Preferred Behaviors Used by Coaches in Female Middle School Athletic Programs

Authors: Raymond Tucker

Corresponding Author:
Raymond Tucker, D.S.M, CSCS, FMSL1, USATFL1, USAWLP-1
Assistant Professor of Kinesiology
University of Houston at Victoria
3007 N. Ben Wilson
Victoria, Texas 77901
Phone: (361)-570-4381

Raymond Tucker is an assistant professor of Kinesiology at the University of Houston at Victoria. He is a graduate of the United States Sports Academy with a Doctorate in Sports Management, and he is a certified strength and conditioning specialist by the National Strength and Conditioning Association. He is also a certified coach by the United States Track and Field Association, United States Weightlifting Federation, and Functional Movement Systems. He is certified by the state board of educator certification in Texas in health grades (EC-12) and secondary physical education (6-12).

Preferred Behaviors Used by Coaches in Female Middle School Athletic Programs

The purpose of this study was to determine female athlete’s perception of the behavior styles of leadership used by their coaches in female middle school athletic programs. The average of these perceptions can be viewed as the actual behavior style of leadership coaches used in the treatment of their athletes. The study compared behavior styles of leadership used by coaches in female middle school athletic programs at three different middle schools. This study also compares coaches from the three different middle schools to determine if the behavior styles of leadership used are similar amongst coaches.

Data for this study was collected using the Leadership Scale of Sports (LSS) questionnaire with the permission of Dr. Packianthan Chelladurai Ph.D at Ohio State University. The questionnaire measures an athlete’s perception of their coach’s behavior style of leadership and consists of forty items that all begin with “My Coach.” These forty items represent five dimensions of leadership behavior in sports and operationally defined in the Leadership Scale of Sports.

The scoring of the Leadership Scale of Sports questionnaire was based on an ordinal scale, five-category scale that consists of a numerical number: 1. Always; 2. Often (about 75 % of the time); 3. Occasionally (50% of the time); 4. Seldom (about 25% of the time); 5 Never. Each of the forty items on the Leadership Scale of Sports questionnaire represents one of the five latent dimensions of leadership (2). These five dimensions were
1. Autocratic Behavior
2. Democratic Behavior
3. Positive Feedback
4. Social Support Behavior
5. Training and Instruction

The athletic coordinators of each school were each given instructions in person prior to the questionnaire being mailed. The questionnaires were sent back in a self- addressed stamped envelope. Athletic coordinators at the respective middle schools received communication in person, phone, and e-mail. The data was analyzed quantitatively by using the 15.0 version of the SPSS statistical software. Due to the ordinal and theoretically categorical nature of the LSS scale, nonparametric statistical methods (i.e., a test of medians rather than means) was used in all data analyses. Specially, the Mann-Whitney U, Kruskal-Wallis, and multi-way contingency table (log-linear) nonparametric ANOVA tests was used. To what degree was there a difference among the distribution of LSS scores on the five dimensions for eighth grade females in middle school sports? To answer this question, the Kruskal-Wallis nonparametric alternative to the parametric analysis of variance (ANOVA) was employed. If a statistically significant finding was observed, post-hoc analyses was conducted to determine what leadership behaviors were preferred based on median scores.

Results of this study did detect a statistically significant difference in the behavior styles of leadership used by coaches among the middle schools between the following dimensions: (1) democratic behavior and training and instruction, (2) autocratic behavior and training and instruction, (3) social support and training and instruction, (4) positive feedback and democratic behavior, (5) positive feedback and autocratic behavior, (6) positive feedback and social support. Results of this study indicate coaches at the three respective middle school in this study place more emphasis on the social support, democratic and autocratic behavior styles of leadership. This study does not determine which behavior style of leadership is superior for the overall success of a female’s middle school athletic program. What follows is the basis for this study, procedures used to conduct the research, an analysis of the data, conclusions, and finally, recommendations for further research on this topic.

Keywords: Coaches, Coaching Climate, Effective Leadership, Female Athletes, Sports

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Factors That Influence Collegiate Student-Athletes to Transfer, Consider Transferring, or Not Transfer

Authors: Jared K. Richards, Undergraduate Student, Shelley L. Holden, Ed.D., Steven F. Pugh, Ph.D.

Corresponding Author:
Steven F. Pugh
Department of Health, Kinesiology, and Sport
University of South Alabama, 36688

Steven Pugh is a professor and program leader for teacher education programs in health and physical education, Shelley Holden, is an associate professor in health and physical education and Jared Richards is an undergraduate, exercise science major in the B.S. program at the University of South Alabama.

