“What’s a good number, Coach?” This question might seem simple, but the answer is often complex. Early in my coaching career, I didn’t always keep meticulous records. Sure, I tracked the basics like load, sets, and reps in real-time, but I failed to maintain comprehensive historical data. Over time, I learned that tracking longitudinal data—data collected over long periods—provides the most valuable insights for performance coaching.
As John Wooden once said, “My record keeping was comprehensive but really no different from that of a banker who accounts for every penny and can show you the records of transactions going back years and years.” Keeping diligent records is crucial for understanding trends and making informed decisions. Here’s why and how you should do it.
The Importance of Longitudinal Data
Longitudinal data is at the top of the “Evidential Substantiation” list for performance coaches. It helps you track the progress and performance of athletes over time, providing a comprehensive view of their development and the effectiveness of training programs. This type of data is particularly important because, in sports science and coaching, our sample (our team) is essentially our population.
What Kind of Records Should You Keep?
The type of records you keep will vary depending on your situation, context, and environment. At the professional level, Athlete Management Systems (AMS) can store and display data to key decision-makers and players. In the private sector, budget constraints might require alternative methods. Regardless of your resources, it’s essential to have effective tools for data collection and communication.
For our teams, we use three main dashboards:
- Team Dashboard (For the Coach):
- Top 5/Bottom 5 performers
- Positional averages
- Team averages
- Customized date ranges
- Personal Player Card (For the Player):
- Key Performance Indicator (KPI) tracking
- Performance trends
- Radar chart comparing the athlete to team standards
- Longitudinal Data (Internal Record Keeping):
- Team and position performance over time
Let’s focus on the third type: Longitudinal Data.
Using Box and Whisker Plots
When displaying longitudinal data, Box and Whisker Plots are incredibly effective. They provide a clear visual narrative, whether comparing teams or positions over time. Here’s a quick guide:
- Box and Whisker Plot Overview:
- Box: Represents the middle 50% of the data set (interquartile range).
- Middle Line: The median of the data set, unaffected by outliers.
- X: The mean of the data set.
- Lower Whisker: The bottom 25% of the data set.
- Upper Whisker: The top 25% of the data set.
- Outliers: Marked with dots above or below the whiskers.
- Interpreting Box Plots:
- Smaller boxes indicate less variability in scores.
- Longer boxes indicate more variability.
- One box higher than another shows differences between groups or positions.
- Different median distributions help compare groups/positions.
Here’s how to create a Box and Whisker Plot in Excel:
- Enter your data into a spreadsheet.
- Select the data range.
- Go to the “Insert” tab and choose “Box and Whisker Plot.”
- Customize the plot as needed to best display your data.
Conclusion
Collecting and analyzing longitudinal data is essential for answering the question, “What’s good, Coach?” Metrics and technology might change, but the need for diligent record-keeping remains constant. By managing, collecting, and communicating data effectively, we can provide better insights and guidance to our athletes, helping them reach their full potential. Remember, the best answers come from the best data, so keep those records comprehensive and up-to-date.