The swing performance Index
Developing a single-score index of golf swing rotational biomechanics quantified with 3D kinematics
Bibliographic Data
| ID | 13129803 |
|---|---|
| Authors | Joanne Zhou (0000-0002-6226-4701, Stanford University), Alexander Richards (0000-0002-7444-8559, Stanford University), Kornél Schadl (Lucile Packard Children's Hospital), Amy L Ladd (0000-0003-0948-1034, Lucile Packard Children's Hospital), Jessica Rose (0000-0003-0094-5525, Lucile Packard Children's Hospital, corresponding author) |
| Year | 2022 |
| Volume | 4 |
| Pages | 986281-986281 |
| Publication date | 2022-12-23 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Sports and Active Living (JOURNAL) |
| Journal identifiers | ISSN: 2624-9367 • E-ISSN: 2624-9367 |
| Publisher | Frontiers Media (PUBLISHER • CH) |
| DOI | 10.3389/fspor.2022.986281 |
| PMID | 36619352 |
| OpenAlex | W4312172234 |
| Language | EN |
| Citations received | 1 |
| References cited | 30 |
Introduction Golf swing generates power through coordinated rotations of the pelvis and upper torso, which are highly consistent among professionals. Currently, golf performance is graded on handicap, length-of-shot, and clubhead-speed-at-impact. No performance indices are grading the technique of pelvic and torso rotations. As an initial step toward developing a performance index, we collected kinematic metrics of swing rotational biomechanics and hypothesized that a set of these metrics could differentiate between amateur and pro players. The aim of this study was to develop a single-score index of rotational biomechanics based on metrics that are consistent among pros and could be derived in the future using inertial measurement units (IMU). Methods Golf swing rotational biomechanics was analyzed using 3D kinematics on eleven professional (age 31.0 ± 5.9 years) and five amateur (age 28.4 ± 6.9 years) golfers. Nine kinematic metrics known to be consistent among professionals and could be obtained using IMUs were selected as candidate variables. Oversampling was used to account for dataset imbalances. All combinations, up to three metrics, were tested for suitability for factor analysis using Kaiser-Meyer-Olkin tests. Principal component analysis was performed, and the logarithm of Euclidean distance of principal components between golf swings and the average pro vector was used to classify pro vs. amateur golf swings employing logistic regression and leave-one-out cross-validation. The area under the receiver operating characteristic curve was used to determine the optimal set of kinematic metrics. Results A single-score index calculated using peak pelvic rotational velocity pre-impact, pelvic rotational velocity at impact, and peak upper torso rotational velocity post-impact demonstrated strong predictive performance to differentiate pro (mean ± SD:100 ± 10) vs. amateur (mean ± SD:82 ± 4) golfers with an AUC of 0.97 and a standardized mean difference of 2.12. Discussion In this initial analysis, an index derived from peak pelvic rotational velocity pre-impact, pelvic rotational velocity at impact, and peak upper torso rotational velocity post-impact demonstrated strong predictive performance to differentiate pro from amateur golfers. Swing Performance Index was developed using a limited sample size; future research is needed to confirm results. The Swing Performance Index aims to provide quantified feedback on swing technique to improve performance, expedite training, and prevent injuries
Biomechanics · Kinematics · Physics · Simulation · Sports biomechanics · Statistics · Swing · Torso · Computer Science · Engineering · Mathematics · Medicine · Sports Analytics and Performance · Sports Dynamics and Biomechanics · Sports Performance and Training
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |