Stance, barrel movement, and trigger control significantly predict individual shot performance, accounting for approximately 20% of variance¶
Claim · All claims
Evidence · 1 study (2 entries) · designr2·q2
Currency · newest study 2018 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? In a stepwise regression on the expert data set, barrel movement AUC, trigger control AUC, and firing stance (prone vs. kneeling) entered the equation and were significantly related to shot group size performance, with a multiple correlation of .452. → Goldberg 2018
q2 i? Gear setup and breathing AUC were not significant predictors and were excluded from the regression equation. → Goldberg 2018 (2)
Evidence¶
Goldberg 2018¶
Goldberg, B., Amburn, C., Ragusa, C., & Chen, D. (2018). Modeling Expert Behavior in Support of an Adaptive Psychomotor Training Environment: a Marksmanship Use Case. Int J Artif Intell Educ 28:194–224. https://doi.org/10.1007/s40593-017-0155-y
q2 · i? · design · r2
Stepwise regression (SPSS Statistics 19) on the full expert shot data set, with individual shot performance as the dependent variable. The authors report a multiple correlation coefficient of .452, indicating approximately 20% of variance in individual shot score accounted for.
"At step 3 of the analysis the behaviors of barrel movement and trigger, as represented by the AUC value, and the stance from which an expert shot from (prone vs. kneeling) entered into the regression equation and were found to be significantly related to shot group size performance."
Goldberg 2018 (2)¶
Goldberg, B., Amburn, C., Ragusa, C., & Chen, D. (2018). Modeling Expert Behavior in Support of an Adaptive Psychomotor Training Environment: a Marksmanship Use Case. Int J Artif Intell Educ 28:194–224. https://doi.org/10.1007/s40593-017-0155-y
q2 · i? · design · r2
Same stepwise regression: gear setup and breathing control were exclusion variables, with t(1555) = −1.326, p > .1 for gear setup and t(1555) = −1.444, p > .1 for breathing control; no standardized effect size is printed.
"The gear setup and breathing AUC factors were not found to significantly impact performance and were therefore not entered into the regression equation; they were instead listed as exclusion variables (gear setup, t(1555) = −1.326, p > .1; breathing control, t( 1 5 5 5 )= −1.444, p >. 1 )."
Discussion¶
Related Claims¶
- Expert trigger-control behavior diverges from Army training doctrine, showing slack removal with an extended pause at the breakpoint — related
- Cross-fold validation supports generalized expert models of marksmanship behavior across firing conditions and behavioral measures — related
- GIFT serves as a testbed for developing and validating expert models for psychomotor tasks such as rifle marksmanship — a broader claim this one bears on
- Kneeling stance produces worse shot-group performance on average than prone stance among expert marksmen — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
stance-barrel-trigger-predict-shot-performance |
title |
Stance, barrel movement, and trigger control significantly predict individual shot performance, accounting for approximately 20% of variance |
description |
Stance, barrel movement, and trigger control significantly predict individual shot performance, accounting for approximately 20% of variance |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2018 |
generated |
by process:wiki-ingest on 2026-10-27 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — goldberg-2018, goldberg-2018-2 |
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