How to Get More Consistent Data into Your AMS

by Fusion Sport
 | 14th July, 2021

by Kim Gilmour 

An athlete management system (AMS) like Smartabase can help a team make better, timelier, and more decisions that enable its athletes to perform better, recover fully, and become more resistant to injury. But for an AMS to be deployed effectively, it must be regularly ingesting consistent and accurate data.

Good compliance demands great leadership, and teams can leave a lot of potential on the table because the performance staff doesn’t give athletes or coaches a clear “why” to get their full support for consistent data collection.

Whether an AMS initiative sinks or swims ultimately comes back to leadership and communication. The performance team needs to get coach buy-in around the collection of certain data sets before beginning to collect them. If the coach doesn’t understand the purpose, he or she won’t encourage their athletes to comply, and will also likely refuse to oversee any data gathering that he or she is supposed to be responsible for.

Below, we outline how a performance staff can create the necessary level of engagement to ensure the AMS is being utilized effectively. We’ll also share some best practices from pro and college teams for improving data consistency and accuracy which will lead to better outcomes.

 

Getting Coach Buy-In

When a performance expert starts talking jargon and using a string of acronyms, coaches’ eyes glaze over – particularly when they’re “old school” and, perhaps by their own admission, not very tech savvy. Instead of starting with numbers, lead with the head coach’s big picture goals, game plan, and principles of play. It’s all very well getting athletes to jump higher and run faster for longer, but such performance outputs can’t exist in isolation and must be put into the context of the coach’s overarching plan and goals for the team.

Once a performance staff understands where the coach is trying to take their players, they can begin working backward to determine the physical qualities that need to be developed to achieve these aims. They can then pinpoint the metrics that will indicate progress in each of these areas and decide which technologies best measure them. This determines the kind of data sets that will be fed into the AMS once tools like force plates, GPS units, fitness trackers, and so on are connected.

 

Show (Don’t Just Tell) Why Consistency Matters

Body composition, sleep, wellness, and other information is only actionable if it’s put into the AMS regularly. Unfortunately, athletes often enter their data in a haphazard fashion. Communication and leadership is required to help coaches and athletes understand why entering consistent data is truly in their best interests.

Inconsistent data entry can be because of lack of attention or follow through, but also because athletes tend to enter only “good” or “bad” data – like when they get 8+ hours of sleep or are particularly sore in one muscle group. If the performance staff doesn’t know their normal values, the data becomes much less useful. These inconsistencies can lead to the performance or coaching staff making ill-informed decisions based on incomplete information.

For example, an athlete only enters HRV/sleep data when they’re feeling poorly recovered, so their “normal” levels are skewed low, and it looks like they’re ready for training when you’d expect them to need a lower intensity day.

On the flip side, when the team is traveling, the performance team might expect sleep disruption to have taken a toll. But with inconsistent data, what they might not see is that a certain athlete has been sleeping inadequately for a month and not only are they poorly recovered from taking a night flight (which we’d expect), the issue has been compounding for an entire month. In this case, the performance team is likely to miss the opportunity for more extreme sleep and recovery interventions.

In addition to providing specific and relevant examples to show why consistent data entry is critical, presenting the data graphically in real-time engagement and compliance dashboards helps motivate naturally competitive athletes and coaches.

For example, Smartabase can be configured to highlight the name of any player who hasn’t entered their daily data in red. This not only gives the staff a heads-up, but also fosters an atmosphere of competition and accountability among teammates. If everyone can see who has done what’s required and who hasn’t, it facilitates a culture of compliance enabling athletes to hold each other accountable and own their own data and success.

 

Making Data Collection and Presentation Simple

In addition to using certain features of Smartabase to encourage shared responsibility among players and coaches, the performance staff can also increase compliance and consistency by creating daily routines.

If every player knows that the first thing they do when they get to the practice facility is go to a certain corner of the weight room to weigh in using a kiosk, they’re much more likely to do it regularly than if the process is haphazard.

Smartabase can automatically push notifications to players’ phones to encourage them to enter data and complete regular wellness questionnaires, encouraging compliance. This all comes back to setting expectations and letting athletes know what they’re supposed to be doing, when, and how.

In addition to having a routine, limiting the amount of data and the time it takes to enter that data increases players’ and coaches’ compliance. With already packed calendars and long days, the last thing they want to do is spend hours each week inputting mountains of data.

To achieve this, using your AMS to automate data collection from the right inputs is key. The performance specialists overseeing this must ensure information gathering is reduced to the bare minimum to avoid player and coach frustration, which will eventually lead to non-compliance.

At the other end of the process, the data presented to athletes and coaches needs to be as simple and intuitive as possible. Using Smartabase to simplify data by displaying it in visual forms via charts, graphs, and composite scores (like 87 out of 100 for sleep quality or seven out of 10 for muscle soreness) will make it easier to understand and interpret. Such visual displays can also act as a conversation starter as the performance staff educates athletes on what the numbers mean and how they can use them to inform adjustments to their training and recovery. Course corrections driven by the data can easily be tied back to the “why” behind the numbers and the team’s goals.

For example, if a player’s force plate measurements consistently decline over the course of a week and their recovery data also takes a nosedive, the performance staff might decide to reduce the intensity and volume of their training in the remaining days before the next game so that they feel refreshed and ready to go when they take the field.

The buck stops with the performance team when it comes to making an AMS implementation successful. But as we’ve just explored, doing so requires a true group effort characterized by strong leadership, clear and open communication, regular routines, simplicity, and consideration for coaches’ and athletes’ busy schedules. If these pieces are in place, data accuracy and consistency will increase, leading to improvements in both performance and recovery outcomes.

 

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