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Sports, Volume 3, Issue 1 (March 2015) – 5 articles , Pages 1-55

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213 KiB  
Article
Pitch Sequence Complexity and Long-Term Pitcher Performance
by Joel R. Bock
Sports 2015, 3(1), 40-55; https://doi.org/10.3390/sports3010040 - 2 Mar 2015
Cited by 9 | Viewed by 9465
Abstract
Winning one or two games during a Major League Baseball (MLB) season is often the difference between a team advancing to post-season play, or “waiting until next year”. Technology advances have made it feasible to augment historical data with in-game contextual data to [...] Read more.
Winning one or two games during a Major League Baseball (MLB) season is often the difference between a team advancing to post-season play, or “waiting until next year”. Technology advances have made it feasible to augment historical data with in-game contextual data to provide managers immediate insights regarding an opponent’s next move, thereby providing a competitive edge. We developed statistical models of pitcher behavior using pitch sequences thrown during three recent MLB seasons (2011–2013). The purpose of these models was to predict the next pitch type, for each pitcher, based on data available at the immediate moment, in each at-bat. Independent models were developed for each player’s most frequent four pitches. The overall predictability of next pitch type is 74:5%. Additional analyses on pitcher predictability within specific game situations are discussed. Finally, using linear regression analysis, we show that an index of pitch sequence predictability may be used to project player performance in terms of Earned Run Average (ERA) and Fielding Independent Pitching (FIP) over a longer term. On a restricted range of the independent variable, reducing complexity in selection of pitches is correlated with higher values of both FIP and ERA for the players represented in the sample. Both models were significant at the α = 0.05 level (ERA: p = 0.022; FIP: p = 0.0114). With further development, such models may reduce risk faced by management in evaluation of potential trades, or to scouts assessing unproven emerging talent. Pitchers themselves might benefit from awareness of their individual statistical tendencies, and adapt their behavior on the mound accordingly. To our knowledge, the predictive model relating pitch-wise complexity and long-term performance appears to be novel. Full article
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536 KiB  
Article
The Progression of Male 100 m Sprinting with a Lower-Limb Amputation 1976–2012
by Bryce Dyer
Sports 2015, 3(1), 30-39; https://doi.org/10.3390/sports3010030 - 16 Feb 2015
Cited by 9 | Viewed by 7121
Abstract
Sprinting with a lower-limb amputation over 100 m has taken place in the Paralympic Games for over three decades. The aim of this paper is to statistically evaluate the performances and participation levels of such athletes during this period. The level of performance [...] Read more.
Sprinting with a lower-limb amputation over 100 m has taken place in the Paralympic Games for over three decades. The aim of this paper is to statistically evaluate the performances and participation levels of such athletes during this period. The level of performance improvement over a 36-year period was proposed to be significantly greater than the able-bodied equivalent. Coupled with this, a major spike in amputee running performance improvement was shown to occur from 1984–1988. This supports previously recorded accounts of a major technological change being made at this time. Finally, whilst the average performance of the medallists has increased consistently over the 36-year history, the overall participation in the event fell significantly after 1988 and did not recover until 2012. Full article
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386 KiB  
Review
Epidemiological Review of Injuries in Rugby Union
by Jean-François Kaux, Marc Julia, François Delvaux, Jean-Louis Croisier, Bénédicte Forthomme, Damien Monnot, Marie Chupin, Jean-Michel Crielaard, Caroline Le Goff, Patrick Durez, Philippe Ernst, Sébastien Guns and Arnaud Laly
Sports 2015, 3(1), 21-29; https://doi.org/10.3390/sports3010021 - 23 Jan 2015
Cited by 12 | Viewed by 15254
Abstract
Rugby is a sport that is growing in popularity. A contact sport par excellence, it causes a significant number of injuries. In Rugby Union, there are 30 to 91 injuries per 1000 match hours. This epidemiological review of injuries incurred by rugby [...] Read more.
