LISTEN: Biochemistry and Biomechanics of Sport Performance

From the elitefts™ Sports Performance Podcast host

Carl Valle doesn't pull any punches when it comes to discussing what is really important in sports performance. In an industry that often depends on the appearance of improvement in order to market training methodologies, Valle has stayed objective asking the simple question, "how do you know your training is working?" This is especially true when it comes to testing and assessment with the use of technology. Valle understands and has communicated his message much like a quote from John Maxwell:

Valle may have the most comprehensive knowledge of the ever-so-prominent use of measuring tools when it comes to athletic readiness and performance. He has managed to stay unbiased in an industry that is built on and somewhat depends on that bias to sell products and services. Valle is concerned with results and has dedicated himself to helping coaches decipher between the most applicable technology to truly understand what is reliable and valid.

Topics Covered in this Podcast

1. Deciding to Take a Risk
2. The Gap between Technology and Application
3. From HRV to GPS: Assessing Readiness
4. Over-Testing Syndrome
5. Practical Procedures for Testing
6. Facial Coding for Readiness
7. Evaluating Muscle Tissue with TMG
8. Using GPS to Adapt Workload
9. Communicating and Educating Team Coaches to Morph Tactical and Physical Training
10. VBT Training: A Metric of a Metric of a Metric
11. Perspective on the Athlete Management System
12. The 3 Data Sets That All Coaches Want
13. Technology and Job Security
14. Jurassic Park for Coaches and the 3 Levels of Technology
15. Quick Take-A-Ways
16. Speed Training Made Simple
17. How to Reach Carl

The Carl Valle File

Since 1997 Carl Valle has coached Track and Field at every level, from high school to the Olympic level in the sprints and hurdles. Having the privilege of working with great athletes that have been All-American and school record holders, many rewarding experiences made Valle love both the sport and working with great people. After years of seeing athletes fall through the cracks in the US and abroad, Valle decided to create a unique solution to leverage the great coaching community and medical network by organizing those resources.

- Courtesy Freelap USA

The following is a section from the Kinetics Manual, 2013 and is now 
part of the FreelapUSA Article Resource

As technologies evolve, the research grade data is not more available to coaches, which creates a major explosion in analytics from wearable sensors and mobile technologies. Just like the infestation of false profits with the area of periodization, experts in monitoring have increased as the “Moneyball” era is not transforming to the data age of sport.

Now, questionable proprietary metrics, performance dashboards using moronic emoticons, and inappropriate data collection techniques are plaguing elite sport. Monitoring, instead of creating insight to the responses of athletes to training, is now creating a data and information Dark Age in regards to the understanding of training, by poorly appreciating the basic principles. Without fully comprehending the training process, monitoring is nothing more than observational recordings of a suicide mission, resulting in ornamental data displayed real time for coaches to find a purpose because they are too fearful to train. In order to change sport or team culture and/or give honest feedback to elite athletes, coaches must have the authority to create accountability of all parts of the performance team, including] management, ownership medical staff, and the athletes themselves. Monitoring has favored the low hanging fruit of data sets, such as the use of heart rate data and player tracking options like GPS or accelerometers.

In this article, the importance of balancing biodynamics will be explored, as an over-representation of physiological data has poorly guided coaches. The severe need to monitor training programs with the use of fusion technologies, the best practices in data management and analytics, and proper data visualization strategies will be fully outlined. In the future, evidence based coaching will be a standard that coaches can use as a resource to fully reveal what is truth and what is fiction.

Monitoring by definition may evoke the wrong approach to coaches and medical professionals, as it conveys a passive attitude to training, even if interventions are ready to implement in reaction to what is seen. Monitoring to reduce injury from fatigue will cripple any program and backfire if programs are looking for markers of overreaching because of a reversal of placebo. Culturally, the purpose of monitoring is to audit the planned program and any plan that is poorly deigned will be doomed from the beginning if monitoring is layered on top, no matter how advanced the technologies and powerful the analysis. Eventually, programs must train or stress the athlete in order to perform as well as the past or to perform better. Each year, no matter how closely the program resembles the previous season, there will be uncharted directions from a simple change of life’s variables that can be either poisoning the well or mixing helpful catalyst agents, such as a positive influence in athletes. Monitoring is an attempt to show the current and perhaps future trends in sport science and sports medicine, but it is only the tip of the iceberg as more data is below the surface, data of which the most progressive of researchers are aware of. No matter how many data sets one has or how powerful the analytic engine of an athlete.

