Many tangible and intangible factors are considered when making a hiring decision in the National Football League (NFL). One difficult decision that executives must make is whom they will select in the NFL Draft or which NFL Free Agent they will sign in the offseason. Mathematical models can be developed to aid humans in their decision-making process because they are able to find non-obvious relationships within numeric data.

HEART, or Heuristic Evaluation of Artificially Replaced Teammates, is a mathematical model that utilizes machine learning and statistical-based methodologies to aid managers with their hiring decisions. HEART is not intended to be a ‘decision tool,’ or a tool that explicitly states who a team should hire. A ‘decision tool’ would need to encompass not only the tangible information available to hiring managers but also intangible aspects that are difficult or impossible for mathematical model to capture accurately. HEART is a ‘decision support tool’ that provides additional information for hiring managers to use in conjunction with other available resources.

The goal of HEART is to determine an Expected and Theoretical Contribution Value for a potential hiring candidate, which represents a player’s ability to increase or decrease the estimated number of games won by a particular team in an upcoming season. This value is significant because it represents a player’s level of compatibility with potential teammates and considers the effect that aging has on players’ physiological ability to play football. HEART is also designed to allow direct comparisons of players from any playing position as well as players from either college or professional leagues.

From a quantitative standpoint, the results of the HEART methodology were statistically validated using both parametric and nonparametric testing procedures. This validation procedure analyzed the results collected from a convenient sample of experts who participated in a survey instrument. The validation results show that the HEART methodology provided at least ‘Useful’ results, and at times ‘Very Useful’ results, using a five-point Likert scale for a case study involving the 2007 NFL Draft Class and Free Agent Players.