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How We Used Monte Carlo Simulation to Solve the Best Ball League Puzzle
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Monte Carlo Strategies to Win 2016 MFL10s – Part I
AJ Bessette and Greg Meade
July 12, 2016
Editor’s note: This is one of two Monte Carlo simulation articles aimed at solving the best-ball puzzle, each using different assumptions. We believe doing so gives a good idea of the range of possible outcomes. For the other article by Nick Giffen (@RotoDoc), click here…. Membership Required You must be a member to access this content.View Membership LevelsAlready a member? Log in here...
Using Monte Carlo Simulation to Win Your Best Ball League: Player Selection
AJ Bessette and Greg Meade
August 28, 2014
… Membership Required You must be a member to access this content.View Membership LevelsAlready a member? Log in here...
Monte Carlo Strategies to Win 2016 MFL10s – Part I
AJ Bessette and Greg Meade
July 12, 2016
Editor’s note: This is one of two Monte Carlo simulation articles aimed at solving the best-ball puzzle, each using different assumptions. We believe doing so gives a good idea of the range of possible outcomes. For the other article by Nick Giffen (@RotoDoc), click here…. Membership Required You must be a member to access this content.View Membership LevelsAlready a member? Log in here...
Using Monte Carlo Simulation to Win Your Best Ball League: Player Selection
AJ Bessette and Greg Meade
August 28, 2014
… Membership Required You must be a member to access this content.View Membership LevelsAlready a member? Log in here...
Analysis
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