Peter Huynh, Samuel Guadagnino, Jessica Zendler, Cristine Agresta
{"title":"Physical demands of collegiate basketball practice: a preliminary report on novel methods and metrics.","authors":"Peter Huynh, Samuel Guadagnino, Jessica Zendler, Cristine Agresta","doi":"10.3389/fspor.2024.1324650","DOIUrl":null,"url":null,"abstract":"<p><p>Knowing the specific physical demands of basketball players can provide useful information for clinical decision making when rehabilitating athletes following injury. The purpose of this observational study was to describe the physical demands of basketball play at the Division I collegiate level using video-based time-motion analysis and introduce a time-efficient alternative method of quantifying demands. Eleven NCAA Division I basketball players (6M, 5F; 4 guards, 4 centers, 3 forwards) participated in the study. Video footage was collected from four practices (2 men's, 2 women's) and used to quantify the types and frequencies of player movements based on definitions from seminal work. A second and simpler method was also used to classify movement. A two-way ANOVA was used to assess significant differences in movement by team (men's, women's) and position (guard, forward, center). There were significant differences in counts of stand/walk (<i>p</i> < 0.001), jog (<i>p</i> = 0.012), run (<i>p</i> = 0.001), stride/sprint (<i>p</i> = 0.04), and medium-intensity shuffling (<i>p</i> < 0.001) per minute and proportion of practice time spent in bodyweight (<i>p</i> < 0.001) or above-bodyweight (<i>p</i> < 0.001) loading between teams. There were significant differences for jog (<i>p</i> = 0.001) and transition (<i>p</i> = 0.07) rates across positions. Position and team are important considerations for rehabilitation and return-to-sport clearance. Quantification of these demands can be reliably acquired through video analysis using a simplified method (estimated foot load) or using traditional methods of movement classification and counts, particularly when applying descriptors that better capture the current style of play.</p>","PeriodicalId":12716,"journal":{"name":"Frontiers in Sports and Active Living","volume":null,"pages":null},"PeriodicalIF":2.3000,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11472002/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Sports and Active Living","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fspor.2024.1324650","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"SPORT SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Knowing the specific physical demands of basketball players can provide useful information for clinical decision making when rehabilitating athletes following injury. The purpose of this observational study was to describe the physical demands of basketball play at the Division I collegiate level using video-based time-motion analysis and introduce a time-efficient alternative method of quantifying demands. Eleven NCAA Division I basketball players (6M, 5F; 4 guards, 4 centers, 3 forwards) participated in the study. Video footage was collected from four practices (2 men's, 2 women's) and used to quantify the types and frequencies of player movements based on definitions from seminal work. A second and simpler method was also used to classify movement. A two-way ANOVA was used to assess significant differences in movement by team (men's, women's) and position (guard, forward, center). There were significant differences in counts of stand/walk (p < 0.001), jog (p = 0.012), run (p = 0.001), stride/sprint (p = 0.04), and medium-intensity shuffling (p < 0.001) per minute and proportion of practice time spent in bodyweight (p < 0.001) or above-bodyweight (p < 0.001) loading between teams. There were significant differences for jog (p = 0.001) and transition (p = 0.07) rates across positions. Position and team are important considerations for rehabilitation and return-to-sport clearance. Quantification of these demands can be reliably acquired through video analysis using a simplified method (estimated foot load) or using traditional methods of movement classification and counts, particularly when applying descriptors that better capture the current style of play.