Applied Sports Science newsletter – June 15, 2016

… He feels so good right now, in fact, that [James] Harrison said he could see playing beyond 2016.

“I’m not ready to say anything” about this possibly being his final season. “Could I extend it? If you would ask me now, yeah. That’s something I’ll deal with when I get to that.”

Only two linebackers in NFL history have played the game into their 40s — Clay Matthews II and Junior Seau.

An athlete is anyone who is committed to a sporting, recreational or lifestyle goal. Setting a goal is the first step. After you’ve set yourself a S.M.A.R.T. (Specific, Measurable, Attainable, Relevant and Timely) goal, the work begins.

But how do you know where to start?
What are your weaknesses?
How do you exploit your strengths?

Creating a baseline and learning where you are now allows you to effectively plan for the future and achieve your goals. All athletes should complete performance assessments in order to safely and effectively create training programs.

PURPOSE:

Cortisol (C) and testosterone (T) are impacted significantly by prolonged endurance exercise with inverse responses. Increases in C are witnessed concurrently with decrements in T, possibly impacting recovery. This study was conducted to assess the dynamics of C and free T (fT) concentration and recovery time following an exhaustive endurance exercise session (EES).
METHODS:

12 endurance-trained males (X ± SD: VO2max 66.3±4.8 ml/kg/min, age 22.8 ± 3.1 years, body fat 11.0 ± 1.4 %, training 7.1 ± 3.2 years) completed a treadmill EES at ventilatory threshold (74.7 ± 4.6 % of VO2max; 96.9 ± 10.8 min). Basal blood C and fT were collected at baseline: -48, -24 h, and immediately before (0 h) the EES as well as immediately (+0 h), +24 h, +48 h, and +72 h after the EES. Blood glucose (G) was measured to confirm no undue influence on C. Statistically data were analyzed with repeated measures ANOVA (LSD post hoc).
RESULTS:

C (nmol/L) increased significantly from -48 h (321 ± 59) to +0 h (701 ± 178) (p < 0.001), and displayed a baseline overshoot with +24 h (209 ± 67) being significantly lower than -48 and +0 h (p < 0.03). fT (pmol/L) decreased significantly from -48 h (161 ± 40) to +0 h (106 ± 38) (p < 0.01) and remained lower at +24 h (110 ± 33) and +48 h (129 ± 30) (p < 0.001). G remained stable throughout. A moderately negative correlation (r = -0.636, p < 0.026) was found between C and fT at +0 h.
CONCLUSIONS:

EES recovery may require 48 h for C and 72 h for fT to return to baseline values. Furthermore, C and fT were only correlated immediately post-exercise. Future research should perform more frequent measurements throughout time course.

Purpose: Stride-to-stride fluctuations in running stride interval display long-range correlations that breakdown in the presence of fatigue accumulated during an exhaustive run. The purpose of our study was to investigate whether long-range correlations in running stride interval were reduced by fatigue accumulated during prolonged exposure to a high training load (functional overreaching) and were associated with decrements in performance caused by functional overreaching. Methods: Ten trained male runners completed 7-days of light training (LT7), 14-days of heavy training (HT14) designed to induce a state of functional overreaching and 10-days of light training (LT10) in a fixed order. Running stride intervals and 5 km time trial (5TT) performance were assessed after each training phase. The strength of long-range correlations in running stride interval was assessed at three speeds (8, 10.5 and 13 km?h-1) using detrended fluctuation analysis. Results: Relative to performance post-LT7, time to complete the 5TT was increased post-HT14 (+18 seconds; P0.50). Changes in stride interval long-range correlations measured at a 10.5 km?h-1 running speed were negatively associated with changes in 5TT performance (r -0.46; P=0.03). Conclusions: Runners who were most affected by the prolonged exposure to high training load (as evidenced by greater reductions in 5TT performance) experienced the greatest reductions in stride interval long-range correlations. Measurement of stride interval long-range correlations may be useful for monitoring the effect of high training loads on athlete performance.

