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<p>Selecting capable counsel can shape the outcome of litigation, yet evaluating law firm performance remains challenging. Widely used rankings prioritize prestige, size and revenue over empirical litigation outcomes, offering little practical guidance. Here, to address this gap, we build on the Bradley–Terry model and introduce a new ranking framework that treats each lawsuit as a competitive game between plaintiff and defendant law firms. Leveraging a newly constructed dataset of 60,540 US civil lawsuits involving 54,541 law firms, our findings show that existing reputation-based rankings correlate poorly with actual litigation success, while our outcome-based ranking substantially improves predictive accuracy. These findings establish a foundation for more transparent, data-driven assessments of legal performance.</p>

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Data-driven law firm rankings to reduce information asymmetry in legal disputes

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月31日

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  • Alexandre Mojon,
  • Robert Mahari,
  • Sandro Claudio Lera

摘要

Selecting capable counsel can shape the outcome of litigation, yet evaluating law firm performance remains challenging. Widely used rankings prioritize prestige, size and revenue over empirical litigation outcomes, offering little practical guidance. Here, to address this gap, we build on the Bradley–Terry model and introduce a new ranking framework that treats each lawsuit as a competitive game between plaintiff and defendant law firms. Leveraging a newly constructed dataset of 60,540 US civil lawsuits involving 54,541 law firms, our findings show that existing reputation-based rankings correlate poorly with actual litigation success, while our outcome-based ranking substantially improves predictive accuracy. These findings establish a foundation for more transparent, data-driven assessments of legal performance.