) is a preeminent example of creatively using statistical tools and techniques to concoct a statistic that normalizes differences in order to compare individual performance on a level field. The next level in this analytics evolution is "graphical" analytics, which enable discovering and comparing patterns in the data.
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Leydy henao
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