Assessment of Human Expertise in First-Person Shooter Games
Ian DonovaniD, Marcia A. Saul, Kevin DeSimoneiD, Jennifer B. ListmaniD, Wayne E. MackeyiD, David J. HeegeriD
Abstract
Contrary to traditional professional sports, there are few standardized metrics in professional esports (competitive multiplayer video games) for assessing a players skill and ability. To begin to address this, we assessed the performance of professional-level players in Aim Lab, a first-person shooter training and assessment game, within two separate target-shooting tasks. These tasks differed primarily in the relative incentive for fast and imprecise shots versus slow and precise shots. Each players motor acuity was measured by characterizing the speed-accuracy trade-off in shot behavior: shot frequency and shot spatial error (distance from center of a target). We also characterized the fine-grained kinematics of players mouse movements. Our findings demonstrate that: 1) movement kinematics depended on task demands; and 2) individual differences in motor acuity were significantly correlated with both kinematics and the number of movements needed to hit a target. We demonstrate the importance of transforming from orientation in the virtual environment to centimeters on the mouse pad, as well as accounting for differences in mouse sensitivity across players, for characterizing human performance in first-person shooter games. This approach to measuring motor acuity has widespread application not only in esports assessment and training, but also in basic (motor psychophysics) and clinical (gamified rehabilitation) research.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 3
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Kinematic markers of skill in first-person shooter video games
Matthew Warburton, Carlo Campagnoli, … J. Ryan Morehead·PNAS NexusPeer-reviewed·Jul 31, 2023
- Long-term Motor Learning in the Wild with High Volume Video Game Data
Jennifer B. Listman, Jonathan S. Tsay, … David J. Heeger·Frontiers in Human NeurosciencePeer-reviewed·Dec 20, 2021
- Computer mouse weight is associated with one-week motor skill improvement in a large naturalistic video game cohort
Jennifer B. Listman, Wayne E. Mackey·bioRxiv·Oct 8, 2026
- Joint Pupillometry and Heart Rate Monitoring Identify Zone-Like High Performance in Esports
Shohei Dobashi, Shion Takahashi, … Takashi Matsui·bioRxiv·Sep 11, 2026
- Skilled strategies of release parameters for accurate free-throw shooting in the presence of motor noise
Nobuyasu Nakano, Yuki Inaba, … Shinsuke Yoshioka·bioRxiv·Oct 4, 2019
- Keeping Your Eye, Head, and Hand on the Ball: Rapidly Orchestrated Visuomotor Behavior in a Continuous Action Task
Anna Schroeger, Alexander Goettker, … Karl R. Gegenfurtner·Journal of VisionPeer-reviewed·Oct 21, 2025