Evaluating Player Strategies in the Design of a Hot Hand Game

Abstract

AbstractThe user’s strategy and their approach to decisionmaking are two important concerns when designing user-centric software. While decision-making and strategy are key factors in a wide range of business systems from stock market trading to medical diagnosis, in this paper we focus on the role these factors play in a serious computer game. Players may adopt individual strategies when playing a computer game. Furthermore, different approaches to playing the game may impact on the effectiveness of the core mechanics designed into the game play. In this paper we investigate player strategy in relation to two serious games designed for studying the ‘hot hand’. The ‘hot hand’ is an interesting psychological phenomenon originally studied in sports such as basketball. The study of ‘hot hand’ promises to shed further light on cognitive decision-making tasks applicable to domains beyond sport. The ‘hot hand’ suggests that players sometimes display above average performance, get on a hot streak, or develop ‘hot hands’. Although this is a widely held belief, analysis of data in a number of sports has produced mixed findings. While this lack of evidence may indicate belief in the hot hand is a cognitive fallacy, alternate views have suggested that the player’s strategy, confidence, and risk-taking may account for the difficulty of measuring the hot hand. Unfortunately, it is difficult to objectively measure and quantify the amount of risk taking in a sporting contest. Therefore to investigate this phenomenon more closely we developed novel, tailor-made computer games that allow rigorous empirical study of ‘hot hands’. The design of such games has some specific design requirements. The gameplay needs to allow players to perform a sequence of repeated challenges, where they either fail or succeed with about equal likelihood. Importantly the design also needs to allow players to choose a strategy entailing more or less risk in response to their current performance. In this paper we compare two hot hand game designs by collecting empirical data that captures player performance in terms of success and level of difficulty (as gauged by response time). We then use a variety of analytical and visualization techniques to study player strategies in these games. This allows us to detect a key design flaw the first game and validate the design of the second game for use in further studies of the hot hand phenomenon.