9 citations · 23 across the 5 of their papers we have counts for
5 papers
Applications of Improvements to the Pythagorean Won-Loss Expectation in Optimizing Rosters
Alexander F. Almeida, Kevin Dayaratna, Steven J. Miller +1
Bill James' Pythagorean formula has for decades done an excellent job estimating a baseball team's winning percentage from very little data: if the average runs scored and allowed…
The Pythagorean Won-Loss Formula and Hockey: A Statistical Justification for Using the Classic Baseball Formula as an Evaluative Tool in Hockey
Kevin D. Dayaratna, Steven J. Miller
Originally devised for baseball, the Pythagorean Won-Loss formula estimates the percentage of games a team should have won at a particular point in a season. For decades, this form…
A Mathematical Reformulation of the Reference Price
Kevin D. Dayaratna, P. K. Kannan
Reference prices have long been studied in applied economics and business research. One of the classic formulations of the reference price is in terms of an iterative function of p…
First Order Approximations of the Pythagorean Won-Loss Formula for Predicting MLB Teams' Winning Percentages
Kevin D. Dayaratna, Steven J. Miller
We mathematically prove that an existing linear predictor of baseball teams' winning percentages (Jones and Tappin 2005) is simply just a first-order approximation to Bill James' P…
Closed-Form Bayesian Inferences for the Logit Model via Polynomial Expansions
Steven J. Miller, Eric T. Bradlow, Kevin Dayaratna
Articles in Marketing and choice literatures have demonstrated the need for incorporating person-level heterogeneity into behavioral models (e.g., logit models for multiple binary…