Factors That Influence Collegiate Student-Athletes to Transfer, Consider Transferring, or Not Transfer

Student-athletes deal with many stressors every day of their collegiate career and each athlete responds to these stressors in different ways. Some thrive, while others seek new environments. The purpose of this study was to assess the reasons college student-athletes reported for transferring, seriously considered transferring, or not transferring from their original university. Also, the study examined transfer status and perceived stress and/or internal locus of control scores. Little research investigating factors related to athlete transfer decisions has been done. Participants were collegiate student athletes aged 17-23. Results indicated that 56% of athletes that transferred or seriously considered transferring listed coaching style as a reason, while 88% of athletes that have not transferred listed academics as a reason for remaining in their current setting. Data indicated that one factor does not typically convince a student-athlete to transfer, rather, it is a complex interaction of many factors.

Keywords: Athlete attrition, Sport, Coaching

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General Managers and the Importance of Using Analytics

Authors: Dr. Rocco P. Porreca

Corresponding Author:
Rocco P. Porreca, Ed. D.
380 SE Mizner Blvd. Apt. 1718
Boca Raton, FL 33432

Dr. Porreca is an adjunct professor in the College of Business and Management at Lynn University.

General Managers and the Importance of Using Analytics

Albert Einstein defined insanity as “doing the same thing over and over again and expecting different results.” Sport is changing. Athletes are becoming faster and stronger. The rate and pace of play is steadily increasing. Therefore sport, as a result, adapts and evolves. Recently, the way in which franchises draft players and build rosters is beginning to change. In order to remain competitive, sport franchises are beginning to shy away from the conventional norm and are thinking outside of the box. Specifically, franchises are exploring analytics and how this type of statistical analysis can be beneficial.

Keywords: analytics, moneyball, moneypuck, statistics

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On the Relationship Between Attacking Third Passes and Success in the English Premier League

Authors: Bret R. Myers; Brian Q. Coughlin

Corresponding Author:
Bret R. Myers
204 Eagle Glen Drive
Coatesville, PA 19320

Bret Myers is an assistant professor of management and operations at Villanova University. He also works as an analytics consultant for Toronto FC of Major League Soccer. Bret’s research and consulting is at the intersection of core sporting knowledge and the leveraging of data analysis to improve decision making for competitive advantage.

Brian Coughlin is a senior data analyst at Decision Resources Group in Exton, PA. He also serves as director of lacrosse operations at Villanova University. His passion lies in the field of analytics with a specific interest in mining data, analyzing statistics, and offering strategic recommendations that help organizations make better decisions.

On the relationship between attacking third passes and success in the English Premier League

This research examined how changes in attacking third pass behavior can impact a team’s ability to maintain leads and secure wins based on data collected from the 2011-2012 English Premier League Season. A team’s attacking third behavior is measured by the number of attacking third passes completed per minute. The results of this paper suggest that while teams tend to complete less passes in the final third when they are ahead in a match vs. being behind, there is evidence to suggest that a drop in attacking third pass behavior when ahead in a match will reduce the likelihood of maintaining a lead and securing three points.

Keywords: Soccer Strategy, Coaching Strategy, Sports Analytics, Soccer Analytics, Protecting a Lead, Staying Aggressive throughout a Match

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Goal-based Metrics Better Than Shot-based Metrics at Predicting Hockey Success

Author: Rob Found
9432-152 Street
Edmonton, AB, Canada
T5R 1N2
(780) 479-7919

Corresponding author:

The growing business of professional sports has lead to an increasing demand for effective metrics quantifying factors leading to team success, and evaluating individual player contributions to that success. In the sport of hockey the advancement of analytics has lead to a decline in the use of goal-based metrics, and an increased reliance on shot-based metrics. I tested assumptions behind this trend by using statistical modeling of 10 years of NHL data to directly compare the effectiveness of goal versus shot-based metrics at predicting team success, and comparative hypothesis testing to determine how well goals and shots quantify player contributions to team success. Goal-based models consistently outperformed their shot-based analogs. Models of team goal differential successfully predicted winning % during the 2015-16 season, while shot differential did not. Goal-based metrics (i.e. relative plus-minus/minute of ice time) were also better than shot-based metrics (i.e. relative Corsi/minute of ice time) for evaluating individual player contributions to team winning %. These results show that team and individual performance is not correlated with all shots, but only those shots effective enough to result in goals. These results will lead to more effective evaluation of individual players, and better understanding and prediction of those factors leading to team success.

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