Maloney Performance

So, we’ve looked at the background behind the use of jump testing to monitor neuromuscular fatigue in part one and the use of the reactive strength index (RSI) as an assessment tool in part two.

In brief, the RSI shows some real promise as a relatively low-cost way of monitoring readiness, although other parameters may be more sensitive longitudinally.

This is all very well in theory, but how does it work in practice?

The aim of this article is to show you how I use jump-based monitoring with myself and my athletes.

Who do I use it with?

I use regular jump-based monitoring with only a very small percentage of my more experienced (in terms of either training age or competitive status) athletes. The bottom line is that unless the results would make a difference to my programming, it’s not worth testing. This only qualifies about 2-3% of my current athletes.

For the majority of athletes I still rely on feel to dictate the session. We have a plan in mind before the session and this will normally come with an intended dose. Generally if I’s a good day the dose is higher, a bad day the dose is lower. Not really rocket science.

An analogy

I think of the RSI as the cherry on the cake. This is a tool to fine-tune within-session programming and is therefore a strategy that few athletes need. Focus on putting the right ingredients into the cake first. Mix them well and bake it properly. Now for the icing. Then, finally, the pop the cherry on top.

What does RSI monitoring look like?

Following the pre-performance prep, athletes perform two sets of three drop jumps from a height of ~18 cm. Hands are positioned on hips throughout (see video).

The prep work will always have included a) landing focus elements, b) ankle stiffness elements, and c) global power/priming elements. These are all important factors to consider prior to testing as they demonstrate the potential to affect the RSI and therefore influence the reliability of your method.

How reliable is it?

If a test is not reliable then it’s meaningless. For the athletes we use the RSI with, we first establish a baseline over a period of two-three weeks.

• Within-session reliability

First off, we look at the within-session reliability over the three best jumps from the six jumps performed. Using just the best three helps to reduce some of the noise.

We typically see an average coefficient of variation (CV%) of somewhere between 1% and 3% after just a few sessions – meaning there’s about 1-3% variation on the same day.

My CV is just under 2%. Marwick et al. (2015) report ~3% in professional basketball players.

• Between-session reliability

If the RSI is a sensitive representation of fatigue then it would be expected to fluctuate a considerable amount over the training week and over the training cycle. Because of this, it makes determining a value for between-session reliability a little challenging. However, as we’ll start using the RSI during an out of competition period, we can try to get an idea of the reliability over a few weeks of fairly consistent GPP-style training to see how well it’s working.

My own RSI data

The figure below shows my RSI over the last six-seven months of training.

The blue markers represent the mean score from the best three jumps, the red markers represent the best score. The lines represent the four-point moving average.

What does it show?

It’s clear that the RSI certainly isn’t flat-lining, there are a large number of peaks of troughs as we move through the year. Even with just a quick eyeball of the graph, we can see these peaks and troughs follow a fairly predictable pattern, typically occurring every three-four weeks or so.

This mirrors my general training cycle of three weeks on, one week deload pretty closely – fatigue accumulates over the three week cycle and the RSI subsequently drop and then, following deload week, the RSI picks up again.

My own jump height data

I also monitor my own CMJ height along with my RSI, mainly as a general gauge of lower body power and ‘effectiveness’ of my current programme.

A single set of two maximal CMJs, with hands on hips, are performed after the drop jumps.

The case for RSI

Have a look at how the RSI and CMJ height compare. The RSI is definitely more sensitive to change. For this reason it’s probably a better choice if you’re looking to monitor the accumulation of fatigue over multiple training cycles.

However, I’ve found that when my RSI has really skyrocketed or plummeted, my CMJ score has tended to go with it.

So what about jump height?

If I’m going to use any parameter to adjust training load on a given then I’ll need to see a pretty decent change. And when I say decent change that doesn’t just mean anything above the ‘smallest worthwhile change’, I’m talking at least 10%.

With this in mind, at least from my own example, if I were only using this type of monitoring with as an indicator of ‘red-light’ sessions – times where the intended session needs to be changed substantially from the original plan- the CMJ would probably suffice.

Other options…

Would the broad jump do the same thing as the CMJ? Possibly, although it’s not something I’ve looked at. This may even be a more attractive prospect than the CMJ as it’s even easier to set-up.

In the same ballpark, could something like the 3 Hop Test do for horizontal jump testing what the drop jump does for vertical testing? Certainly an interesting thought if the SSC is as important as it seems to be.

Really interested to see what people’s thoughts and experiences are with this. Please feel free to pop or comment below or drop me an email.

References

Marwick WJ, Bird SP, Tufano JJ, Seitz LB, Haff GG. The intraday reliability of the reactive strength index calculated from a drop jump in professional men’s basketball. International Journal of Sports Physiology and Performance. 2015: 10: 482-488.

Last time out we looked at the potential for using jump testing to monitor neuromuscular fatigue. To summarise briefly, the countermovement (CMJ) jump shows strong promise as an assessment tool. The flight time to contraction time (FT/CT) ratio during the CMJ appeared to be the measure most sensitive to change following a fatiguing event.