Management System (AMS), the experienced coach with good analog record keeping is vastly more effective. Technology is an extension of coaching to make things a little bit more automated and to save time, but the surplus of time must be in actual action, not hindsight preaching. Included here are five primary concepts that are the foundation for monitoring elite sport.

Data Acquisition

Most efforts in a program should involve the most effective ways to make information acquisition faster, simpler, easier, and broader in volume, depth, and width. Data collection should not be seen as an impairment to the actual training or therapy session, but a silent and passive surveillance of the athlete with the leveraging of security type configurations. Coaches and medical staff have poorly implemented data collections, especially on the clinical areas.

The use of wearable video and voice recognition software can help not only with real time collection, but help translate real world data into more manageable options such as text and imaging solutions. Workflows must be efficient and effective in both delivering the intervention and the collection of the data.

Data Management

Data volume is growing, but ensuring that all data sets are coherent requires a lot of cleaning, in regards to data and metadata. The most powerful changes are time stamps paired with global position system coordinates, since time and space and the data in context is the best evidence one can have objectively. Data management is about organizing data, be it medical images, raw sensor feeds, physiological data, or even game information. Organization is not about compartmentalizing data, but creating powerful timelines to see how events shape from data trends and decision-making. Cloud systems and API development are key areas that technologies must make work or data will be orphaned on segregated islands. Organized data is not just sorting, but making sure that the data interacts appropriately, so when combined, the information doesn’t overload the observer. Currently, no system, be it open source or private outside of two Spanish systems in Europe. Evolution occurs when any professional in an organization can easily access and view data that is meaningful without extensive manual work.

Data Analysis

When data is properly warehoused and backed up, proper analysis can start. Countless times, data is unable to be analyzed because of formatting and compatibility issues. Analysis should be based on both real world significance and statistical relevance. When data is analyzed, the process may become tainted from inappropriate representation, from the wrong statistical practices. Many convenient approaches may falsely give credit to the wrong variable or major problems are overlooked because statistical significance is interpreted wrongly with some sports metrics. Analysis in trending and prediction should be very carefully arranged not to misjudge data and the best approaches involve minimizing analysis outside of visualizing data. Some data must be analyzed and pushed through algorithms, but only when necessary. Data mining should be about finding the right pattern or right data sets, not forcefully creating relationships that don’t exist in reality because of bias and agenda specific approaches.

Data Visualization

The best practices of data visualization should support the most powerful of options, the integrated timeline. Coaches and medical staff should see the entire season, if not the entire career in a broad perspective and be able to drill down to specific details that are relevant. Dashboards should be free of graphic debris that is unnecessary and poorly represented. Animation, cartoony pie charts, and useless gauges are common in sports performance because business dashboards are crippled by the same problems. Key performance indicators should number between three to eight and they should have the ability to be drilled down by proper data management and gesture controls on devices and wearable screens. Reports and cloud pages should have the clarity that allows all parties to be on one page collaboratively, without dilution of specialization or confusion from poor graphical design.

Data Action

All of the data processing doesn’t need to be immediately actionable in some cases, but strangely, many don’t have any intervention strategy based on the effectiveness in impact. Interventions should be chased based on application and how much impact one can perform. Natural decision trees should be mapped out based on predicted outcomes, ideally being dormant from good planning. Unexpected events, acts of God, and randomness will create a need for reaction, but most action should be based on normative responses, not counteracting foolish plans and inexperience. Coaches and medical staffs should think about the refinement of the plans in place from monitoring and improve the methodology or keep the methodology in place and work on compliance and execution.

Monitoring and testing is a constant and vigilant approach to ensuring the plans are working accordingly, not an overreaction to data that may be perfectly normal. As pedagogy and screening evolves, monitoring will be more of an insurance policy and less of a feed forward approach.

Integrated Timeline: The most effective way to monitor athletes involves a linear timeline starting with the transition phase, followed by the other phases in calendar order. Abstract models simply ignore the reality that the given time dictates what is done and what must be compromised. Adaptation rates and recovery periods can be seen with simple line plots and tables. Additional user experience enhancements with touch interfaces using gestures, can drill down for more data, but the analog options still have major impacts in planning, the evaluation of the effectiveness of the program, and the implementation. Different perspectives and roles will need their specific data, but all data should be shared to help with both communication, to reduce gaps, and to overlap coverage that could be problematic.

