So, you have a player who is not performing as well as you’d like, and it’s frustrating. They are among your most talented players, but they just don’t get it done.
You have your own theories as to why, and over time you convince yourself you are right – he’s just lazy, he’s too slow, he’s not aggressive enough.
But what if you are wrong? What if there is a simple explanation that neither you nor the player have considered? What a waste that would be.
“People make choices based on what they know, and if they don’t have all the information, they can’t make the best choices,” says Darcy Norman, AS Roma’s director of performance and a DRIVN user. “Collecting data helps you make a more informed decision.
“Using data to get data gives you a better opportunity for learning,” Norman adds. “You are getting information quicker, and that allows you to ask better, more informed questions, which gets you data which allows you to ask better more informed questions. All that allows you to get to the root of the issue.
Norman uses an approach called Differential Diagnosis when collecting data, and he uses DRIVN to do it all. Any performance problem a player is encountering can be diagnosed using data Norman collects and charts by using DRIVN’s Trackers.
“What you should collect should depend on what you want to know, and it can be anything. An example is self-evaluation of the player so you get a sense of they think they are at,” says Norman. “You have your opinion of where they are at. Between those two pieces you can see if both groups are on track.”
When there is an issue that needs to be solved, Norman diagnoses the problem to determine the factors that are holding the player back? From there, he can systemically get to the root of the issue. The information collected is more valuable, he says, when you are able to compare it to other information you have collected on a player.
“Once you get one piece of data, then you are using other pieces of data against that data to help you differentially diagnose what the limitation is so you can address it,” says Norman.
Much of the data he needs has already been collected in DRIVN through simple fitness and strength tests, or performance-related questionnaires on fatigue, nutrition.
Here’s an example. The old saying that you can’t coach speed, while seemingly true for a long time, has been proven to be false. With the proper tests and by collecting the right data, speed can improve.
“Maybe you want to know why a player is not fast, so you measure their speed. That will tell you if they are fast or not,” Norman says. “Then you have to ask how come they are not fast, so you measure their power. Then you think, okay, they have great power, they should be fast. If they have great power but are not fast, then you know the factor is technique. They need technique training to express their power.
“Or let’s say you have a player who is not fast and they are not powerful,” Norman continues. “The next thing is to measure them in the weight room and see if they are strong. If they are strong relative their age group or size category, you know they have to work on their power training. If they are not strong, they need to spend more time in the weight room and that will improve their speed.
“On the flip side, if they are fast but not strong, you know their potential upside is much better because if they are as fast without being strong, they probably have very efficient technique. If you can give them more horsepower in their engine they will be much faster.”
Norman believes anyone – whether its AS Roma or the U14 Koala Bears — can collect essential data
“DRIVN makes it very simple because everyone, all the players, can be responsible for their own data, or the coach can enter in data for each player,” he says. “Then you have that data in one place that you can always reference. With the Trackers and the Data Sheets in DRIVN, you can look at that data and refer to it any time to you have an issue.
“DRIVN makes is super-efficient and easy,” says Norman. “Then with the more data you collect, the better choices you can make. You get more insight into the total picture. Once you get one piece of data, then you are using other pieces of data against that data to help you differentially diagnose what the limitation is so you can address it