A Certified Athletic Trainer at a division I football program (who was happy to share their story but wished to remain anonymous) spoke to IMeasureU about how the medical department found an objective way to measure their teams training load, which had previously been tracked subjectively. Initially they wanted to monitor athletes who were rehabbing from long term injuries and slowly transition to healthy athletes as well. He turned to IMU Step to fill this gap in provision.
“We had an aim of tracking our injured athletes to get a deeper understanding of what they were doing during their sessions,” he explained. “Thankfully we have an excellent strength and conditioning staff here and anecdotally we knew they were doing a great job but we wanted some numbers to put to that. We try to get the athletes in a position to be passed over to [the strength staff] as soon as it is safe because we see it as a valuable step in the RTP (return to play) process.”
“We were able to get the IMeasureU team in for some benchmark testing through the new service they are now offering to organisations. That led us into being able to get funding to purchase 8 sensors. Due to Covid it was a little harder to start implementation, but since starting in the spring it’s been fantastic.”
The right fit
The Athletic Trainer and other staff decided not to go down the route of GPS (global positioning system) due to a number of factors, mostly price and the fact that their practice facility was indoors. Instead, they collected subjective data to understand the demands being placed on their athletes.
“Unfortunately we’re at an institution that doesn’t have unlimited resources. Due to these constraints, we also don’t have more global measures of workload like GPS. We’ve always tracked training load via time and subjective measures and used that to identify which activities were more stressful than others.”
“We haven’t gone down the GPS route in the past because of two reasons; one, the amount of time we actually have with our athletes, and two, we are often indoors due to the weather. The weather is a huge limitation when looking at GPS because it limits the metrics we can collect indoors. IMU Step doesn’t have these limitations but still gives us incredibly actionable data.”
Getting benchmark data for the rehabilitation process
Getting athlete baseline data to use during the rehabilitation process was something that he and the team prioritized with a new system. This would enable them to work backwards from what ‘healthy’ looked like. Ideally that would mean getting information on each individual’s baseline and that’s something that wasn’t possible due to the amount of athletes. Instead they grouped players together by size and position to get some data that they could use.
“We have almost 1,000 athletes on campus and 200 in the football program. If we had an injured defensive lineman, we wanted to have some objective data from when someone in that position group was fit so we can work backwards during the RTP process. We wouldn’t have been able to do this without IMU Step.”
“We hadn’t collected athlete baseline data before this spring so unfortunately didn’t have data on guys before they were injured. However, the testing session with James and Blake this summer was an opportunity for us to get a larger group of athletes baselined during a linear running training session.”
He and his colleagues had identified a linear running test that the football athletes were familiar with already and decided to use that as a way to benchmark them.
“We created a standardised run which was 80% self selected speed for 100 yards and they did 17 repetitions. We had a time goal for each group depending on position. We had a big group which was primarily offensive and defensive line, a midsize group that’s linebackers and full backs and then we have a skill group that’s the smaller faster guys. They ran these tempos in about 14 seconds. We chose this as it’s easier to run and everyone has done it before. In the future this will be used for baselining.”
From that initial benchmarking, he was able to identify some interesting asymmetry data that can be used immediately to try to mitigate any future injury.
“As you can see from this report, athlete 1 was over 18% asymmetrical to the right and athlete 0 was nearly 12% asymmetrical to the left. These are not numbers that are going to guarantee that these athletes will get injured but having set a threshold of 5%, these guys were on our list to keep a close eye on.”
You can also see above that player 9 had a 10% asymmetry to the left but also below that they had the second highest total impact load and impact load/minute. Again, that athlete was on our list to do more investigation into.
The table below shows each tempo run in detail, giving insights into how asymmetries progressed over time allowing the staff to identify which athletes started to break down due to fatigue.
Tracking long term rehab athletes
Besides the benchmarking, the staff were interested in tracking their long term rehab athletes on a daily basis to see what impact the program was having.
“This is the first time we’ve really been able to collect objective data so we looked at three of our long-term rehab athletes,” he explained. “It’s the first time ever we have been able to assess whether they are on the right track to return or not. Two out of the three were doing really well but one was showing that he wasn’t tolerating the load very well. That had been picked up by the athletic training staff but his IMU number definitely backed that up. We were seeing his asymmetry get larger over time instead of smaller and that helped us identify how we were going to change his program.”
“As the two athletes went through their rehabs without any problems, we tracked them using IMU Step as they transitioned back to full practice with the team. We wanted them to stay under a 5% threshold which is exactly what they did. The third athlete who’s rehab hadn’t gone as smoothly experienced a little bit of knee pain and wasn’t moving quite as well. The data from IMU Step again backed that up and gave us confidence so we used the crucial data as part of our decision making process. We were able to confidently return that athlete to the performance staff to do similar sort of training activities but without the eyes of the coaches on him and in drills with the team where he wasn’t competing. We decreased his volume as that was clearly what he was struggling to cope with. He was still lifting with the team and still integrated as much as possible. After two weeks of slow integration, he is now doing more in team practice.”
He and the team have plans to build out the benchmarking test as well as using the sensors to collect data on tests they already currently do in the athletic training room. Using IMU Step has provided objectivity in an environment not blessed with unlimited resources or unlimited time.
“Going forward we’d like to be more specific with our choice of benchmarking activity. We would like to incorporate more lateral movements such as the 5-10-5 shuttle which will enable us to compare some more dynamic movements post rehab.”
“Covid did provide some disruption which slowed down our ability to understand which metrics we should be spending our time looking at but now we have our dashboard nailed down we have found the IMU Step data to be incredibly helpful.”
This case study builds on concepts we’ve explored in-depth at IMeasureU. Follow the links below to learn more –
Practical Examples of Using IMU-Step to Modify Outcomes: Asymmetry and Impact Load in the Real World – a webinar with Andrew Gray
Understanding External Biomechanical Load During ACLR Rehabilitation – A webinar with Mark Armitage
Set Up for Success with Inertial Data – A Case Study with the Wests Tigers
Have an injured athlete? Get in touch with us and ask about a free demo of IMU Step to see how we can help your return to play.