Performance Data Streams: The efforts to reduce injury by modifying performance training has ironically failed to increase output and make an impact on athlete health. Performance data should involve organized benchmarks and recorded training data. Based on time and the beginning status, one must create a reasonable set of goals of what can be done, given the resources available. All data looking for changes in positive outcomes should be included, such as speed, power, conditioning, athletic skill, and joint range of motion. Weekly loading and sessions technique driven output should be recorded and the most elegant options in data visualization and representation should be summarized in a dashboard or training log. Benchmarks ranging form simple attendance to very specific foot mechanics are to be projected, based on norms of growth and intervention strength.

Medical Data Streams: Medical data is actually far behind performance due to the clinical bottlenecks of acquisition. When data is not available, the records are usually only documented when political problems surface. As a result, revisionist history coupled with theoretical beliefs will be the only data available. AMS systems, such as those used at major soccer clubs are glorified Content Management Systems (CMS) and are poor solutions, as the underlying problems in the acquisition of data and the more important thought processes behind clinical choices is a needed area. Voice recognition, guided point of view cameras, and BAN style tools will change how data is collected with a hands on program. Since rehabilitation is roughly summarized as sub-maximal training, the parallels are enough to focus on diagnostic and prescription style rehabilitation plans with return to play, rather than spending efforts on sub-maximal training, an area that coaches tend to comprehend far better.

The three primary data sets that all professionals need to be focused on are molecular, motion, and emotion. Both medical and performance specialists will want to have all three data sets and will have responsibilities adjusted based on roles and expertise.

• Biochemistry: The biochemical data with physiological motoring should be streamed as ways to look for fatigue and new milestones of interventions from nutrition and training load. Physiological and biochemical data is the most manageable, but languages and units should be carefully converted to reduce error in interpretation.
• Biomechanics: Mobile devices have increased the video data volume drastically, but the data quality has had a major reduction in useful metrics. Device style analysis and coaching is at first glance a game changer, but most approaches actually are poor options in the immediate and long run. Motion capture and high end video systems should be a priority with infrastructure, such as cloud systems and appropriate analytics. Video limitations are speed of analysis and current algorithm and software development is leaning towards automatic detection of plantar pressure, 3-D joint kinematics and kinetics, and video motion.
• Biopsychology: Humans have an innate ability to communicate nonverbally with each other and new technologies are able to capture emotional communication with the use of video and facial expression. Still, the coach has the most powerful data set that no machine can ever harness like another person. The feedback form personal communication must be entered into a notation platform as the coaches senses are the most important data set. Athlete’s lives and the emotional and neurological pains and pleasures will need to be factored into the more objective data from training and medical sets.

The most glaring problem with monitoring is the fixation of physiological data, most likely stemming from the convenience of simple heart rate and now GPS tools. Work rates of practice are easily captured by the devices and the data is far easier to interpret than motion capture. Unfortunately, the injury rates are seen in the absence of fatigue and athletes are not injuring the cellular organelles, but the musculoskeletal system. Thus, it can be strongly warned that movement impairments must be thoroughly used to reduce injuries, beyond just baseline screening. Both coaches and medical professionals need to dramatically change in viewing joint and muscle function instead of relying on more crude options, such as player tracking and physiological data streams.

Key Performance Indicators for movement are highly matched and inversely related to the etiology of injury. Both the medical and performance specialists will be reviewing the same data but in far different perspectives. While each department will have unique interests, many of the data sets will serve many roles and sometimes, roles overlap. For example, inefficient movement performance scores and metrics may induce the risk of joint compensations. Sometimes, as performance decreases, the risk of injury increases with some sporting movements.

