Cleveland Browns: Analytics in Football

By: Kyle Schroeder

Browns Organizational Structure

http://www.dawgsbynature.com/2016/1/4/10706930/illustrating-the-browns-new-organizational-structure

Browns Organizational Structure

• Their structure differs from the norm in the NFL.

• Personnel (usually a GM) is above the Head Coach in pecking order in NFL Franchises

• In the Browns case they don’t have a chain of command but a group of differing minds working together and sharing responsibility

• Exec. VP of Football Ops. Sashi Brown has final say over the roster and personnel moves

Change of the Norm

• With the Browns massive struggles, they have gone away from the traditional approach

• This is the reason for their change to analytics

• This is a monumental change for the NFL organizations.

Analytics • Defined as the field of data analysis, often involves

studying past historical data to research potential trends, to analyze the effects of certain decisions or events, or to evaluate the performance of a given tool or scenario. (http://www.businessdictionary.com/definition/analytics.html)

Analytics

• The use of analytics in sports involves using historical data and statistics to build and run a team.

• Has become very prevalent as of late in sports

• Has been restricted to MLB & NBA, due to these sports being very highly based off of percentages.

Analytics Case Study: Oakland Athletics (MLB)

• GM Billy Beane (1998-present)

• “Moneyball” technique was based on using saber-metrics to pick-up value players, Beane valued high On Base % players

• Valued players who have had past success and play percentages but could come on small deals to fit into the A’s small payroll.

Analytics Case Study: Houston Rockets (NBA)

• GM Daryl Morey (2007-present)

• Believes in NBA you must have at least one superstar player.

• He believes Stockpiling assets (young players, draft picks, expiring contracts for cap relief) allows you to land that Star.

• Preaches and hires to belief that 3-point shots and shots in the paint are the most beneficial by % and provide the most value to the team. Mid-range 2’s are not and are not highly taken by Rockets.

Analytics Case Study: Philadelphia 76ers (NBA)

• GM Sam Hinkie (2013-present) previously w/ Daryl Morey in Houston so adapts his schemes.

• Difference is the 76ers have not been able to find their star player.

• They are Drafting in hopes to continue to stockpile assets. Tanking for the future and not trying to win now to play the “long-game”

What will it Look like in Football?

• It’s a hard judge, this group in Cleveland has not had much to do yet.

• Due to Football being more of pure production as opposed to percentages, it is hard to see what types of players people of the Analytics mind set are looking for.

Paul DePodesta • He took over as the Chief Strategy Officer of the Browns this offseason.

• Was Assistant GM, of Billy Beane with the “Moneyball” Oakland Athletics

• "I was standing right in front of them in line and I could hear them in back of me and they were talking trash about me and the Cleveland Browns,”-Paul DePodesta from the NFL Combine

• Considered “Baseball-guy” going to football to try his approach to analytics in a new sport.

Browns Offseason So Far?• Notable Departures: C Alex Mack (Free Agency), T

Mitchell Schwartz (Free Agency), FS Tashaun Gipson (Free Agency), QB Johnny Manziel (released), WR Travis Benjamin (Free Agency), ILB Karlos Dansby (released)

• Notable Additions: QB Robert Griffin III, ILB Demario Davis, S Rahim Moore, OL Alvin Bailey

Browns Additions• Robert Griffin III-26 Years Old (2-years $15M, up to $22M

based on performance)

• Demario Davis-27 years old (2-years $8M)

• Rahim Moore-26 years old (1-year $1.85M)

• Alvin Bailey-24 years old (3-years $6M)

Observations• It appears that the Browns are combining some of the elements used in

NBA and MLB analytics.

• As seen by their signings they are adding players who are in the “prime” of their careers. They have had some past success in their careers. (This seems to come from the “Moneyball" approach to analytics.

• Also in letting their own players go they will be eligible to receive compensatory draft picks, which for the first time next season are able to be traded.

• This seems to be a stockpiling of assets, which falls close to the NBA model of analytics, where you gather them in order to make big moves.

Conclusion

• In conclusion, Analytics is an upcoming way of looking at sports

• More and more teams continue to adopt this ideology in sports, the Cleveland Browns being the first to do so.

Questions• How does Analytics transfer to Football?

• Will this go well for the Cleveland Browns?

• Will this be a trend or a “one-and-done”?

• WHEN WILL THE CLEVELAND BROWNS WIN??? No Matter the approach!