共 2 条
Tracking the Reliability of Force Plate-Derived Countermovement Jump Metrics Over Time in Female Basketball Athletes: A Comparison of Principal Component Analysis vs. Conventional Methods
被引:4
|作者:
Keogh, Joshua A. J.
[1
]
Bishop, Chris
[2
]
Ruder, Matthew C.
[1
]
Kobsar, Dylan
[1
]
机构:
[1] McMaster Univ, Dept Kinesiol, Biomech Lab, Hamilton, ON L8S 4L8, Canada
[2] Middlesex Univ, London Sports Inst, London NW4 4BT, England
关键词:
Athlete monitoring;
Injury prevention;
Athlete performance;
Asymmetry;
Between-limb differences;
Longitudinal;
LIMB ASYMMETRIES;
TRAINING LOADS;
PERFORMANCE;
STRENGTH;
PLAYERS;
SPRINT;
TESTS;
KNEE;
D O I:
10.1007/s42978-023-00239-8
中图分类号:
G8 [体育];
学科分类号:
04 ;
0403 ;
摘要:
BackgroundEstablishing the reliability of countermovement jump (CMJ) metrics over multiple weeks can be important in understanding and tracking changes in jump performance over time. However, a limited number of key performance indicators are generally retained for ease of interpretation. Fortunately, CMJ metrics are often highly correlated, which offers the potential to summarize key jump aspects using principal component analysis (PCA).PurposeThe objective of this study was to assess and compare the week-to-week (i.e., week 1 vs. week 2, week 2 vs. week 3, etc.) vs. preseason (i.e., nth-week vs. average of the 7-weeks) reliability of CMJ metrics, relative to principal components (PCs).MethodsThirteen varsity female basketball athletes completed 17 weeks of CMJ testing (i.e., offseason (4 weeks), preseason (7 weeks), and regular season (6 weeks)). The PCA was developed from all data collected, but only results of the preseason PC scores were examined for reliability purposes.ResultsIt was found that both methods displayed comparable reliability, such that 11/18 CMJ metrics and 3/6 PCs displayed excellent weekly reliability (ICC >= 0.9), while 17/18 of the CMJ metrics and 5/6 of the PCS displayed excellent reliability when assessed longitudinally. PCs 1-4 explained 83% of the variance in the data relating to force measures, braking metrics, jump power measures, and between-limb differences, respectively.ConclusionThese findings support the use of PCA in routine longitudinal athletic monitoring, as this technique retains valuable performance information and summarizes distinct aspects of the jump, providing a more holistic assessment of performance and indication of injury susceptibility.
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