• Baseline Testing: The earliest contact during the season is a natural time to do baseline testing. While the monitoring process never ends in theory, a cyclical action of each season presses the need to see how the athlete is initiating each year. Collecting baseline data is not just timing, but the data must represent what a baseline is in terms of factoring in a normalcy with athletes. For example, any mechanical data on the body should be captured in a period of time in which the athlete has completed rehabilitation, which demonstrates a sufficient fitness level to adequately represent normalcy. Baseline data without normalcy may be necessary, since athletes will need to have some comparative data to start with.
• Retesting Frequency: The amount of retesting should be based on a needs analysis and a rate of change factor. The rhythm of testing should only be at the rate at which the action is necessary or when added information will change the decision significantly. Return to play strategies should have at least three data points, not including baseline, in order to discharge an athlete per metric. Testing may not be an isolated or artificially segregated period, such as using the warm up as a functional screen, but sometimes, complex injury or stagnation may merit specific testing periods.
• Athlete Comparison: Data from any performance evaluation or pathomechanics should compare not only to the athlete in other time periods, but team, league, and sport norms. Problems need to be identified and possibly quarantined if possible, if they are patterns from a central source, such as a specific coaching style or a body of knowledge that is directing staff misinformation. Comparing athletes to different models of success such as competition, historical champions, and emerging trends and styles, is an effective way to create a wise viewpoint.
• Human Performance Perspective: General or global abilities should be the standard if other sports are to have the proper perspective in athlete performance. Performance in team sport or specific events should be based on what is possible and where things are going, not where things are currently, in regards to the sport of choice. The best example can be found in comparing linear speed of Olympic athletes to team sports, in an effort to understand if current outputs are limits based on the constraints of the sport and league or the goal setting and cultural beliefs of what is possible. Realistic goals require outside perspectives in order to prevent inbreeding and apathy with innovation and improvement.

Creating KPIs should be based on what areas the organization or individual finds to have a unique and obvious impact with performance longitudinally and acutely. The most logical option is to look at injury patterns in the sport and the athlete’s medical history and simply screen the movements that are at risk and start from there. Additional input from actual team or sport coaches is perhaps the most needed area since a gap sometimes exists between the nuances of the movement in an applied manner and the general sterile and abbreviated data from a research study. The best options in acquiring authentic data are to simply test the athletes in their own environment, as it replicates what they actually do versus bringing the athlete to an artificial lab setting. Many vital elements are often eliminated from the lab, creating results that may not be applicable, even after interpretation.

Biochemical Testing

Invasive or semi-invasive testing should be done to collect data that is the underlying root variable. Sensor data is improving, but actual fluid or human material is necessary to have a fully accurate depiction of the challenges athletes face in training and in competition. Research uses blood testing and other fluid samples to show cause and effect, but bringing the lab quality information in an applied fashion with biochemical testing is a challenge in applied sport science. As technology evolves, getting biochemical data is faster, easier, less invasive, and more applied. The ecosystem of analytics and algorithm development through crowdsourcing is changing the role of sport science and disrupting the current model of consultants and advisors. Biochemical testing should be done at least three times a year at key millstones, such as the recovery week following the heaviest loading in each training phase. Combining biochemical data to sensor data is the next hot area since more wearable technologies are increasing, but individual biochemical responses are highly variable and kinetic data doesn't always indicate fatigue or a response to a training load.

Blood Testing and Analysis- The backbone of biochemical testing and mounting should be based on blood testing and the analysis that follows. Blood is not only dense in biomarker content, it has many actionable and unique benefits that make it the most valuable of data. While genetic testing is extremely useful because it has so many areas that can be identified, the information is static. Blood testing can get immediate information to the very minute, such as acidosis or longitudinal data, when analyzing nutritional status. Currently, less blood is needed to get more biomarkers, with the benefit of faster turnaround times. Mobile devices will enable small samples to give immediate feedback inexpensively in the future and current technologies are nearly at that level. Since the current standards are phlebotomist and lab structured, testing is less frequent and must be more comprehensive due to the limitations of testing frequency and convenience. This will force the timing of the testing to focus on getting more actionable and relevant information by precisely including added interpretation, based on other factors such as training and testing. Mentioned earlier, milestones in training or gauging the success of trends with performance data from training and competition, is essential to be included, especially in markers of overtraining and immune status. Metabolic factors such as blood oxygen carrying capacity must be seen as both a performance and nutritional responsibility, since many nutrients must be consumed by athletes and cannot be manufactured in the body. Countless performance and fatigue data is heavily influenced by the biochemical status of the body and nutritional information is the hardest to monitor. While a heart rate monitor is available at the consumer level, it will take years for a live or real time tool to equally match the same information for dietary practices. Blood testing and the right analysis can help create a working estimate of patterns of eating, rest, and training.

Genetic Screening- DNA advancements is making genetic screening a valuable and rather difficult set of data to manage, as the underlying reasons for the test results may be vague and unclear. For example, genetic information on the achilles is a popular area for risk consideration, but the mechanism, be it collagen formation or content versus biomechanics and structural causes, is not in agreement. The other issue is athlete privacy and the business side of sport, areas that could cease advancements or radically alter how potential is recognized with talent and risk. The crystal ball of prediction will always be cloudy, since prediction is often based on what probability is likely without interventions and no road is definite with the human will overriding a set future.

