Tritionwear Race Analysis: 2018 Commonwealth Games Men’s 100 Fly

TritonWear and SwimSwam bring you the best in swimming race analysis for the 2018 Commonwealth Games. With the power of TritonWear, you can access 12+ metrics for all athletes simultaneously, display the results in real-time to unlimited screens on deck, and review later in an easy to use interface for monitoring progress and identifying trends over time. See all Tritonwear Race Analysis here.

The men’s 100m butterfly marked South Africa’s Chad le Clos’ third gold of the meet, with him
winning all of the butterfly events. He smashed his own Commonwealth Games record from
2014, and swam half a second faster than he did at the 2016 Olympic Games in Rio. This win
also makes him the first man in history to swim in 3 consecutive games, winning gold in 2 of
them…

Le Clos took the early lead off the breakout. England’s James Guy was not far behind, and
though not as proficient in underwater technique, he managed to match le Clos’ speed on the
first 50m. He used a faster stroke rate to catch up to le Clos’ stronger strokes and turn a mere
four hundredths of a second behind. However, le Clos’ powerful underwater once again gave
him the advantage, as he remained underwater for 1.6s longer, and surfaced a half body length
ahead of Guy. This time, Guy’s strokes and speed were not enough to fully close the gap. Their
stroking speed decreased by the same rate, and le Clos’ stroke efficiency suffered a bigger
decline off the turn, but the lead he gained off the breakout gave him enough distance to finish
more than half a second ahead.

Overall, le Clos’ speed and stroking metrics at the Commonwealth Games saw great progress
from his performance in Rio. The only metric improvement he missed was his turn time. He
transitioned off the wall almost two tenths of a second slower, but made up for this deficit with
stronger and faster strokes.

His stroke count per lap remained exactly the same in both competitions, but he generated
slightly more distance with each pull on this meet. The marginal increase in DPS while
increasing speed, meant he logged in higher stroke index numbers, translating to better stroke
efficiency. This efficiency gain could already lead to cutting down his time, but the progress in
his metrics did not end there.

Not only were his strokes more powerful and efficient; he also produced them at a faster rate.
This is the dream combination: increasing BOTH stroke rate AND DPS for maximal speed
gains. On the first lap, he took each of his 17 strokes 0.04 seconds faster than he did in Rio.
And although his stroke rate was less consistent and had a larger decrease on the way back as
he began fatiguing, it was still faster by 0.02 seconds per cycle (s/cycle). All these
improvements contributed to his lower splits and a faster overall time. If he can make this type
of improvement in under 2 years at his level, imagine what you can do!

Key Takeaways

Le Clos’ performance highlights the importance of developing individual metrics without
sacrificing another, but more so the difference it can make when they come together. Small
improvements in each add up to great progress. Le Clos improved his stroke speed without
compromising stroke efficiency or power, and vice versa. Instead, he supplemented the

increase in stroke rate with an increase in his DPS and stroke index, which ultimately resulted in
a significantly better race performance.

To dive into the numbers of each athlete yourself, use the interactive board below to see exactly
how they performed across all metrics.

Stay tuned for more race analysis!

VISIT THE TRITONWEAR HQ

LIKE TRITONWEAR ON FACEBOOK

FOLLOW TRITONWEAR ON TWITTER

FOLLOW TRITONWEAR ON INSTAGRAM

Swimming analysis is courtesy of Tritonwear, a SwimSwam partner. 

In This Story

3
Leave a Reply

Subscribe
Notify of

3 Comments
newest
oldest most voted
Inline Feedbacks
View all comments
HB Swim Dad
5 years ago

Tritonwear needs to develop an Apple Watch app that can calculate these things for swimmers of all levels/ages.

Teddy
5 years ago

It’d be cool to see a correlation or regression between finishing rank and stuff like: reaction time, first or last 50 time, height, etc. I’d guess a lot of them would be curvilinear relationships, maybe with important predictors modifying strategies for swimmers with different builds ad stuff, or specialities (50 specialists might have different optimal startegies for 100s than 200 specialists)

Admin
5 years ago

This is a Tritonwear post from Tritonwear. Not Coleman. It’s what they do. They’ve been generating these for two years now. I love ’em.