We’re not telling you anything you (probably) don’t already know here, but the FC Dallas academy might just be the best of its ilk in the entire country.

This season’s academy performance, to say nothing of the 14 Homegrowns and bevy of U.S. YNT stalwarts, is as good a confirmation as any. The FCD U16s, fresh off a 2015 title, look poised to win it again with a fresh group, something no team has ever done in the DA’s nine-year history. Their 23-2-0 record is the best in the academy at the U16 level and gave them the top overall “seed” entering the playoffs in their hometown this month.

The relationship between your ‘need to achieve’ and your ‘fear of failure’ will ultimately dictate your success as an athlete. Professor Greg Whyte reveals how to keep motivation in check

Two key factors affect motivation in sport: the need to achieve and the fear of failure.

During the first off-season practice open to reporters on May 24, all eyes were on No. 27, and the speculation began. How much weight did Green Bay Packers running back Eddie Lacy lose?

After practice, Packers coach Mike McCarthy was asked if Lacy had dropped into the right weight range.

“Every player has a body composition, so that’s what we focus on,” McCarthy said. “That’s a daily focus and evaluation between the weight room and the training room and the nutrition.”

Asked more specifically if Lacy needed to weigh 240 pounds or less, McCarthy simply said, “It’s based on his body composition.”

A new study found that the NFL, NBA and NHL teams traveling from west to east had a higher winning percentage compared to teams traveling in the opposite direction.

The results of this study highlight the importance of the direction of the circadian disadvantage on the probability of success.

“These results highlight the importance of circadian rhythms in sport performance. They also raise concerns about well-established practices such as early training sessions and late-night athletic competitions and the possible negative effects on performance and health,” said co-author, Geneviève Forest, PhD, Université du Québec en Outaouais (UQO).

Apple Watch will now allow users to share activity and work-out data with their friends, the company announced at its annual WWDC conference today.

With this new feature, users can share heart rate data with their friends, and even “smack talk” using voice messages in order to encourage competition. Users receive notifications about their friends’ progress, including completed activity rings, finished workouts, and earned achievements. This sharing feature is also directly connected to the Messages app, so users can communicate with friends and family with new “smart replies” specially customized for activity and workouts.

Screening methods sensitive to movement strategies that increase anterior cruciate ligament (ACL) loads are likely to be effective in identifying athletes at-risk of ACL injury. Current ACL injury risk screening methods are yet to be evaluated for their ability to identify athletes’ who exhibit high-risk lower limb mechanics during sport-specific maneuvers associated with ACL injury occurrences. The purpose of this study was to examine the efficacy of two ACL injury risk screening methods in identifying high-risk lower limb mechanics during a sport-specific landing task. Thirty-two female athletes were screened using the Landing Error Scoring System (LESS) and Tuck Jump Assessment. Participants’ also completed a sport-specific landing task, during which three-dimensional kinematic and kinetic data were collected. One-dimensional statistical parametric mapping was used to examine the relationships between screening method scores, and the three-dimensional hip and knee joint rotation and moment data from the sport-specific landing. Higher LESS scores were associated with reduced knee flexion from 30 to 57 ms after initial contact (P = 0.003) during the sport-specific landing; however, no additional relationships were found. These findings suggest the LESS and Tuck Jump Assessment may have minimal applicability in identifying athletes’ who exhibit high-risk landing postures in the sport-specific task examined.