Additional Options- Advancements in other fluid collections and sometimes tissues can be evaluated, but the advantages and disadvantages must be considered, such as collections of urine and athlete privacy or the annoyance of having a dry cotton cylinder in the jaw for repeated periods of time, with saliva, instead of sensors that collect GSR. It may be effective to combine different biochemical options when necessary, but one must consider the benefit or burden ratio of any data collection option. The data from hair and tissues may be integrated when needed, but it’s up to the organization or individual to consider resources such as time, expertise, cost, and application, in order to determine it’s value and role.

Speed and Power Evaluation

Specific speed development and general power abilities should be closely watched to see how the training system is succeeding or retarding the improvements of the athlete. The current observation of power is highly coveted as it’s convenient to use power meters and weight data to see the acute and long term changes, but the primary focus should be on speed qualities and the relationship of lifting data. Longitudinal and gross scores should be balanced with context specific and very finite details to generate a complete picture. General training of specific or integrated biomotor abilities are the cornerstone to gauging change from phases and individual sessions. Provided that they are not interfered with cumbersome set-ups, they can private immediate feedback to the coach and athlete.

Testing Speed and Power should include all primary or secondary modalities to remove the learning or familiarization of the tests. Athletes will improve in testing from higher frequency of tests, but very high retesting rates wash the early improvement curves and training should be repetitive enough to see trends in the microcycle and even phases if possible. Gross tests such as short and maximal speed tests, paired with specific training modalities such as jumping and strength training tests should be done to see the results of the supportive programs. Game data can be sensitive to see changes potentially, but athletes are not stock cars or horses, thus the style and personality factors need to be considered. Absolute testing may have risks, such as maximal strength tests, but projected and sub maximal tests are not always effectively representing one’s abilities as the same challenges exist with many options. All training data is testing in some way and the kinematic and kinetic data should be fused when possible. For example, lifting tests have poor carryover in performance if done with technique that doesn’t recruit or engage the correct muscular patterns or joint kinematics. Integrating video capture and 3-D motion capture with other data sets can see how general qualities may have specific benefits unknowingly. The failure of raw wattage increases can be explained when EMG validation and pressure profiling is used. While force plates are helpful, the most useful data is timing gates, linear encoders, and accelerometers with positional hardware such as gyros. A current option of using force plate analysis with a gross jump test is too crude to be a compass in training and movement signatures should be actual sporting movements, not vertical jumps. Testing days should be used with or without resting periods to emphasize the cause and effect of gross biomotor abilities. The purity of general testing is that interpretation error is reduced and athletes will receive superb training effects from heightened arousals. The hierarchy of transfer and effectiveness of modalities starts with speed, then power, and then strength, based on the meta analysis of correlation. Some areas may be more influenced by strength, but in chapter one, the Vermeil table showed what areas in global speed can be influenced by specific options. Testing speed and power should be the soul of most programs, since most team sports are highly influenced by strength and power from culture and practice demands that are more of a factor to conditioning. Each year, the data should be cleaned and presented to show how each athlete responded to the training program in clear scoring and records of what was done and what worked or not should be presented as well.

Any time data is created, the results and process of acquiring the information must be reviewed. Numbers in isolation are not helpful and getting better numbers doesn't always lead to better results on the field, court, or track. An honest and validated effort must be done to see if the athlete is getting a better score or if they are actually producing better output. Countless examples of athletes trying to test better are timeless, as athletes will cheat tests like they sometimes cheat sport. Specific and measurable criteria must accompany each test to properly address the pursuit of better numbers versus better abilities. As we move to higher data volumes and outputs of performance, the temptation is to be completely driven by data. Team sports are faced with higher demands of interpretation as mostOlympic sports are very pure in analysis, due to the nature of their events being very quantified in time or similar scoring.

The best training programs will develop bodies that have higher outputs of functional power that can be seen in locomotive outputs in both speed and endurance capabilities of athletes. Simple metrics such as power to weight ratio are not to be overlooked, but innovations in evaluating program design such as specific benchmarks that can be recalculated depending on the received data, will be the future.

