Construct Validity of Accelerometry-Derived Force to Quantify Basketball Movement Patterns

Abstract

This study assessed the construct validity of accelerometry-derived net force to quantify the external demands of basketball movements. Twenty-eight basketballers completed the Yo-Yo intermittent recovery test (Yo-Yo-IR1) and basketball exercise simulation test (BEST). Intensity was quantified using accelerometry-derived average net force (AvF) and PlayerLoad per minute (PL/min). Within-player correlations were determined between intensity and running speed during Yo-Yo-IR1. Measured AvF was determined for movements during the BEST and predicted AvF was calculated using movement speed and correlations from Yo-Yo-IR1. Relationships between AvF and running speed during Yo-Yo-IR1 were nearly perfect (r=0.95, 95% CI: 0.94-0.96; p<0.001) and stronger than correlations between running speed and PL/min (r=0.80, 95% CI: 0.73-0.87; p<0.001). Differences between measured and predicted AvF were small during jogging and running (<1%), but large for basketball movements including jumping, change-of-direction and shuffling (15%-41%). As hypothesised, AvF differed by playing position (11%-16%; <0.001) and reflected the additional demand upon players with larger body mass and lower movement efficiency. Both sprint speed and AvF reduced during the course of the BEST (≤0.013). These findings confirm the construct validity of AvF to quantify the external demand of basketball movements. Accelerometry-derived net force has the potential to quantify the external demands of basketballers during training and competition.

Accelerometry-Derived Relative Exercise Intensities in Elite Women’s Basketball

“…For all data collection, players wore a 100-Hz tri-axial accelerometer (Link; Actigraph, Pensacola, FL, USA) on the upper back, as described previously [20]. In addition, breath-by-breath respiratory parameters (Oxycon Mobile, Jaeger, Hoechberg, Germany) were recorded during the modified Yo-Yo-IR1.…”

“…This is because time-motion analyses typically use predetermined, arbitrary speed thresholds to categorise exercise intensity and, therefore, fail to account for differences in physical capacities between players. Furthermore, although measuring distances and speeds of movement from time-motion analyses can provide useful information about the activities that players perform during match play, this practice underestimates the external demands of basketball-specific movements (e. g., jumping, shuffling, changes of direction) [20].…”

“…Average net force (AvF Net ) is an accelerometry-derived objective marker of exercise intensity, which has confirmed construct validity to measure basketball-specific movements [20]. The intensity of each movement pattern during a basketball match simulation protocol was assessed for 28 elite basketballers from AvF Net and timemotion analysis.…”

Accelerometry-Based External Load Indicators in Sport: Too Many Options, Same Practical Outcome?

“…), with high reliability and validity [19][20][21]. Other variables have been created with the same purpose, such as vectorial sum of acceleration (a(t)) [22][23][24] used by almost all the companies, Player Load developed by the company RealTrack Systems (Player Load RT ) [25], Impulse Load created by Zephyr TM [26], New Body Load by GPS Sports [27], Player Load by the manufacturer ZXY SportTracking (Player Load RE ) [17] and Total Load by StatSports [28]. All the companies use accelerometer data from the vertical, horizontal and medio-lateral planes but the calculations made to extract the final external workload are quite different, complicating comparison among them.In this respect, two important aspects of accelerometry-based external load indicators (ABELIs) have been considered: (a) the difference among the algorithms used to calculate the ABELIs and the resulting magnitude and unit variability among them hinder their practical application by team staff and sport scientists due to the different devices used [29]; and (b) different technical aspects such as variety of sampling frequencies, chip sets, filtering methods and data-processing algorithms also influence interdevice comparison among ABELIs.…”

“…), with high reliability and validity [19][20][21]. Other variables have been created with the same purpose, such as vectorial sum of acceleration (a(t)) [22][23][24] used by almost all the companies, Player Load developed by the company RealTrack Systems (Player Load RT ) [25], Impulse Load created by Zephyr TM [26], New Body Load by GPS Sports [27], Player Load by the manufacturer ZXY SportTracking (Player Load RE ) [17] and Total Load by StatSports [28]. All the companies use accelerometer data from the vertical, horizontal and medio-lateral planes but the calculations made to extract the final external workload are quite different, complicating comparison among them.…”