No description available.

No description available.

Use of accelerometers to assess physical activity (PA) is widespread in public health research, but their utility is often limited by the accuracy of data processing techniques. We hypothesized that more sophisticated approaches to data processing could distinguish between activity types based on accelerometer data, providing a more accurate picture of PA. Using data from MTI Actigraphs worn by 6 subjects during four activities (walking, walking uphill, vacuuming, working at a computer) quadratic discriminant analysis (QDA) was performed, and a hidden Markov model (HMM) was "trained" to recognize the activities. The ability of the new analytic techniques to accurately classify PA was assessed. The mean (SE) percentage of time points for which the QDA correctly identified activity mode was 70.9(1.2)%. Computer work was correctly recognized most frequently (mean (SE) percent correct = 100(0.01)%) followed by vacuuming (67.5(1.5)%), uphill walking (58.2(3.5)%), and walking (53.6(3.3)%). The mean (SE) percentage of time points for which the HMM correctly identified activity mode was 80.8(0.9)%. Vacuuming was correctly recognized most frequently (mean (SE) percent correct = 98.8(0.05)%) followed by computer work (97.3(0.7)%), walking (62.6(2.3)%), and uphill walking (62.5(2.3)%). In contrast to a traditional method of data processing that misidentified the intensity level of 100% of the time spent vacuuming and walking uphill, the QDA and HMM approaches correctly estimated the intensity of activity 99% of the time. In a second study, we applied and HMM to data collected on five subjects doing a variety of activities. The HMM was able to correctly classify sitting most frequently (mean(se) percentage of time points correctly identified was 99.2%(0.8%)) followed by walking on declined treadmill (94.2%(4.6%)), jogging (91.6%(5.6%)), walking on level treadmill at 1.25 m·s-1 (90.8%(6.3%)), walking on level treadmill at 1.70 m·s-1 (81.8%(18.2%)), walking on an inclined treadmill (73.1%(16.6%)), vacuuming (58.6%(14.3%)), walking up stairs (50.3%(17.0%)), walking down stairs (43.3%(17.8%)), and a box loading task (27.8%(9.5%)). The novel approach of estimating activity mode, rather than activity level, may allow for more accurate field-based estimates of physical activity using accelerometer data, which would allow for more accurate public health information regarding the relationship between exercise and a variety of chronic diseases.

No description available.

No description available.

No description available.

No description available.

The purpose of this descriptive study was to provide insight into ice hockey coaches' beliefs and perceptions of coach education programs. USA Hockey is the governing body for all hockey in the United States and requires education through the USA Hockey Coaching Education Program. Gaining a better understanding of how hockey coaches perceive coach education programs provided information that can be used in the evaluation and development of future programs. The theoretical framework used in this study was expectancy-value theory. USA Hockey youth coaches (N = 410) were surveyed using the Coaching Education Questionnaire, a 55-item instrument used to collect quantitative data. The study's findings indicated that coaches found communication with athletes (M = 4.27, SD = 0.90), advanced instructional drills (M = 4.03, SD = 0.96), and motivational techniques (M = 4.02, SD = 0.98) to be topics that are most helpful in a coach education program. Coaches were most likely to pursue further education if the program contained relevant topics (M = 4.01, SD = 0.91), had online availability (M = 3.97, SD = 1.04), and was convenient (M = 3.80, SD = 1.08). Coaches rated items related to coaching education pursuit (M = 2.60, SD = 0.48) higher than items related to coaching education beliefs (M = 2.77, SD = 0.38) by coaches. These findings revealed the need for a more robust evaluation program for USA Hockey's Coaching Education Program. Additionally, the findings suggest the formal education program offered by USA Hockey may not be sufficient in developing effective coaches; a formal mentoring program should be developed to complement the current program.

Much of the literature regarding abuse in athletics has focused on the effects these actions have on the athletes both short and long term. In relation to ethics, such research has been primarily focused on how ethics effects all aspects of athletics. Therefore, the purpose of this study was to examine if factors that cause coaches to victimize athletes are related to a lack of ethical understanding. This qualitative phenomenological research design was used to highlight emerging themes revealed during the study. Thirteen purposely selected individuals, labeled as athlete, athlete/coach, or coach, participated in one-on-one semi structured interviews. The participants' interviews were conducted independently, reflecting a wide range of opinions and experiences. The conceptual framework included the theories of self-perception and Nash's Three Moral Languages that guide ethical behavior. The use of the seven constructs as identifiers allowed for recommendations for athletes, coaches, the National Governing Bodies (NGB's), and the United States Olympic Committee. For athletes, high-achieving or otherwise, this study provided a perspective into not only what allowed these individuals to achieve their athletic and coaching goals, but also a view into the issues they faced related to abuse and experiencing unethical situations. For coaches, their beliefs of what is acceptable behavior of athlete and coach is apparent to others on the field of play. However, their own self-perception of what is acceptable might be completely different. The ability to act ethically is dependent on coaches connecting their own actions to decisions that would be considered ethical according to the rules or guidelines of their sport. Recommendations include areas regarding teaching ethics to athletes as part of sports programs beginning in the early years of education, and better educating coaches to not put themselves in unethical situations. Though education is a factor in the quality of life post athletics, this and other research studies suggest that abuse of athletes can cause mental, physical, and emotional issues as these individuals transition into life post-athletics.

Sports analytics is a fast-growing field of analytics. In particular, sports analytics with a focus on National Football League (NFL). In this thesis, we will review many articles on football analytics to have an in-depth understanding of the current stat of football analytics. In addition, we can learn from past research to identify interesting research direction to advance sports analytics with a focus on football analytics. In this thesis, we have carefully examined all current analytical results in the following fields: current state of football analytics, analytics regarding the draft, analytics for wide receivers as well as offensive linemen, analytics on other offensive positions, and we have identified the following research direction: the need for a scale rating system that is equal of all positions but unique to expectations of that position especially when it comes to wide receivers and offensive linemen. Lastly, we lay the groundwork for future work, which will make use of the following statistical learning algorithms: logistic regression, XG Boost, decision trees, and time series, to analyze the NFL data, both tracking data from the first six weeks of the 2020 season as well as play by play data from 1999 to 2022 to introduce these new algorithms to sports analytics community.