Fatigue Management - The resulting fatigue or replenishing needs of stress are popular in monitoring solutions, but are mere shadows of the underlying goal, performance. Fatigue is a necessary and essential part of training and should be seen as a tool, rather than something to avoid. Many programs with no training, such as many professional soccer clubs paint themselves into a corner of a doomed strategy of managing a ticking time bomb. While the sport may create adaptations from practice and competition, the physiological needs of long schedules still require training. Coaches and medical staffs should rethink about how biochemical, biomechanics, and biopsychology interact with the popular data sets below.

• Sleep Monitoring: One of the most obvious needs of elite or developing athletes is sleep, but very few programs change the cultural and baggage of explosive athletes.Lifestyles of student athletes or elite professionals range from monks to rockstars, living in excess. HRV can capture sleep stage data with the use of smart fabrics and mobile solutions can feed the data into a cloud system for teams and individuals to make necessary changes. Changes in androgen status can be related to both sleep and alcohol, along with travel demands of world class athletes. Interventions are only as effective as creativity and marketing, like campaigns showing cause and effect through education.
• Activity Tracking: Patterns of general activity, such as standing or sitting or even the most specific and detailed method of tracking, such as the foot strike of athletes through pressure mapping, can be performed to see recovery rates and training load responses. GPS and other tracking systems can acquire volumes and distributions of work rates, but they are crude volume estimates and are excellent for nutritional interventions and practice adjustments. Motion capture and high intensity systems such as timing, jump wattage, and other anatomy based mechanics data is needed to obtain etiology that is not able to be managed with workloads. Mobile devices, through open source options of sensor technology are already using the discarded “noise” and creating a true signal with gross accelerometer and GPS data of behavior patterns, are a far greater influence than raw pedometer type data.
• Neuromuscular Changes: The current use of Tensiomyography, thermography, and pulse technology with smart fabrics are seeing day to day and now real time changes amongst athletes. Wireless EMG competes the triad of use, fatigue, and intervention (electrical muscle stimulation or rest) with athletes. Global fatigue from nerve stimulation response metrics can get a general indication of total body fatigue and site specific or local fatigue to peripheral muscle groups, which can be identified with rapid testing procedures. Mobile and wireless technologies are necessary to take the research grade data and make the consumer friendly and clinic speed with data capture.
• ANS and SNS Balance: Heart rate variability (HRV) and galvanic skin response (GSR) are popular ways to gauge the parasympathetic state of athletes and pupil dilation metrics are emerging as options to get rapid status within a few seconds. The most solid of options is the use of HRV ultrashort tests, with a mobile device and finger sensor. Real time metrics may provide more detail, but the added value shows very little information beyond the RMSSD of a short sampling period upon wake. Blood work and other data sets are necessary to interpret daily data and weekly trends, but HRV use is very effective if compliance is there with the athletes.
• Mental and Central Fatigue: Facial coding recognition programs will evolve to create added value to subjective

indicators, just like GSR has done to help with the stress response in lie detectors. Unlike GSR with only one metric, facial coding has several options to help create more insight. Central fatigue can be estimated with brainwave technology and nerve stimulation response metrics. Subjective indicators of both pain and fatigue can help calibrate the objective data so athletes are aware of their feelings and serve as an important way to communicate with coaches in a natural manner. Subjective indicators should be used, as the athletes’ interpretations of their feelings are valuable and valid if integrated properly.

Medical Data and Return to Play

Medical data is a unique challenge in all areas of collection, analysis, and data visualization. The specific demands of both understanding the complexities of injury and the return to play strategies can be alleviated with medical grade equipment and sounding out the findings of therapeutic treatment. It is vital that the role of sports medicine is to focus on diagnosis and management versus treatment modalities. Manual therapy creates a universal impairment of data collection since the therapist is literally hands on and must compromise data collection for treatment implementation. Even if video and audio recordings capture verbal and visual information, the intricate decisions may not be shared as the thought process is very reactive with manual therapy, as many unknowns exist with both incoming injury and reaction to treatment. A solution should be the integration of diagnostic care with objective data and outlined treatment protocols for overall plans. The gaps of data and the ability to have flexibility in a program can be fulfilled with voice recognition software and annotation later.

