The Center of Excellence has a large team of graduate students and faculty involved with the development of hundreds of college athletes. With the wide variety of sports, performance levels, competitive time frames, and academic schedules involved in our program, sound and effective communication is of utmost importance to ensure excellent service is provided to ensure our athletes perform their best. Bridge Athletics helps to provide a means to communicate between coaching staffs. Having all the information stored on a shared network allows our whole program access to each other’s work. This allows for quality control from team to team to be implemented.
Additionally, these communicative efforts go beyond just among faculty, but also from coach to athlete. Athletes can leave notes in their programming that will be updated to the server in real time. This allows the coach the ability to have athletes leave notes that are related to their personal programming. Not only could this serve multiple purposes for the strength and conditioning coach to keep better tabs on
the individualization of their athletes, but it will also help their fellow coaches have that ability to with everything in house on the Bridge server, further cementing quality communication and understanding among all involved in the development of our athletes.
Whether it is universal terminology shared for every athlete, appropriate volume loads are implemented at the appropriate times in relation to the competitive calendar or being able to look back on the history of the team’s training program to see where they have been in the weightroom and how to plan for the future. Bridge acts as a standardized method to perform a variety of tasks.

Kurt McDowell, MS, CSCS
Doctoral Student, Sport Physiology and Performance
East Tennessee State University

         In the first installment of this series, Andrew Nelson discussed why accurate tracking of volume load is crucial when conducting sport science research. The previous post by Luke DeVirgiliis discussed how our program is initiating the transition to Bridge athletics. If you haven’t read these posts yet - scroll down to get caught up.
        This post will expand on how our program accomplishes this research, provides evidence-based training to our athletes, and how Bridge Athletics helps us accomplish both of these tasks.
            As a brief summary: for a sport scientist or coach working in high-level sport, quantifying training loads helps us understand why changes in performance occurred. This information provides a window into how to elicit beneficial changes in our athletes in the future.
            Our program is responsible for planning and executing S&C with six hundred team and individual sports athletes. One of the foundational pillars of our program is athlete monitoring, which helps us provide a better service to the coaching staff and athletes, along with producing transformative sport science research. Let’s first give a general example of how we perform athlete monitoring in a long-term scenario:

​(Oftentimes, testing is completed more frequently; nonetheless, this example provides a general overview of the process) ​

This system allows us quite literally to monitor performance changes over time in our athletes. Physical performance testing may include:

• Body composition
• Maximal force production [such as the Isometric Mid-Thigh Pull (Stone et al., 2019)]
• Jump Testing (including calculation of power output & net impulse)
• Field testing specific to the sport (sprints or other sport-specific metrics such as serve velocity)

 
            Between the testing sessions, it is essential to carefully quantify and track an athlete’s training. Bridge Athletic has included several functionalities that make this a much more time-effective, complete, and accurate process for our coaching and sport science staff. Some of these tools include:

• Tracking attendance to training sessions
• Tracking actual volume load completed by athletes during sessions
  • Including if all sets were completed and what exercises were altered
• Timestamping workouts
• Automatically tracking Session RPE based on a validated approach (Foster, 2001)

 
In the old days, this work all had to be done by hand, taking considerable time, energy, and detracting from the important responsibility of actually coaching. Now, Bridge accomplishes this without our coaches giving it a second thought. Not only is it easier, but it’s also more accurate; yielding more valid data collection.
As the semester closes, we retest our athletes’ physical performance to track changes from the pre-semester baseline. Let’s say the results come in and scores have improved; great! The sports coaches are happy with their team’s enhanced athletic ability, meaning we’ve done our jobs as high-performance coaches. But it’s important to ask: why did they improve? As Andrew mentioned previously, a practitioner needs to apply the correct stimulus to create positive adaptation. By using Bridge Athletics, the Sport Scientist can look back and see exactly what quantity and mode of stimulus was applied. We can then learn what has worked, and use this information to empower our future training protocols.
On the other hand, what do we do when an athlete doesn’t improve? Tracking the training throughout the year can help us understand why the athlete did not improve. There’s a handful of factors to consider including:

• Perhaps this athlete missed a handful of sessions, and at crucial times in training.
• Alternatively, maybe the volume load completed was much different than the athletes who did improve; this can help us identify athletes who are overworking or underworking.
• Or, perhaps the athlete’s performance excelled during one phase of training but faltered during another. In this instance, we can make sure that in the future we schedule that athlete to train in the method that worked for them around the time of competition.
• In a block periodized model, there are certain phases when we don’t expect all of the athlete’s physical attributes to improve. For example, during a heavy accumulation phase of strength-endurance during the offseason, we might expect the rate of force development to temporarily decrease. We program this training style far away from important competition, laying the foundation for the subsequent training phases (strength and strength-power) to super compensate RFD at the time of competition. Objective volume-load monitoring accomplished through Bridge makes it effortless to track when an athlete went through this phase of training; we can then continue to monitor the effects of each individual training phase, making sure our block periodized model allowed the athlete’s performance to peak at the necessary time.

