MoneyLaw The Art of Winning an Unfair Academic Game

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MoneyLawThe Art of Winning an Unfair Academic
Game

• Moneyball and baseballs sabermetric revolution
• Asymmetries and biases in evaluating talent
• Prophets and profits, pennants and playoffs
• MoneyLaw The art of winning an unfair academic
  game

Jim Chen Dean and Professor of Law University of
Louisville Brandeis School of Law
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From Moneyball to MoneyLawAnother way of
bridging athletics and academics
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The sabermetric revolution

• Baseball, like life, is unfair
• Differences in talent
• Differences in money
• Conventional wisdom
• E.g., speed kills
• Scouts honor
• Batting average, RBI, ERA, fielding percentage,
  saves
• Real numbers offer real answers to real problems

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Moneyball The story of Billy Beane

• Billy Beane the bonus baby
• Won the 270-foot dash and scouts love
• Drafted fifth overall by the Mets
• Billy Beane the bust
• 80 strikeouts, 66 hits, and a .546 OPS
• Quit playing and started scouting
• Billy Beane the general manager
• Consistently takes the As deep
• Evaluates college players the right way
• Arbitrages other GMs biases

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Sources of asymmetry and bias in the evaluation
of talent in baseball

• Talent and money are unbalanced. So is
  information, along three dimensions
• Heuristic bias shortcuts that backfire
• E.g., favoring skinny over fat talent
• CK genes Available, salient, vivid data
• Social bias herd instincts can kill
• Statistical bias bad stats can mislead
• E.g., batting average versus OPS

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Example Defense-Independent Pitching Statistics
(DIPS)

• Conventional pitching stats are misleading
• Vörös McCracken balls put into play follow no
  pitcher-specific pattern
• Defense, ballpark effects, weather, and random
  factors matter more
• DIPS K, BB, HR

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MoneyLawApplying baseballs lessons to academia

• Talent is hungry, but money is unevenly
  distributed
• We tout access, diversity, social justice,
  community engagement values often overlooked
  elsewhere
• The UofL and schools like it must do more with
  less
• Academia needs its Oakland As and its Dean Beanes

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Performance 1, Pedigree 0

• Perhaps the deepest source of bias in academia is
  reputation
• Unexamined reputation wins because it is . . .
• Succinct
• Socially safe
• Repeated till it seems true
• Like baseballs scouts (but not Liz Phair), we
  overlook potential with no credentials

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RIPS Reputation Independent Performance
Statistics

• No measure of academic performance is valid if it
  relies on reputation
• A bibliometric manifesto
• Citation counts
• Impact factors
• Arxiv, SSRN downloads
• RSCA percentage
• Use RIPS to hire talent
• Use RIPS to rate schools

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Other ways to apply MoneyLaw

• Post-graduation results
• Job rates starting salaries
• Bar passage
• Access and diversity
• Financial aid
• Philanthropy
• Percentage participation
• Dollars per graduate
• Young alumni