Stacking in College Basketball: A Neglected Analysis

1987 ◽  
Vol 4 (4) ◽  
pp. 403-409 ◽  
Author(s):  
Wilbert M. Leonard
Keyword(s):  
Student Athletes ◽  
Control Variables ◽  
Basketball Players ◽  
College Basketball ◽  
Center Position ◽  
Bivariate Outcomes ◽  
The Relationship

The relationship between race and position for college basketball players was investigated using a sample of 644 student-athletes at 47 NCAA affiliates. Seven different operationalizations of position, the dependent variable, produced bivariate associations that were negligible and not statistically significant. The introduction of five control variables (NCAA division, playing and scholarship status, sex, and year in school) failed to alter the bivariate outcomes. The present data indicate that stacking in college basketball has declined, particularly at the center position, but continues to exist at forward and guard slots.

scholarly journals Aptidão aeróbica é associada com a melhora da capacidade de sprints repetidos de atletas de basquetebol após seis semanas de treinamento durante o período preparatório

2018 ◽  
Vol 20 (1) ◽  
pp. 114-124
Author(s):  
Petrus Gantois ◽  
Felipe José Aidar ◽  
Matheus Peixoto Dantas ◽  
Leandro Medeiros da Silva ◽  
Pedro Pinheiros Paes ◽  
...  
Keyword(s):  
Limiting Factor ◽  
Simple Linear Regression ◽  
Treadmill Test ◽  
Basketball Players ◽  
Repeated Sprints ◽  
College Basketball ◽  
Male College ◽  
Before And After ◽  
The Relationship ◽  
Paired T Test

The repeated sprints ability (RSA) is considered an important attribute for basketball, being aerobic fitness pointed out as limiting factor for repetition of sprints. The aim of the study was to verify if the change in VO2PEAK is related to the improvement of RSA after six weeks of training during preseason. Twelve male college basketball players aged 18-24 participated in the study. Players were submitted to body composition evaluation, maximum incremental treadmill test and RSA test (6x30-m) before and after six weeks of training. For the purpose of the study, the calculation of the change percentage delta was used. Paired t-test was used to verify differences after training and Pearson’s correlation and simple linear regression were used to verify the relationship between Δ%VO2PEAK and Δ%RSA. There were improvements in RSAPEAK (t (1.11) = 2.7, p = 0.023); RSAMEAN (t (1.11)= 2.8, p= 0.019); RSATOTAL (t (1.11)= 2.6, p= 0.028); RSADEC (t (1.11)= 2.9, p = 0.015); and sprints 4 (t (1.11)= 2.4, p= 0.037); 5 (t (1.11)= 3.14, p= 0.010); and 6 (t (1.11)= 3.65, p= 0.004) and VO2PEAK (t (1.11)= -5.4, p <0.001); Δ%VO2PEAK was related to Δ%RSAMEAN (r= -0.667; r2= 0.383), Δ%RSATOTAL (r= -0.673; r2= 0.393), Δ%Sprint 3 (r= -0.669; r2= 0.387), Δ%Sprint 4 (r= -0.659 ; r2 = 0.371), Δ%Sprint 5 (r= -0.689; r2 = 0.413), Δ%Sprint 6 (r= -0.678; r2 = 0.400). It is possible to conclude that ~ 39% of the improvement in variables associated with the maintenance of repeated sprints (RSAMEAN, RSATOTAL, Sprints 3,4,5 and 6) of basketball players was accompanied by an increase of ~ 7.5% in VO2PEAK. 

Association Between Functional Movement Screen Scores and Injuries in Male College Basketball Players

2020 ◽  
Vol 29 (5) ◽  
pp. 621-625 ◽  
Author(s):  
Kanako Shimoura ◽  
Yasuaki Nakayama ◽  
Yuto Tashiro ◽  
Takayuki Hotta ◽  
Yusuke Suzuki ◽  
...  
Keyword(s):  
Group Differences ◽  
Functional Movement Screen ◽  
Basketball Players ◽  
Functional Movement ◽  
College Basketball ◽  
Logistic Analysis ◽  
Male College ◽  
Deep Squat ◽  
The Relationship ◽  
Multivariate Logistic Analysis