What’s the problem with FT/CT?

To work out contraction time during the CMJ you’ll need a force plate. Do you have a force plate? If so, great. If not, we need to start looking at potential alternatives.

What is FT/CT meant to represent?

The FT/CT is representative of the movement strategy utilised to perform the CMJ. A longer CT (i.e. slower speed of contraction) indicates utilisation of a slower jumping which may indicate neuromuscular fatigue.

Enter the RSI…

RSI stands for reactive strength index and can be determined during a drop jump using a simple contact mat. The RSI is a function of either:

• flight time / ground contact time
• jump height / ground contact time

Personally, I’ll always favour the former. It’s possible to calculate jump height in a plethora of different ways so think it avoids a little confusion.

What does the RSI represent?

The RSI gives provides an indication of an athlete’s capacity to utilise the stretch shortening cycle in similar manner to the FT/CT. A longer ground contact time is indicative of a longer contraction time and, as with the FT/CT, highlights the utilisation of a slower jumping strategy.

Added impact?

An advantage the RSI has over the FT/CT is that it also demonstrates the capacity to tolerate impact loading, a parameter which also may be sensitive to fatigue. Indeed, a study by Nicol et al. (1991) published in the very first issue of Scandinavian Journal of Medicine & Science in Sports reported an increase in impact forces during a drop jump performed following a fatiguing marathon run.

Why is it a potential monitoring tool?

The roots of using the RSI as a monitoring tool can largely be traced back to an investigation by Oliver et al. (2008). Oliver et al. examined changes in the jump performance of youth footballers (aged: 15.8 ± 0.4) following a sport-specific exercise test. Squat jump (-1.4 ± 1.6 cm; P < 0.05), CMJ (-3.0 ± 2.9 cm; P < 0.05) and drop jump (-2.3 ± 1.7 cm; P < 0.01) performance were all impaired by fatigue, however, the only force variable to be affected was impact loading in the drop jump.

Is the drop jump better than the CMJ?

Two studies by Dave Hamilton may shed light on this question. Initially it was reported that CMJ height was not affected during a period of intensified completion in elite youth (aged: 14.4 ± 0.4) soccer players (Hamilton 2009a). A subsequent study in a similar population went on to demonstrate that drop jump RSI appeared to provide an indication of neuromuscular fatigue when examined on an individual, but not group, basis (Hamilton 2009b).

Who is using the RSI as a monitoring tool?

The popularity of the RSI as a monitoring tool hit new heights in 2012. The UKSCA conference of that year was littered with references to how this was incorporated by the English Institute of Sport, perhaps most notably in Dave Hamilton’s presentation on the physical preparation of the GB women’s field hockey team in the years leading up to 2012 (Hamilton 2012). The data he presented certainly appeared to back up his previous observations in youth soccer.

Is RSI monitoring viable?

Given the relatively low-cost and additional utility of jump mats, RSI monitoring is now a viable option for almost all professional organisations and a considerable percentage of sports teams.

But is RSI all it’s cracked up to be?

A new study to be published in an upcoming issue of the European Journal of Sport Science sought to evaluate both the short- and long-term potential of jump based monitoring. Oliver et al. (2015) evaluated the CMJ height, RSI, leg stiffness and perceived well-being of elite junior (aged: 16.9 ± 0.8) rugby players over a seven-week in-season period. Unsurprisingly, the authors reported that CMJ, RSI and well-being were all sensitive to detecting post-match fatigue. However, whereas CMJ and stiffness were deemed sensitive to detecting accumulated fatigue over the seven-week period, RSI and well-being were not.

It’s important to note that the RSI in the Oliver study was not measured during a drop jump, but during a series of repeated CMJs. This technique typically results in a less reliable measurement and may explain why such a substantial variation was observed in the study.

Hopefully the last two posts have given you an insight into the rationale behind using jump based monitoring. Next time out I’ll walk you through my own thoughts and observations. I’ll promise you’ll not have to wait as long as last time for this one!

References:

Hamilton D. Drop jumps as an indicator of neuromuscular fatigue and recovery in elite youth soccer athletes. Journal of Australian Strength and Conditioning. 2009: 17: 3-8.

Hamilton D. Explosive performance in young soccer players during several games in succession: a tournament scenario. Journal of Australian Strength and Conditioning. 2009: 17.

Hamilton D. The Impact of Monitoring Strategies on a Team Sport Through an Olympiad: Physical Development, Taper & Recovery. UKSCA Annual Conference. Royal Holloway University, London, 2012.

Nicol C, Komi PV, Marconnet P. Fatigue effects of marathon running on neuromuscular performance, I. Changes in muscle force and stiffness characteristics. Scandinavian Journal of Medicine and Science in Sports. 1991: 1: 10-17.

Oliver J, Armstrong N, Williams C. Changes in jump performance and muscle activity following soccer-specific exercise. Journal of Sports Sciences. 2008: 26: 141-148.

Oliver JL, Lloyd RS, Whitney A. Monitoring of in-season neuromuscular and perceptual fatigue in youth rugby players. European Journal of Sport Science. 2015: 15: 514-522.