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Report 755
    Assessment of Rifle Marksmanship Skill Using Sensor-Based Measures
    Sam O. Nagashima, Gregory K. W. K. Chung, Paul D. Espinosa, Chris Berka, Eva L. Baker

    The goal of this report was to test the use of sensor-based skill measures in evaluating performance differences in rifle marksmanship. Ten shots were collected from 30 novices and 9 experts. Three measures for breath control and one for trigger control were used to predict skill classification. The data were fitted with a logistic regression model using holdout validation to assess the quality of model classifications. Individually, all four measures were significant; when considered together, only three measures were significant predictors for level of expertise (p < .05). Overall percent correct in shot classification for the testing data was 90.0%, with a sensitivity of 67.5%, and 96.0% specificity.



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