A Tale of Two Presidents: The Rise and Fall of Division I Athletics at Birmingham-Southern College

Abstract

In 1999, Birmingham-Southern College (BSC) announced that they were leaving the National Association of Intercollegiate Athletics to join the highest rank of the National Collegiate Athletic Association-Division I. While competing in Division I, the size of BSC’s athletic budget was in the bottom 10 per cent. By 2006, the Board of Trustees at Birmingham-Southern voted to reclassify to Division III. Why did Birmingham-Southern decide to enter Division I? How did the academic mission of Birmingham-Southern play a role in the rise to Division I or the fall to Division III? What role, if any, did the presidents of Birmingham-Southern play in its joining and leaving Division I? One reason Birmingham-Southern decided to compete at the Division I level was because their leaders believed in the ‘Flutie Factor’, which is the concept that athletic success will benefit the entire institution. BSC’s transition into Division I during 1999 suggests that the commercialization of big-time college athletics encourages presidents to overemphasize athletics, and that they face little opposition when doing so. Moreover, the opposition to BSC’s reclassification into Division III during 2006 suggests that presidents face more resistance when attempting to lead their college into a less prestigious level of competition, even if the move better fits the college’s academic mission.     

Sprint performance and mechanical outputs computed with an iPhone app: Comparison with existing reference methods

The purpose of this study was to assess validity and reliability of sprint performance outcomes measured with an iPhone application (named: MySprint) and existing field methods (i.e. timing photocells and radar gun). To do this, 12 highly trained male sprinters performed 6 maximal 40-m sprints during a single session which were simultaneously timed using 7 pairs of timing photocells, a radar gun and a newly developed iPhone app based on high-speed video recording. Several split times as well as mechanical outputs computed from the model proposed by Samozino et al. [(2015). A simple method for measuring power, force, velocity properties, and mechanical effectiveness in sprint running. Scandinavian Journal of Medicine & Science in Sports. https://doi.org/10.1111/sms.12490] were then measured by each system, and values were compared for validity and reliability purposes. First, there was an almost perfect correlation between the values of time for each split of the 40-m sprint measured with MySprint and the timing photocells (r?=?0.989–0.999, standard error of estimate?=?0.007–0.015?s, intraclass correlation coefficient (ICC)?=?1.0). Second, almost perfect associations were observed for the maximal theoretical horizontal force (F₀), the maximal theoretical velocity (V₀), the maximal power (P_max) and the mechanical effectiveness (DRF – decrease in the ratio of force over acceleration) measured with the app and the radar gun (r?=?0.974–0.999, ICC?=?0.987–1.00). Finally, when analysing the performance outputs of the six different sprints of each athlete, almost identical levels of reliability were observed as revealed by the coefficient of variation (MySprint: CV?=?0.027–0.14%; reference systems: CV?=?0.028–0.11%). Results on the present study showed that sprint performance can be evaluated in a valid and reliable way using a novel iPhone app.     

Validity of the “Samsung Health” application to measure steps: A study with two different samsung smartphones

The purpose of this study was to examine the validity of a highly popular pedometer application (Samsung Health). Sixteen adults (28.8 ± 8.9 years of age) wore two Samsung smartphone models, Samsung Galaxy Core Prime (SGCP) and Samsung Galaxy S4 (SGS4), at three body locations (waist, arm, and hand) while walking and running over a 50-m test. All trials were recorded using a video as a gold standard measure of step counts. Results indicated that the validity of Samsung Health varied depending on the smartphone model, its body location, and the type of gait (walking and running). Samsung Health showed acceptable validity when the SGCP was located on the hand (Bias = ?8.3%; RMSE = 5.6), and especially on the arm (Bias = ?7.2%; RMSE = 4.9) while running, and when the SGS4 was located on the arm (Bias = ?7.5%; RMSE = 5.4), and especially on the waist (Bias = 5.4%; RMSE = 3.7) while walking. Samsung Health only showed good validity when the SGS4 was located on the arm (Bias = 2.9%; RMSE = 3.6), and especially on the hand (Bias = 0.5%; RMSE = 2.5) while running. This application showed unacceptable validity in the remaining options.     

Jump height loss as an indicator of fatigue during sprint training

This study analysed the acute mechanical and metabolic responses to a sprint training session focused on maintaining maximal speed until a given speed loss was reached. Nine male high-level sprinters performed 60 m running sprints up to a 3% in speed loss with 6 min rests between sets. Mechanical responses (countermovement jump (CMJ) height and speed loss) and metabolic responses (blood lactate and ammonia concentrations) were measured pre-exercise and after each set was performed. Jump height loss showed almost perfect relationships with both lactate (r = 0.91) and ammonia (r = 0.91) concentrations. In addition, nearly perfect relationships were observed for each athlete between CMJ height loss and lactate (r = 0.93–0.99) and ammonia (r = 0.94–0.99). Very large correlations were found between speed loss and lactate (r = 0.83), and ammonia (r = 0.86) concentrations. Furthermore, close relationships were observed for each athlete between speed loss and lactate (r = 0.86–0.99), and ammonia (r = 0.88–0.98). These results suggest that the CMJ test may allow more accurate setting of training loads in sprint training sessions, by using an individualised sprint dose based on mechanical and physiological responses rather than a standard fixed number of sprints for all athletes.     

Snap-N-Send: A valid and reliable method for assessing the energy intake of elite adolescent athletes

To ensure that elite adolescent athletes meet their unique training, growth and maturation demands, it is imperative to have access to valid measures of energy intake. Contemporary methods demand close attention-to-detail, meaning that athletes often do not fully adhere to real-time protocols. This study represents the first investigation of a real-time dietary assessment designed using a comprehensive behaviour change framework (COM-B). In a crossover design, 12 elite adolescent male rugby players recorded their energy intake via an estimated food diary (est-FD) and photography-based mobile assessment (‘Snap-n-Send’), combined with a 24-h dietary recall interview. Two 4-day assessment periods were divided into three separate recording environments: 96?h free-living and researcher-observed; 72?h free-living and 10?h researcher-observed. Assessment periods were one month apart. All foods and beverages were provided and weighed by the research team to quantify actual intakes. ‘Snap-n-Send’ reported a small mean bias for under-reporting across 96?h (?0.75?MJ?day^?1; 95% confidence interval [CI] for bias?=??5.7% to ?2.2%, p?<?.001), 72?h (?0.76?MJ?day^?1; 95% CI for bias?=??5.6% to ?2.1%, p?=?.004) and 10?h (?0.72?MJ?day^?1; 95% CI for bias?=??8.1% to ?0.1%; p?=?.067) environments. The est-FD reported a moderate mean bias for under-reporting across 96?h (?2.89?MJ?day^?1; 95% CI for bias?=??17.9% to ?10.2%; p?<?.001), 72?h (?2.88?MJ?day^?1; 95% CI for bias?=??17.9% to ?10.1%; p?<?.001) and 10?h (?2.52?MJ?day^?1;?26.1% to ?5.3%; p?=?.023) environments. Results evidence the ability of ‘Snap-n-Send’ to accurately assess the diet of elite adolescent athletes, signalling the exciting promise of this comprehensive and theoretical behavioural approach within valid dietary assessment.