Context: The functional movement screen (FMS) is an assessment tool for movement dysfunction, which is used to reduce the risk of injury. Although the relationship between the FMS composite score and injuries has been extensively studied, the association between FMS scores and injuries in only college basketball players remains unknown. Objective: To examine the relationship between the FMS score and injuries in basketball players. Design: Cross-sectional study. Setting: University research laboratory. Participants: Eighty-one male college basketball players (average age 20.1 [1.3] y) participated. Main Outcome Measures: The FMS composite score was calculated from 7 movement tests. The incidence of injuries over a 1-year period prior to the test day was determined based on a questionnaire. Individuals were categorized into 2 groups: injury (with a serious basketball-related injury resulting in the loss of practice and game time for at least 4 wk) and noninjury groups. Mann–Whitney U and chi-square tests were used to evaluate group differences in the composite FMS and 7 movement scores, respectively. Furthermore, the scores significant on univariate analyses were submitted to a multivariate logistic analysis, adjusting for participant characteristics. Results: The composite FMS scores of the 2 groups were not significantly different (P = .38). Among the 7 tasks, only the deep squat and hurdle step showed significant group differences (P = .03 and P = .001, respectively). The multivariate logistic analysis revealed that deep squat (odds ratio, 6.48; 95% confidence interval, 1.23–34.01; P = .03) and hurdle step scores (odds ratio, 25.80; 95% confidence interval, 1.81–368.73; P = .02) were significantly associated with injuries, even after adjustment for participant characteristics. Conclusions: Deep squat and hurdle step scores may be associated with injuries in basketball players. Further research should be conducted to confirm that these 2 scores can predict the incidence of injuries in basketball players.

Race, Revenues, and College Basketball

1995 ◽  
Vol 23 (3) ◽  
pp. 75-90 ◽  
Author(s):  
Robert W. Brown ◽  
R. Todd Jewell
Keyword(s):  
Racial Differences ◽  
Black Student ◽  
Student Athletes ◽  
Marginal Revenue ◽  
Basketball Players ◽  
Strong Incentive ◽  
Black And White ◽  
Black Player ◽  
College Basketball ◽  
White College

Customer discrimination may result in racial differences in the marginal revenue products generated by workers. College basketball data allow for direct comparisons of the racial differences in the marginal revenues generated by players. This article compares the revenue generating potential of the top black and white college basketball players. A highly skilled white college player generates over $100,000 in per game revenues as compared to around $30,000 for a black player of equal talent, providing a strong incentive for colleges to discriminate against recruiting black student-athletes.

scholarly journals The link between ethnic diversity and scientific impact: the mediating effect of novelty and audience diversity

2021 ◽  
Author(s):  
Jielan Ding ◽  
Zhesi Shen ◽  
Per Ahlgren ◽  
Tobias Jeppsson ◽  
David Minguillo ◽  
...  
Keyword(s):  
Ethnic Diversity ◽  
Scientific Collaboration ◽  
Information Science ◽  
Mediating Effect ◽  
Path Modeling ◽  
Control Variables ◽  
Scientific Impact ◽  
Subject Categories ◽  
Sound Management ◽  
The Relationship

AbstractUnderstanding the nature and value of scientific collaboration is essential for sound management and proactive research policies. One component of collaboration is the composition and diversity of contributing authors. This study explores how ethnic diversity in scientific collaboration affects scientific impact, by presenting a conceptual model to connect ethnic diversity, based on author names, with scientific impact, assuming novelty and audience diversity as mediators. The model also controls for affiliated country diversity and affiliated country size. Using path modeling, we apply the model to the Web of Science subject categories Nanoscience & Nanotechnology, Ecology and Information Science & Library. For all three subject categories, and regardless of if control variables are considered or not, we find a weak positive relationship between ethnic diversity and scientific impact. The relationship is weaker, however, when control variables are included. For all three fields, the mediated effect through audience diversity is substantially stronger than the mediated effect through novelty in the relationship, and the former effect is much stronger than the direct effect between the ethnic diversity and scientific impact. Our findings further suggest that ethnic diversity is more associated with short-term scientific impact compared to long-term scientific impact.

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