 
Without monitoring, quantifying, and recording the athlete’s training, it would be impossible to figure out why we observed the long-term changes we did. Bridge takes out the guesswork in sport performance, by automatically tracking these metrics.
 In addition to formal testing of performance at the beginning and end of a semester, it’s imperative to monitor performance continually throughout the year. This can be accomplished with weekly jump testing or weekly tracking of sprint or pitch velocity in practice. By comparing these sport specific performance metrics to the training being accomplished in the weight room, we can understand how athletes acutely react to training. We can use this information to acutely set the athletes up for success in season, by planning training that acutely increases physical capabilities immediately before important events or matches.
Needless to say, by carefully tracking training and response, a sport scientist can learn from training, and use this knowledge to improve training in the future. This method of monitoring also provides copious amounts of data that can be utilized to create powerful sport science research. This meticulous data collection doesn’t happen by accident, however. A tool such as Bridge Athletics greatly improves the practitioner’s ability to track all this information, with much less time and effort spent on busy work. It allows the practitioner to focus on what really matters, as they don’t have to spend excess time and energy on the collection; they can focus on using the data to inform their training programs.
 
Trader Flora, M.S., CSCS
Ph.D Student in Exercise Physiology
East Tennessee State University
 
References
Foster, C., Florhaug., Franklin, J., Gottschall, L., Hrovatin, L., Parker, S., Doleshal, P., Dodge, C. (2001). A new approach to monitoring exercise training. Journal of Strength and Conditioning Research: National Strength & Conditioning Association. 15. 109-15. 10.1519/00124278-200102000-00019. 
 
Stone, Michael & O'Bryant, Harold & Hornsby, Guy & Cunanan, Aaron & Mizuguchi, Satoshi & Suarez, Dylan & Marsh, Donald & Haff, Guy & Ramsey, Michael & Beckham, George & Santana, Hugo & Wagle, John & Stone, Meg & Pierce, Kyle. (2019). Using the Isometric Mid-thigh Pull in the Monitoring of Weightlifters: 25+ Years of Experience. 19-26.
 
 

 
 
 

​Bridging the gap between technology and Strength and Conditioning
 
One of the biggest obstacles facing collegiate strength and conditioning coaches is effective and timely program implementation. Coaches are competing with class schedules, practice times and NCAA hour regulations to get the time to work with their athletes in the weight room. Beyond limitations with scheduling, strength and conditioning coaches have to program for multiple positions, injured athletes, and scale appropriately for athletes with vastly different abilities and training ages. Bridge Athletic provides solutions for any Strength Coach looking to overcome these obstacles. Any program written in Bridge Athletic can be delivered to athletes as an out-of-season program, which allows coaches to remain NCAA compliant over the summer. The ability to change between a playlist or scheduled program allows coaches to be more flexible with teams that have variable travel schedules, or athletes involved in clinicals in their field of study. Bridge also allows coaches to program regression and progression exercises within a training session to accommodate injured or less advanced athletes, as well as assign positions to athletes and adjust programs accordingly.
 
 Our partnership with Bridge Athletic has allowed for us to deliver high quality programming to the athletes we work with over the past several months. By creating and delivering our programs in Bridge, the athletes utilizing the Bridge Tracker app can see a history of every set rep and exercise they’ve done, adding precision to their training process. Bridge also allows coaches to add video and audio comments to blocks within a program, or individual exercises, allowing us as coaches to provide our athletes with more context than just words on an excel sheet.
 
Our department is gearing up to get all of our coaches and athletes on Bridge Athletic for this semester, as well as begin the use of Bridge in volume load tracking for research.  Stay tuned for updates on how we're using BA to improve our performance coaching and sport science research.  For more information on the partnership opportunities and possible research conducted by our laboratory using BridgeAthletic please contact nelsonda1@etsu.edu.
 
