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@chompk

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The route is quite narrow but way better than Bangkok footpath lol There’s even a wild boar appeared during the route😂

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The split was as planned because I cheated a bit lol

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Running at rail corridor - SG today Following @dopemandave.eth workouts 3k warmup (1k@4:25 + 1k@4:05) x 4 sets 1k@4:25 3k cooldown It was brutal lol. I need to take 2-3 min rest on the 4:25 min/km set (goal pace +sec set) before progress to the next set😂) Will attempt this again in the week after!

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The power of imperial metric standard metric won’t understand

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I typically rotates between Boston 12 and Takumi sen 9. I prefers Boston 12 tho, takumi sen 9 is a bit too responsive because the foam wasn’t very thick

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Just completed my last month at my old AI consultant company on August and I just start my new journey as a founder for a medical AI startups It’s a huge leap of faith that I did jumping to the unknown. Being founders could be stressful as hell but hope I’ll enjoying the ride!

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Just did two runs this week - Intervals 800@4:00/200m walk 6 sets - easy 13k run Reducing my distance and focusing more on speed works💪

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Man this workouts are brutal! Kudos! But I think I’ll try something similar to this on my weekends tempo run hahaa

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Totally agree that it’s super soft but I love the soft part tho. I think it’s a very comfortable marathon shoe but not a very good shoes for 5k,10k

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Did a tempo run today! Warmup 3k - 3k @ 4:30 - 3k @ 4:20 - 3k @ 4:10 Cooldown 3.5k Long way to go for a HM!

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Just back to running post-injury after a long 2 weeks break 2 weeks pause really increase my running HR (~10 bpm avg) but the good thing is that all my injuries including shin splints are all gone Back on track🏃🔥

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Yo! Congrats man!! Did you negative splitted? Your HR looks fire!

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12/ Thank you all for reading to the end! If you are curious about any information I can plot from this challenge, feels free to reply this thread! Stay fit y'all🏃

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11/ That's all for the "Onchain summer challenge" workout analysis report! The code is open-sourced and is available here: https://github.com/tann9949/receipts-xyz-py

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10/ Lastly, with this data, I can count the attested workout and see the time of each exercise I visualize the exercise time by heatmap. Surprising to see that there's only one exercise done at noon (on US East time zone)

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9/ How about the distance covered each day between running/biking? At first, I thought biking distance would always more than running, but I was wrong We got many runners here in this challenge!

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8/ Let's breakdown more on the exercise type The data allows me to check the proportion of strength training time vs other sports. Looks like participants aren't weight-training type XD

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7/ Let's shift back to intensity minutes. Since not all exercises time aren't counted as intensity minutes, only time that HR exceeds Z2 We check for the percentage of intense vs non-intense time Tuesday with only 25% intensity minutes surprise me lol

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6/ But with more participants increase while plateauing, how does intensity minutes for each day looks like? Here's the plot of - # of new user each day - Intensity minutes contributed each week Nothing very interesting here

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5/ Let's start with the first boring plot - Participants increase the most first few days and plateau - Intensity minutes increase linearly - People didn't start biking right when the challenge starts (unlike running) - Participants literally runs everyday

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