The majority of National Collegiate Athletic Association (NCAA) programs do not have a sports nutritionist, leaving athletes to gather information from resources that vary in reputability. The objective of this study was to identify a need for the development of accessible and reputable resources of nutrition information by assessing the current use of nutrition information resources, dietary habits, and sports nutrition knowledge among Division I collegiate athletes. Seventy-two athletes across eight sports completed questionnaires concerning nutrition resources used, dietary habits, and sports nutrition knowledge. Additionally, interest levels in a mobile device application for delivery of nutrition information and tools were assessed. Primary sources for nutrition information included parents and family, athletic trainers (AT), and the internet/media, and athletes felt most comfortable discussing nutrition with parents and family, ATs, and strength and conditioning specialists. Performance on a sports nutrition knowledge questionnaire indicated a general lack of nutrition knowledge, and the high frequency of “unsure” responses suggested a lack of confidence in nutrition knowledge. Athletes conveyed a high likelihood that they would utilize a mobile device application as a nutrition resource, but were more interested in access to nutrition topics than tools such as a food log. We found that college athletes possess minimal sports nutrition knowledge, obtain nutrition information from non-professional resources, and were interested in utilizing a mobile device application as a resource. Further research is needed to explore the feasibility and effectiveness of alternative resources, such as a mobile device application, to deliver nutrition information and improve nutrition knowledge.

The GSSI Fuel Habits Survey is a brief assessment of the sports nutrition habits of an athlete for one training session or competition.

Background

Video analysis of running gait is frequently performed in orthopedic and sports medicine practices to assess biomechanical factors that may contribute to injury. However, the reliability of a whole body assessment has not been determined.
Objective

To determine the intra-rater and inter-rater reliability of the qualitative assessment of specific running kinematics from a 2-dimensional video.
Methods

Running gait analysis videos were recorded from 15 individuals, (8 males; 7 females) running at a self-selected pace (3.17 ± 0.40 m/s; 8:28 ± 1:04 min/mile), using a high speed camera (120 frames per second). These videos were independently rated on 2 occasions by 3 experienced physical therapists using a standardized qualitative assessment. Fifteen sagittal and frontal plane kinematic variables were rated using a 3- or 5-point categorical scale at specific events of the gait cycle including initial contact (3) and midstance (9), or across the full gait cycle (3). The video frame number corresponding to each gait event was also recorded. Intra- and inter-rater reliability were calculated for gait event detection (intraclass correlation coefficient (ICC); standard error of measurement (SEM)) and the individual kinematic variables (weighted kappa [Kw]).
Results

Gait event detection was highly reproducible within raters (ICCs, 0.94-0.99; SEM, 0.3-1.0 frames) and between raters (ICCs, 0.77-0.99; SEM, 0.4-1.9 frames). Eleven of the 15 kinematic variables demonstrated substantial (Kw 0.60-.799) or excellent (Kw >0.80) intra-rater agreement with the exception of foot to center of mass position (Kw = 0.59), forefoot position (Kw = 0.58), ankle dorsiflexion at midstance (Kw = 0.49) and center of mass vertical excursion (Kw = 0.36). Inter-rater agreement for the kinematic measures was more widely varying (range of Kw, 0.08-0.85) with 5 variables showing substantial or excellent reliability.
Conclusions

The qualitative assessment of specific kinematic measures during running can be reliably performed with the use of a high-speed video camera. Detection of specific gait events was highly reproducible, as were common kinematic variables such as rearfoot position, foot-strike pattern, tibial inclination angle, knee flexion angle and forward trunk lean. Other variables should be used with caution.

After NHL commissioner Gary Bettman presented Pittsburgh Penguins captain Sidney Crosby with the Stanley Cup, Crosby hoisted the sports’ famed trophy above his head and slowly zigged, zagged and meandered across the ice with no particular direction in mind and with no particular hurry. The Canadian broadcast team noted as much, quipping, “He’s clearly going to savor this for a little bit.”

Crosby’s victory spiral with the Cup was about as slow as he’ll ever skate, particularly after a championship series in which the Penguins beat the San Jose Sharks in six games in large part because of an advantage in speed and quickness.

Pittsburgh acquired Phil Kessel before the season and then during the season promoted Tom Kuhnhackl and traded for Carl Hagelin. Crosby, Hagelin, and Kessel have long ranked among the sport’s fastest skaters, and data from PowerScout Hockey—an optical-tracking company—illustrates the pace advantage the Penguins enjoyed over the Sharks.