MoneyLaw The Art of Winning an Unfair Academic Game Moneyball and baseball’s sabermetric revolution –Asymmetries and biases in evaluating talent –Prophets.

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MoneyLaw The Art of Winning an Unfair Academic Game Moneyball and baseball’s 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

From Moneyball to MoneyLaw Another way of bridging athletics and academics

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

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 A’s deep –Evaluates college players the right way –Arbitrages other GMs’ biases

Sources of asymmetry and bias in the evaluation of talent in baseball  Talent and money are unbalanced. So is information, along three dimensions: 1.Heuristic bias: shortcuts that backfire E.g., favoring “skinny” over “fat” talent “CK genes”: Available, salient, vivid data 2.Social bias: herd instincts can kill 3.Statistical bias: bad stats can mislead E.g., batting average versus OPS

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

MoneyLaw Applying baseball’s 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 A’s and its Dean Beanes

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 baseball’s scouts (but not Liz Phair), we overlook “potential with no credentials”

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

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