Collaboration Recommendations Communication between medical and performance staffs requires a collaborative option that is cloud based and transparent with planning and recording. With decisions based on instantaneous information, gaps or overlaps can ruin expertise by either negating intervention or failing to cover an area that is obvious to all parties. Two examples to illustrate the common problems with rehabilitation and return to play are the roles of corrective/therapeutic exercise and simple training in programs, as well as gray areas, such as nutrition that may be seen as either a medical responsibility or performance area. Rehabilitation using low level exercise for neurological or structural adaptations may be at a threshold, at which fatigue and strain could overload a training program. Organizations must recognize that two sound programs that don’t communicate effectively can negate and or risk further damage if transparency is not instant and clear. Gaps in coverage can be limited by defined roles, even if the areas are shared and overlap each other such as the need for nutritional support. Communication is not just about sharing what one does, but the ways that each role works and what circumstances they are faced with. One simple illustration is the performance demands of training, requiring higher outputs of force than what therapeutic exercises create in rehabilitation. Another needed area is the contraindicated areas during the return to play period, so that manual therapy and tissue changes are not interfered with the specific intensities and modalities of exercises from the performance staff. Many of the lessons learned from less than ideal interactions with staffs, will create innovations and improvements in treatments.

Data Management and Visualization Simple and rapid solutions should be integrated into a combination of timelines, patient notes, and medical imaging and charts. The difficulty of many data sets is the very limited area of visualizing the body while providing conventional data charts, such as line plots and other time series. The area of inflammation of a leg is easy to see if a body chart is used, but when longitudinal data is displayed, it becomes a challenge. The lack of solid data visualization stymies the development of benchmarks and specific metrics beyond the analog scoring we see today. Creative uses of data visualization with experts must be captured properly or team coaches and management will be unable to comprehend current problems to evolve their methods of developing athletes or teams. As mentioned earlier, innovation is not about improvement in other fields, but the impact and change that it creates outside the walls of performance and medical expertise. When strategy and tactical adjutants, along with player development and payroll practices are influenced by medical information to the point of advantage, then true innovation has occurred.

In the future, data volumes will be exponentially higher and the analysis exponentially deeper as well. Visualization can help solve the impending crisis with the ability to clarify the problems of athlete injury and training. Coaches and medical staff can collaborate effectively with the use of current options, provided the support from those who make budgeting decisions appreciate the complexities and near impossible problems those in elite sport face on a day-to-day basis.

Athlete Performance Dashboards

An area that is rising in popularity, but one that is very poorly executed, is the dashboard of key performance indicators with athletes. As a way to show the most important changes in alert style graphics, the aggregation of the weakest yet most convenient data is the current fad. Cartoony bar graphs, random use of bubble charts, and ego driven attempts to place regression analysis are the most coveted toys of coaches. The athlete dashboard is to only see what is unexpected, that of which is time sensitive. Most key performance indicators are the least actionable, but the most convenient for both coaches to collect and developers to make. The combination on convenience and physiological bias creates a deadly cocktail of failure, especially when teams are driven by the fatigue centralized approach to monitoring. Dashboards are not gauges to identify problems, but to to actually audit the plan of training and to see the differences as to what was expected and what actually happened. The development of a dashboard for medical and performance is not a data challenge or even a technology solution, it is a management exercise in priorities and experience. A powerful dashboard with the wrong metrics and lack of proper interventions is no different than an incompetent staff that has no record keeping. Dashboards should be designed to allow both medical staff and coaches to make better and more rapid decisions based on valid data sets. Drilling down or aggregated data streams being available will improve the chances of success. True answers are possible when the problem is clearly addressed and the right evidence is available. The saying that proper dashboards allows coaches and staffs to ask better questions is right, but the dashboards that have the right analytic engines and preload solutions are the gold standard. Displaying problems is the first step and not an answer or process organizations and small groups are needed. Dashboards are a tool to help assist the team in directing things to what they believe will eventually lead them to success down the road.

Creating a dashboard can range from a simple attendance solution with gross performance metrics to a million dollar system with custom hardware. The effectiveness of a dashboard is the insight that it provides compared to other basic recording strategies. Dashboards are not plans, but ways to gauge the gap between what is expected and what is unexpected, with the known areas of monitoring. The advantage will come when dashboards are simply validating the brilliance of a master plan and the clockwork precision of a properly administered plan.

Several elements should be integrated with a dashboard. Dashboards have a stereotype of providing a visual display of data, but the infrastructure of a dashboard requires several other criteria. Included in this list are suggested components of performance and medical dashboards.

