Tuesday, January 1, 2013
Ronald F. Wright (pictured) and Ralph A. Peeples (Wake Forest University - School of Law and Wake Forest University - School of Law) have posted Criminal Defense Lawyer Moneyball: A Demonstration Project (Washington and Lee Law Review, Forthcoming) on SSRN. Here is the abstract:
The book and movie “Moneyball” portray the iconoclastic general manager of a baseball team. When drafting new players, this GM de-emphasized the insights of baseball scouts as on-the-scene evaluators of a player’s talents, and looked instead to statistical measures of player quality. We take this idea from baseball into the criminal courts. In this article, we argue that criminal defense organizations could meaningfully evaluate the skills of their attorneys through the use of metrics, rather than relying so heavily on the in-person observation of their work in the courtroom. Statistical performance-based rankings could support better leadership in defense attorney organizations.
Rather than simply assert that a rating system is possible, we attempt in this paper to show its feasibility. We employ data from the North Carolina courts as a demonstration project to illustrate how an office might develop a rating system for the attorneys who work there. Our attorney ratings are based on the bottom line: sentencing reductions those attorneys achieve for their clients, principally through plea negotiations. We then use our tentative quality ratings to address the question of structural causes. What makes one attorney noticeably more or less effective than the typical defense lawyer? Our most surprising discovery is that experience actually has a negative correlation with performance after the first eight years: the more time an attorney has spent in the profession, the more likely that her clients will obtain a more severe sentence. We close with some reflections on other potential users of a statistical rating system, concluding that managers of defense organizations are better situated than judges, prosecutors, or clients to make wise use of ratings data.