Join Catapult’s Kyle Stobbs as he talks through how to use Catapult technologies to mitigate the risk of injury.

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Hello everyone, we’ve got a question here.

One of our users asking; how can

I use my devices for injury prevention?

Although we don’t claim to prevent injuries, we

can provide some insight into some ways to

mitigate avoidable injuries such as muscle strains.

So let’s jump right into it.

The big question we get from our users

and how we can do this is by

using the application of loading concepts like this

training stress balance involving the acute chronic workload

ratio and the application of field screening drills.

So in this original concept, Hulin and

colleagues came up with the original training

stress balance concept using cricket fastbowlers.

The concept recommends avoidance of spikes in training

load over an average load between a 7

day period and a 28 day period.

The 7 day period is the acute load.

The 28 day period is the chronic load.

As the ratio of these two variables increase, the

likelihood of injury also increases, which is what we

see in the graph on the right here.

And the acute chronic workload ratio works best on

the variables such as total distance or high speed

distance as a measure of locomotive load, PlayerLoad

as a measure of mechanical load, and heart rate

exertion as a measure of an internal load.

This is a case study showing the soccer

player’s data leading up to a hamstring injury.

Here the user is using PlayerLoad.

Chronic load was displayed on the area line

and acute load is displayed as the bar.

And as you can see there is jumps and

spikes leading up to 1.4, which is out of

the sweet spot shown on the previous slide.

Now for Vector Core Plus and Vector Pro users,

they can utilize the acute chronic widget within OpenField.

Now some considerations if you’re interested in

applying the training stress balance concept, you

need to be mindful of these.

The concerns about the validity of the mathematical

calculation used for the acute period using both

seven day and a 28 day calculations.

If you’re interested in looking more into this, then

I suggest you look at the ‘Un-Coupled’ approach.

You may also be interested in look at the

exponentially weighted model which adapts the original concept by

adding a decaying effect so it places extra emphasis

on the sessions closer to the present day.

Lastly, and most importantly, it doesn’t take into

account individual differences, so it assumes that everyone

reacts the same way to the external stimuli.

So screening drills are the second approach

which I outlined at the beginning.

Using fingerprint drills are a way of testing

our players outside of a lab environment.

To implement these into monitoring practice, you can either

ask a coach to incorporate them into the session

plan or use an existing activity which already takes

place, such as lapse around the pitch.

Ideally, this should be performed at the beginning

of the session to adapt load for individuals

for the remainder of the session if needed.

Once these drills have been performed, you can

tag these in your respective Catapult system.

You will be able to generate norms and

benchmarks for each player to compare against.

System permitting though, try and look at the live

data and promote conversation with players to adapt individual

loading. The reason we use PlayerLoad as

an inferred measure of fatigue is based on the

research of Akenhead and colleagues.

When conducting a repeated sprint protocol, they saw

decreased sprint performance, which is an increase in

sprint time, came with a decrease in player

load caused by decreased vertical stiffness as well

as increased ground contact time.

Such changes can also be observed

in the fingerprint drill data once

normal player load values were established.

If users have access to heart rate data,

they should also look at the internal measure

of load and using heart rate exertion.

This can also be shown as a ratio by

dividing by total distance or player load, higher values will

denote a great internal cost to the athletes per

meter or per player load unit, respectively.

Finally, running symmetry is also a powerful tool for

injury mitigation as well as return to play.

Running symmetry in OpenField is a measure of load

imbalance between left and right leg when running.

However, this is only available for Vector

Core Plus and Vector pro clients.

It’s important to note that players will rarely

have a perfect balance between left and right

foot, so we should look to build norms

for each athlete using a consistent protocol.

Once we have these references, we can look

at differences compared to the norm and

consider standard deviation in a running series.

So thanks for listening.

I hope you found that useful.

Please continue to check in with the

Unleash platform for more content like this.

I’ll see you next time. Bye.