• Time series data display
• Action driven metrics
• SMS capability
• Cloud and API Integration
• Agnostic Device Capability

Dashboards must take multiple data streams from devices and various sources and aggregate all of it into one visual display. API development by the devices and wireless transmission removes a step from the data collection, saving time and increasing accuracy. Metrics should be actionable, but if responses from data are unable to be intervened because of culture or other limitations, the data is still valuable. Cellular and wireless internet/network access, as well as local file storage is necessary to have stability anywhere and access to the right data at all times. Immediate response to athlete data with SMS capability is extremely useful, as most athletes respond to smartphone texting over conventional calling and email. The cloud system that feeds and analyzes data should be agnostic by using web interface so any mobile, device, or computer can use the platform. Third party cloud services that sync data, backup data, and share data, are very helpful in organizing different software packages that perform additional analysis to the data used. Currently, no AMS solution is avoiding any added value beyond team or organization branding. Most vendors lure coaches into purchasing systems with the “vanity plate” logos and “your athlete here” type simulations and include random charts and portals. Unfortunately, most AMS systems are just content management systems that are weaker versions than open source options that were available five years earlier. Dashboards are not an end product, but a component to a larger system that involves business intelligence like software and massive data storage that can analyze an array of information to help make better decisions. Dramatic changes in education are necessary now, since many elite teams are still suffering without direction and continue to use crude integer scoring systems without following the best practices in any part of their process.

Reporting and Presentations

Reporting Guidelines When events have occurred requiring further explanation beyond dashboards, reports and presentations are required. Reports can vary from one-page summaries to extensive breakdowns of an event in ruthless detail. Reports currently are very important to explain why failure surfaced, but it could be a document that outlines the needs for building a program. No matter what the cause, reports and presentations have several characteristics in common that expands on dashboards, but include far more written text. A medical or performance document is very similar to a criminal investigation or a scientific journal, both sharing evidence and both showing what possible interpretation can be logically concluded from the data presented. Reports are usually in paper format, but PDFs and interactive ebooks are growing in polarity because of tablet use and the need to show video. Technology should only enhance the message, not provide an artificial degree of confidence to the reader. Conventional paper use does provide enough information when a report follows the guidelines of traditional approaches to sharing data. Reports should include original data by providing the raw data, without filtering the information in the conclusion of the report, in an effort to keep the integrity of the analysis. Visuals should be 2-D and not have ornamental displays. Tables and lists, along with timelines are far more useful than long paragraphs and excessive wording. Reports should have citations of research if needed, usually when a conflict of opinion is present, but testimonial type language is sufficient for most briefings. Longer reports should remember to review all of the information linearly and then conclude the document with a summary of the findings with a segregated professional option. If the report has collaboration, separate perspectives should be isolated in individual chapters or sections. Most reports fail because the information is limited from a recollection, instead of a detailed account from good record keeping and collecting essential data.

Presentation Guidelines

Delivering an effective presentation is important because most learners need a combination of both verbal and visual information. Ideally, hands-on is included when possible, but many informative versus instructional presentations are needed in elite sport. The same problems that occur in business or government plague elite sport, usually worse from the lack of experience or following the styles of other fields improperly. When coaches or medical staff think of presentations, our minds think of slides, versus delivering an interactive presentation of best practices. Presentations should be aware that slideware, such as Microsoft PowerPoint, Apple’s Keynote, and web programs severely handicap the message, as most practices model sales pitches. Reading off of slides, beautiful images without information, and excessive bullets all ruin the opportunity to engage the attendee and dilute the message. Sports performance and sports medicine should reduce slide totals, increase data display, include citations and written summaries, and provide a guided story of the events. High resolution infographics, detailed data displays in graphical form, and the right use of video and photos can dramatically enhance the message. The focus should be showing and not telling, since most presentations simply review what the audience sees instead of sharing what they don’t know.

Educational presentations need to know the difference between informative versus persuasive, since many educational conferences are disguised inbred cults that push an agenda or product like an infomercial. Speakers should be encouraged to show evidence by providing data charts in advance and review their interpretation of the findings. While many presentations are convincing and even moving, the purpose of educational conferences is to give a combination of information and experience, rather than promote bias and style. Smaller venues should focus on a balance between workshop time and instructor to student ratio, a difficult task when compensation and business models may not match the market value. Education requires the right set of moral values, as the new generation of athletes is dependent on the information known by the new generation of coaches and medical staff.

- Special Thanks to Freelap USA for the use of information from the Kinetics Manual