Training, Racing & LCHF Fueling For Skating And Endurance Sports
Any sport where gains can be made through equipment is potentially a slave to technology and innovation…
This is true in the world of inline speed skating, where size matters when it comes to wheels (bigger generally means faster), and the recent introduction of the 3x125mm setup has firmly set the cat amongst the pigeons and reignited the equipment arms race.
3x125s were introduced by Powerslide Racing as far back as 2012, and are being touted by some as the next move in a logical progression that has seen the sport go from 5×84 to 4×100 to 4×110 within the last 15 years.
Of course, the claim is that 125s are superior to the current 4×110 setup favoured by most speedskaters – otherwise why would anyone bother? However, 3 years after their introduction and despite all the promise, it’s fair to say that the reception has been pretty lukewarm and the uptake poor – most skaters are so far unconvinced by the advantages of 125s in relation to the sheer hassle of changing setup. Faster they may be on paper, but as we all know, real world is what counts, and frankly, most of us think that speed skating should be more about the skating, and less about the equipment. Accordingly, 125s are also banned from many events by some organisational bodies, although Powerslide are constantly lobbying to get this overturned.
Designing a skate/frame combination to effectively accommodate 125 wheels is no trivial task – larger wheels necessitate a higher deck high (the actual height that your foot from the ground, and this brings additional problems of ankle control). With the trend in speed skate boots being lower and lower, this does not go well with a wheel setup that suddenly adds 5-10mm to your overall deck height. Wibble wobble.
That said, I feel that a large part of the resistance to 125s is simply because nobody is sure quite sure how much advantage is potentially on the table. Some will say that Bart Swings dominated the last Worlds using 125s, so they are undoubtedly the best option, while others will say that Bart could probably win on hockey skates, so it doesn’t tell us anything. The truth is somewhere in the middle. Discussions on online forums often evolve along the lines of… “Skater A wearing X beat skater B wearing Y” as means of equipment comparison; I hope you’ll agree that this is not a scientific or even sensible method of comparing anything except the skaters in question.
Any scientist worth their lab coat knows that if you want to be taken seriously by your peers then instead of just eulogising about the manufacturer’s claims, you undertake a Randomized Controlled Trial (RCT) study designed to assess and evaluate the effecacy of an intervention.
A well designed RCT selects suitable test subjects for inclusion in the study, test baselines for all subjects, then assign test subjects to either an intervention or a control group, and retests all subjects in both groups while holding as many variables constant as possible to observe and finally summarize before vs after results, drawing conclusions of the intervention from the data produced.
With some RCTs it’s possible to do them double-blinded (you don’t know if you getting the intervention or a placebo) , and to eliminate any possible they can also be performed two-way (the entire experiment is repeated with the two groups swapped around; original intervention group is now the control group, and original control group now gets the intervention) to eliminate any possibility in selectional bias when assigning the test subjects to their respective groups.
In designing a “125mm vs 110mm wheel performance comparison” study, it’s not possible to do any RCT double-blinded (you know what wheels you are skating on just by feel). However, there is no reason why it shouldn’t be done as a two-way study.
Here is the general framework that should be followed:
So how would we design our study? Here’s how I would address each of the points…
We are interested in finding out if 125mm wheels are of benefit to reasonably well training speed skaters. Define that how you want, but we are not talking about hockey players, street skaters or derby players. Male AND females? You betcha.
Selection of study population-
Test subjects should eligible for selection if they have posted a marathon time of 1h20-1h30 in the last 12 months (or 1h25-1h35 for females) with experience of racing on 125mm wheels. A suitable number of test subjects that meet these criteria should be selected for the study – let’s say 10. Test subjects should have previous heart rate data available to accurately judge maxHR.
Obtain Baseline measurements-
All subjects should be baselined in a well designed submaximal time trial on a 110 setup. I would propose a submaximal track-based time trial – constant skating around a track holding 75% of maxHR for 30 minutes. Total distance for each skater is recorded as baseline measurement. Let’s say the test population as a whole managed to cover 10,000m on average during the time trial.
Test subjects are then randomly allocated to either the control group (N=5) or the intervention group (N=5). Individual subjects’ baseline data can then be aggregated to provide the group baseline data. The random nature of the group assignment might have nudged some of the faster skaters into one group or the other, but that’s OK as we will be able to aggregate the performance for the whole group. For example, the control group might have an average time trial distance of 10,100m per skater vs 9,900m. for the intervention group. The selection of the study population should have eliminated vast disparities.
Control / Intervention-
After a washout period (designed to allow setup adjustment for the intervention group), the 30 minute submaximal time trial is repeated for all subjects in both groups. Individual performances are then recorded, and the group’s aggregate performance recorded. Heart rate data should be recorded in all instances to ensure that any performance difference arising from greater effort can be accounted for.
“After” performance is recorded for both all subjects in both Control & Intervention groups.
In the control group there should be no statistically significant performance difference because nothing should have changed- if there is any noticeable difference then it indicates that some other unforeseen variables have not been accounted for, and that no conclusions can be reliably drawn from the results of the Intervention group. If the control group’s average “Before” performance was 10,100m then I would expect that their “After” performance would be very close to this also.
Provided that the control group exhibits no strange results, then the any performance difference of the Intervention group can be reasonably assumed to be reflective of the difference made by the intervention. If the Intervention group’s average “Before” performance was 9,900m and increased to 10,050m after the Intervention, we could confidently say that, on average, the 125 setup provided a (10050/9900 = 1.01515) 1.52% increase in performance.
As well as both group’ average performance Before vs After, other statistical measures such as dispersion measurements can also be calculated and compared. It may be that an increase in the dispersion in the Intervention group indicate that not all skaters are able to gain the same benefit from the setup change, and that some skaters might stand to benefit more than others by going to 125s.
The trickiest part of designing this study is to ensure that all test subjects are equally adept on both 110 and 125 setups when performing the time trial. You can’t just pull a bunch of skaters who’ve never skater 125s before off the street and expect them to automatically be able to make the most of a 125 setup.
That is why the study population should only include skaters who have experience with both 110 and 125 setup in the last year, and why there should also be a “washout” period between the Before vs After time trial, to allow for adjust in the Intervention group so that their skating form and technique has a chance to adjust to the change of setup.
As stated before, this study should repeated with both groups swapped around to eliminate any possible selection bias when assigning test subjects to their groups.
A more complete picture of the performance difference could be also be obtained by repeating the time trial at different intensities – the trial could be repeated at 65%, 75% and 85% of maxHR for all subjects. With this data, it might be possible to see if any performance advantage with a 125 setup is more or less advantageous at higher intensity, or if the any performance difference is constant at all intensities.
so far, I don’t personally know any skaters who have switched to 125s, and I can understand why people are reluctant – much more so than when moving from 100s to 110s. It’s a big jump, and not enough people are skating 125s to be able to form a good subjective idea of any advantages they offer – a chicken and egg situation.
Without any RCT studies to back up the claim being made by those pushing 125, we are left to word of mouth, anecdote, and marketing hype spearheaded by elite skaters (where the rules of engagement are different to us mere mortals) to try to determine their effectiveness.
In most sports that take themselves seriously (noticeably cycling), they jump all over the RCTs as a means to prove and promote the constant innovations that we see in those sports. While not without its own problems of poorly designed and biased studies, at least it shows that they’re being serious about how they bring it to market.
So howabout it, Powerslide? If you want to push 125s, at least give us a reasonably well controlled study that backs up your claims. As I’ve just demonstrated, it’s not hard to do at all.
That Bart is kicking ass on 125s is not a solid or objective argument.