Rugby is a sport that is growing in popularity. A contact sport par excellence, it causes a significant number of injuries. In Rugby Union, there are 30 to 91 injuries per 1000 match hours. This epidemiological review of injuries incurred by rugby players mentions the position and type of injuries, the causes, time during the match and season in which they occur and the players’ positions as well as the length of players’ absences following the injury. Full article
(This article belongs to the Special Issue Sports Medicine)
494 KiB  
Article
Effect of Level and Downhill Running on Breathing Efficiency
by Matthew D. Cook, Stephen D. Myers, John S. M. Kelly and Mark E. T. Willems
Sports 2015, 3(1), 12-20; https://doi.org/10.3390/sports3010012 - 23 Jan 2015
Cited by 5 | Viewed by 6459
Abstract
Ventilatory equivalents for oxygen and carbon dioxide are physiological measures of breathing efficiency, and are known to be affected by the intensity and mode of exercise. We examined the effect of level running (gradient 0%) and muscle-damaging downhill running (−12%), matched for oxygen [...] Read more.
Ventilatory equivalents for oxygen and carbon dioxide are physiological measures of breathing efficiency, and are known to be affected by the intensity and mode of exercise. We examined the effect of level running (gradient 0%) and muscle-damaging downhill running (−12%), matched for oxygen uptake, on the ventilatory equivalents for oxygen () and carbon dioxide (). Nine men (27 ± 9 years, 179 ± 7 cm, 75 ± 12 kg, : 52.0 ± 7.7 mL·kg−1·min−1) completed two 40-min running bouts (5 × 8-min with 2-min inter-bout rest), one level and one downhill. Running intensity was matched at 60% of maximal metabolic equivalent. Maximal isometric force of m.quadriceps femoris was measured before and after the running bouts. Data was analyzed with 2-way ANOVA or paired samples t-tests. Running speed (downhill: 13.5 ± 3.2, level: 9.6 ± 2.2 km·h−1) and isometric force deficits (downhill: 17.2 ± 7.6%, level: 2.0 ± 6.9%) were higher for downhill running. Running bouts for level and downhill gradients had , heart rates and respiratory exchange ratio values that were not different indicating matched intensity and metabolic demands. During downhill running, the , (downhill: 29.7 ± 3.3, level: 27.2 ± 1.6) and (downhill: 33.3 ± 2.7, level: 30.4 ± 1.9) were 7.1% and 8.3% higher (p < 0.05) than level running. In conclusion, breathing efficiency appears lower during downhill running (i.e., muscle-damaging exercise) compared to level running at a similar moderate intensity. Full article
(This article belongs to the Special Issue Sports Medicine)
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509 KiB  
Communication
The Association between Anthropometric Variables, Functional Movement Screen Scores and 100 m Freestyle Swimming Performance in Youth Swimmers
by Daisy Bond, Laura Goodson, Samuel W. Oxford, Alan M. Nevill and Michael J. Duncan
Sports 2015, 3(1), 1-11; https://doi.org/10.3390/sports3010001 - 8 Jan 2015
Cited by 21 | Viewed by 8860
Abstract
This study examined the association between anthropometric variables, Functional Movement Screen (FMS) scores and 100 m freestyle swimming performance in early adolescent swimmers. Fifty competitive, national level, youth swimmers (21 males, 29 females, mean age ± SD = 13.5 ± 1.5 years, age [...] Read more.
This study examined the association between anthropometric variables, Functional Movement Screen (FMS) scores and 100 m freestyle swimming performance in early adolescent swimmers. Fifty competitive, national level, youth swimmers (21 males, 29 females, mean age ± SD = 13.5 ± 1.5 years, age range 11–16 years) performed an “all-out” 100 m freestyle (front crawl) swim as fast as they could in a 50 m pool. A median divide for 100 m timed swim was also used to divide the sample into faster or slower groups. Height, body mass, skinfolds and limb lengths were also assessed. Maturation was calculated by proxy using anthropometric measures and participants also undertook the FMS as a measure of functional performance. Backwards linear regression indicated a significant model (p = 0.0001, Adjusted R2 = 0.638) explaining 63.8% of the variance in swim performance with total sum of skinfolds, upper leg length, lower leg length, hand length and total height significantly contributing to the model. Swimmers who were classed as fast had lower total sum of skinfolds (p = 0.005) and higher total FMS score (p = 0.005) compared to their slower peers. In summary, this study indicates that anthropometric variables significantly explained the variance in 100 m freestyle swimming performance in youth swimmers. Full article
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