I've been around long enough in professional strength & conditioning to have seen numerous different approaches to preparing athletes for competitive sport.
Do you train lower body bilaterally or unilaterally?
Do you train running capacity long to short or short to long?
Without question there is more than one way to "skin a cat" and there are many different types of "cats" (athletes) in the world. I always encourage professionals in the S&C field to develop and regularly refine their own training model. Despite any differences in theoretical or philosophical approach to your training model, there is one thing that binds us all...data.
Data is the one true leveler. Objective data is the single most critical tool in an S&C coach's "bag of tricks". Data allows us to answer four critical questions with respect to the athlete:
Where are they coming from?
Where are they now?
What barriers block the path forward?
How do we plan to get to their destination?
If you can clearly answer these questions, you can then apply those answers to your training model and develop a systematic plan for the progression of your athlete…and make no mistake, collecting data about training is just as important for the guy at the local gym or in his garage as it is for an athlete. Quantification of training allows us to develop plans to improve.
Over the years I've seen everything from coaches who train for tests so their data looks fantastic for the team's head coach, all the way to coaches that effectively don't test so they keep everybody in the dark. While neither of these approaches contributes to long term development of the athlete, somewhere in the middle is the answer.
At the TEDX conference in Sydney 2013, Simon Jackman (political scientist) presented on what he called the Democracy Data Revolution (www.youtube.com/watch?v=INf5u29n-5Q). In his presentation he made a comment that I felt was tailor made for the S&C industry…"In God we trust...everyone else must bring data". I think this statement sums up the nature of S&C coaching. Data gives a clarity to ensure that we can define without question "why" we chose a particular path at any given time for our athletes.
Personally, from a testing perspective I adhere to a philosophy espoused by coach Kelvin Giles…"Training is testing - testing is training". There is nothing I hate more than having to put training on hold to conduct testing. Further, investing in a single testing opportunity that is then compromised by absences or poor performances based on any number of psychological issues ends up leaving "black holes" in your data that doesn't in any way help your end game.
My preference is to measure as many variables as possible as frequently as possible to give me clarity as to where my athletes are at at all times. This then transitions from not just assessing performance, but more specifically to assessing the adaptation of the athlete to the prescribed stimulus. From my perspective understanding an individual athlete's adaptive cycles and capacities is more critical to my programming than simply knowing their current performance cabability.
Now, measuring as many variables as possible as frequently as possible, is quite easy for me to say sitting behind a vast array of technology in a professional sporting environment. Wrong…the technology you have at hand is incidental. The philosophy is what is critical. I work on a system of Lead Indicators. By definition, Lead Indicators are measurable factors that change before the dependent variable (in our case performance) begins to change. A Lead Indicator is in practice data points collected on a regular basis with limited time between data collections that allow you to see "trends" developing. The assessment of a "trend" allows you to make critical tactical changes in programming where required in order to adjust to or sustain the trend as is required. This is opposed to a Lag Indicator which by definition identifies changes once the dependent variable has begun to follow a trend.
For example; assessing body composition by DEXA scan is a Lag Indicator while assessing skinfolds, body mass and intern Lean Muscle Mass (by calculation) is a Lead Indicator. Small changes in SF measurements over a number of weeks will alert you to a trend developing while the DEXA scan will confirm the observation.
In practice I have found that the most effective way to develop a Lead Indicator system is simply to identify the data that you most value with respect to the abilities or performance you are trying to bring up in your athletes, then ensure you measure it as regularly as possible to assess the development of trends. For technology enabled environments this is done with equipment like GPS, accelerometers, linear rate encoders and force plates. For environments that are limited by technology you simply need to think around the data collection issue to find what you can assess.
Here's a number of Palaeolithic (to steal the popular nutrition term) Lead Indicators and ways to measure them.
Power - mark heights on a Smith machine using tape so that jump or throw heights can be assessed visually. This logic also works in a squat cage - use a piece of elastic tubing (Theraband etc) from the front to back of the cage again to create a height gauge, simply adjust up and down to determine the maximum jump or throw height. While power can't directly be assessed, improved jump/throw height at a given load is indicative of improved power.
Running Capacity - develop a "test set" that can be used on a regular basis to assess progression. It can be as scientifically accurate as you like. The most important thing is that it is repeatable. Running sessions based on the work of Veronique Billat and Gregory Dupont (check future posts) are ideal for use with large groups as athletes can be very easily moved up or down groups based on their observed performance.
Remember the most important things about data;
Be consistent in how you measure
Measure on a regular basis
Measure what you value
Ensure what you measure helps your athlete improve
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