Luke DeVirgiliis, MS, CSCS
ETSU Olympic Sports Performance Coach and Weight Room Supervisor
Doctoral Student, Sport Physiology and Performance
East Tennessee State University

​Training in sport, as defined by German sport scientist Dietrich Harre, is “the physical, technical, intellectual, psychological and moral preparation of an athlete by means of physical exercises, i.e., by applying workloads.” (Harre, 1982).  Managing these workloads, or training stressors is of principal importance to the sport preparatory coach or scientist for effectively designing, implementing, and/or monitoring a training program (Haff, 2010).  In the sporting context, this is primarily done through the systematic manipulation of volume and intensity across the yearly training plan. Practitioners may then retroactively analyze how the current training stressors correspond with the previously performed loads or loads that were planned.  Whichever method one chooses to quantify the training load, it is objectively important to the performance coach and sport scientist to accurately track this data to optimize athlete preparedness.  However, the importance of quantifying an athlete’s workload extends beyond just the optimal implementation of training.  Accurately recording and reporting the training load is equally important for researchers within the field of sport science (Haff, 2010). Such research is continuously published by the Exercise and Sport Science Laboratory here at ETSU, an internationally recognized leader in the field.  Graduate students working in this lab have the unique experience of conducting extremely ecologically valid research on high-level athletes while simultaneously undertaking the preparatory training for these athletes.
Serving as the strength coach, sport scientist, and researcher, graduate students within our program are responsible for designing, delivering, and monitoring the training of our athletes under the supervision of the lab director and director of the Center of Excellence for Sport Science and Coach Education (CESSCE) Dr. Michael Stone and Meg Stone, respectively.  Additionally, these students are tasked with using this data to conduct transformational research in the field of sport science.  Using the knowledge gained from our studies, my peers and I are expected to take a research-based approach to design training for our athletes.  However, like most performance coaches, this is where the fulfilling work of designing training ends and the tedious work of visualizing and monitoring these training programs begins.  In the past, concerning designing and monitoring training, this has been done using software such as Microsoft Excel or Google Sheets.  Most within this field are extremely familiar with these programs and would agree that the flexibility they offer in designing, delivering, and monitoring training is most excellent.  Unfortunately, most would also likely agree that this process can be extremely time-consuming, tedious, and often a substandard approach to visualizing large datasets associated with athlete monitoring and research.  Once these training programs are executed, we are then tasked with inspecting and recording all training loads and intensities for monitoring and research purposes.   While extremely important to the work that we do, again, this is an extremely time-consuming and tedious process.  Fortunately, due to our new partnership with BridgeAthletic, this will no longer be the case. 
BridgeAthletic (BA) offers cutting-edge strength and conditioning software geared towards the most effective and efficient planning, delivery, and tracking of training programs with seamless integration of data into our research repository.  Their platform makes for systematic collection of data on external training load, internal training load, performance testing, subjective wellness, etc. more efficient than ever.  Furthermore, due to their easily accessible mobile application, BridgeTracker, our graduate students can effortlessly plan and prescribe training to their athletes.  The first step towards integrating BA into our was learning the ins and outs of the software.  Senior Customer Success Manager at BridgeAthletic, Megan Watson, saw to this by conducting a detailed onboarding demonstration with select graduate students that was later disseminated to all our coaches.  Our scientific approach to training meant we needed to ensure the software would work for what we do, and this session was extremely valuable in navigating the way toward actualizing that.  Since then, we have set up automated data transfer from their platform to our data management system, smartabase.  BA quickly set up the API between the two platforms in the background allowing for hands-free delivery of data to our research repository for future research and data visualization.  Additionally, we began the process of acquiring tablets for the weight room so coaches can easily deliver and monitor training on the floor by taking full advantage of BA’s mobile application for coaches and athletes.  Finally, while BA is preprogrammed with thousands of training templates and exercises, we needed to begin creating an exercise library specific to ETSU.  This is extremely relevant to our research-based approach to training as it ensures our coaches are all speaking the same language and allows for improved continuity when conducting research within our field.
There is much to come from our implementation of BridgeAthletic.  As it stands, BA will become fully integrated by all our coaches come Fall of 2022.  Stay tuned for updates on how we're using BA to improve our performance coaching and sport science research.  For more information on the partnership opportunities and possible research conducted by our laboratory using BridgeAthletic please contact me at nelsonda1@etsu.edu. 
 
Andrew Nelson, MS, CSCS
ETSU Olympic Sports Performance Coach and Weight Room Supervisor
Doctoral Student, Sport Physiology and Performance
East Tennessee State University
 
 
Haff, Guy. (2010). Quantifying Workloads in Resistance Training: A Brief Review. Prof. Strength and Cond.. 10. 31-40.
Harre, D. (1982). Principles of sports training: Introduction to the theory and methods of training.

These data were collected from the 2018 Youth National Championships in Michigan and permission for sharing results was granted by USAW. The file below contains data from countermovement jumps (CMJ) performed on a jump mat. 

Study Description: The CMJ testing was conducted with a jump mat (Probotics Inc., Huntsville, AL USA). Each weightlifter provided two trials with maximum effort while holding a PVC pipe on the back of the shoulders. Countermovement jump heights (CMJH) from the two trials were then averaged as a performance score for each weightlifter.

*Addendum: 8/12/2019*
ICC (two-way mixed with absolute agreement for single measurement) = 0.983
Standard error of measurement = 1.36cm