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|NBA Teams That Have Analytics Department|
The list includes the NBA teams using advanced stats by either employing basketball analytics professionals or working with statistical consultants.
Mike Zarren (Assistant General Manager & Team Counse), David Lewin (Director of Scouting), Drew Cannon (Analyst)
Milton Lee (Director of Basketball Operations), Scott Sereday (Statistical Analyst)
Jason Rosenfeld (Manager of Basketball Analytics)
Steve Weinman (Basketball Operations Assistant)
Jon Nichols (Director of Analytics) Benjamin C. Alamar (Senior Analytics Consultant and Data Engineer)
Roland Beech, (VP of Basketball Operations)
Kenneth Catanella (Director of Basketball Operations), Charles Klask (Statistics Coach)
Kirk Lacob (Assistant General Manager)
Daryl Morey (General Manager), Ed Kupfer (Consultant), Eli Witus (Basketball Operations Analyst), Monte McNair (Basketball Operations Analyst)
Spencer Anderson (Consultant)
Rudy Tomjanovich (Statistical Analyst and Consultant), Trey Tomjanovich (Software Provider)
John Hollinger (Vice President of Basketball Operations)
Bob Chaikin (Basketball Analyst)
Michael Clutterbuck (Director of Basketball Analytics)
Matt Bollero (Manager of Basketball Analytics, Personnel Video Scout)
Mike Smith (Director of Analytics and Pro Scout)
Jesse Weinstein-Gould (Basketball Information Coordinator)
Wynn Sullivan (Basketball Data Analyst)
Analytics work is now being operated by basketball operations staff. Charles Klark has worked for Magic as Scouting Information Manager for 2 years.
Sam Hinkie (GM), Aaron Barzilai (Director of Basketball Analytics)
Steve Ilardi (Analytics Consultant),Eddie Kendralla (Manager, Business Analytics), Ken Borkan (Business Analyst)
Ben Falk (Basketball Analytics Manager),
Jeff Ma (Consultant), Ryan Parker (Statistical Analyst)
Gabe Farkas (Director of Basketball Analytics)
Alex Rucker (Consultant), Keith Boyarsky (Consultant)
Bob Bellotti (Consultant), Joe Sill (Consultant),
Ryan Saunders (Assistant Coach/Statistical Analysis)
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Neural networks are one of the machine learning systems in sports. By the help of neural networks, datasets are learned by the system and hidden trends can be revealed for creating a competitive edge.
Simulations and machine learning systems means a lot for sports analytics. The ability to apply statistics and rigorous mathematical models to provide instantaneous results is quickly becoming an invaluable commodity. Systems of this type vary from simulations that model an entire upcoming seasonís worth of data to identify the best chance of winning, to simulations that identify weaknesses in motion and offer advice for correcting them.
Other than statistical predictive algorithms, neural networks can be used as sports betting and fantasy league tools in following ways;
Other machine learning techniques include;
|New England Statistics Symposium NESSIS|
NESSIS is an event in which statisticians from all over the world come together and present academical studies. NBA and other sports analytics community has been benefiting from NESSIS that many studies on statistics regarding professional sports are being introduced first time at NESSIS just like MIT Sloan Sports Analytics Conference.
The first New England Statistics Symposium was held at the University of Connecticut, which traditionally hosts the Symposium on alternate years. Now, The Department of Statistics of Harvard University hosts the New England Statistics Symposium.