Individual and team performance and behavioral adaptation in competitive adversarial games: an application to elite biathlon

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Di Pietrantonio, Josef, Michael
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Decision sciences and engineering systems
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This dissertation develops and explores prospects for investigating human performance and adaptive behavior in competitive, individual- and team-based settings. It is motivated by recent work on theoretical underpinnings of performance and adaptation in teamwork, but also by a two-fold methodological challenge: how to instrument the environments in which teamwork takes place and how to leverage the resulting data to produce detailed descriptions and insightful analysis of task performance. The research presented here is organized in relation to a modified version of the Input-Mediator-Output (IMO) of Mathieu and colleagues, in which Inputs are the performers and task attributes, Mediators are the processes they engage in while on task, Outputs are the results of these processes by the performers in the task context, and Moderators are the situational factors of the scenario, which ultimately provide the feedback to support the development of teams and their members. Study 1 addresses prospects for capturing various IMO elements within team-based electronic gaming environments. Specifically, Study 1 yields recommendations for using open-source games to capture data on the Inputs of Team Composition and Working History, the Mediators of team Workflow and Communication, and the team Output of Performance. The approach augments the standard IMO framework by assessing the capacity of these games to capture data on different types of Tasks (e.g., Planing vs. Contests/Battles) within Environments that may be either Stable or Turbulent. Many of these themes are addressed in the real-world environment of elite biathlon in Studies 2 and 3. Elite biathlon––a sport that combines cross-country skiing and precision target shooting––is well suited to the study of human adaptation in competitive settings. Equally importantly, it can be used to address many aspects of the framework described in Study 1. In terms of the IMO Inputs, athletes can compete as individuals or as members of a variety of configurations of sub-teams within a national team (Composition), thus accruing experience working with each other (Working History). In terms of IMO Mediators, limited information on the state of the race is available on-course through a competitor's experience and team staff---though clearly this information is neither complete nor necessarily current. In terms of IMO Outputs, there are clearly defined and meaningful intermediate and final measures of performance. Finally, Task type can be defined as "Contest/Battle" while certain aspects of the Environment (such as weather) may be used to determine the extent to which there is stability or turbulence around the athletes. It should be noted that, due to longstanding interest within biathlon in advanced instrumentation, data are available to support analysis of individual- and team-level development at an appropriate scale over fairly long time horizons. Study 2 develops and illustrates the use of theoretically grounded measures of Mediator and Output of task performance at the process (i.e., the product of task actions) and outcome (i.e., intermediate and final standings) levels for the mixed relay discipline of biathlon. This exploratory study examines possible relationships and trade-offs among three measures of process performance: effectiveness, efficiency, and equality. Considering the underlying uncertainty associated with behavioral responses to changes in a system, entropy is used here to characterize behavioral change and adaptation over time. Accordingly, correlations across values of relative intermediate outcome performance variables are examined. The results suggest that process efficiency and equality, rather than effectiveness, introduce more variability in outcome effectiveness. Process effectiveness was highly correlated with and drove outcome effectiveness. The results suggest that future work should explore aspects of a competitive system that are related to the underlying contributors to efficiency and equality in order to understand adaptive behavior. Study 3 further explores Output performance by examining performance outcomes (i.e., intermediate and final standings of individual races) as a function of Input variables (individual, team, and task) and one salient Moderator factor of the environment (wind speed). The cyclic aspects of the IMO framework are considered by the time-series of competitor performance over the course of a race, and by modeling data over five consecutive seasons of elite biathlon. Building on the methodological perspective of Study 2, this study considers the extent to which behavior serves to reduce uncertainty. Adaptation here is framed as a deviation from baseline behavior and expressed in terms of entropy. The study results suggest that deviations from established baseline behavior differ by type of competition (and therefore task type), and that some competitors' substantial deviation across task types is suggestive of adaptive behavior. The overall contributions from this work include 1) the connection of the theories of team behavior to the domain of adversarial competitions, thus creating new empirical results; 2) an underlying theoretical framework to support empirical studies in performance and behavioral adaptation in individual and team competitive adversarial games; 3) suggestions of alternative research paradigms (open-source electronic game environments and complex secondary sporting data) for studying human performance; and 4) application of advanced analytic methods to complex secondary data in the target domain of biathlon. This work has also revealed various challenges and limitations associated with the marshaling of complex secondary data in the development of new theory, the exploration of team-based phenomena in real-world settings over time, and the need for further work in identifying opportunities for measurement of target phenomena.
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Rensselaer Polytechnic Institute, Troy, NY
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