


Personal collective of ideas, thoughts and notes
Another fun year chasing some kudos and KOM’s on #Strava!
Another great experience racing ORAMM (Off-Road Assault on Mount Mitchell). Some of the coolest temps but also pretty slick from all the rain we have had lately. This was my slowest time over the 4 years racing this event, but due to that it was probably the most enjoyable 🙂
3 minutes slower than in 2022 🙂
It has been a great 16 weeks training for Ironman Texas coming up next week. One small injury (foot) from either running or pushing too hard off the wall while swimming. Some interesting stats through these training blocks:
Longest week: 18 hours
Max CTL: 116
Max TSS: 144
Cumulative Miles: 2161
3 week blocks, with 1 week rest. 2 week taper into the race.
Compared with past Ironman races, used the sauna during the last 3 weeks to get more heat adapted, and did a little more strength based workouts. (Not tracked in Intervals). I also focused more on Z2 efforts while running. The Oak Island Half Marathon got me running a lot more early season. Overall, I had some good PR’s during the last 4 months:
Tracking cycling endurance training progress over time. As I have shifted my focus from MTB racing to Endurance/long distance triathlon, My sprint power has decreased slightly (5 minutes and 1 minute) but FTP (20 min+) has slowly been ticking upward. Since I have been swimming and running more, it probably has not increased as much as I hoped, but I am learning endurance is not something that gets established overnight ….
A fun start to the 2024 season in Oak Island. I decided to do a Half Marathon to try and accomplish a one of my goals of breaking 1:20 over the 13.1 miles. This didn’t happen today, but it was fun trying 🙂
3rd Place Overall, 2nd Place Overall Male.
I think I started out at the right pace around 2 – 3 secs faster per mile than planned, I knew going out would be down wind, and coming back was into the wind, so I tried to bank a little bit of time for that. I think I didn’t anticipate the wind being that strong. At the time 2nd place was slowly pulling a gap which also wasn’t motivating, but then seeing that I was making up some time on 3rd place kept me pushing. So mentally it was a little tough on my way back in as once I passed 3rd place I didn’t think I could catch 2nd. With about a mile or mile and a half to go, I took a look back and had dropped 3rd, I also realized I was not going to make 1:20, so backed off a little.
Super interesting article on the use of Hypoxanthine (from sweat) being used as a predictor of performance in athletes.
Having done HR tracking, Power and over the last couple of years, Lactate, it’s always interesting to hear of new methods and advancements in performance, and opportunities to improve metabolic health. So while I am still waiting for a reasonable/practical real-time Lactate monitoring solution, maybe I should skip to the next big thing …
Check it out here: https://pubmed.ncbi.nlm.nih.gov/23670363/
Purine metabolism reflects the exercise-induced muscle adaptations and training status. This study evaluated the utility of plasma hypoxanthine in the prediction of actual sport performance. We studied male athletes: 28 triathletes (21.4±2.9 years), 12 long-distance runners (23.2±1.9 years), 13 middle-distance runners (22.9±1.8 years) and 18 sprinters (22.0±2.7 years). Season-best race times were considered, achieved over standard triathlon, 5 000 m, 1 500 m and 100 m, respectively. Incremental treadmill test was administered to determine maximum and “threshold” oxygen uptake. Resting and post-exercise plasma concentrations of hypoxanthine, xanthine, uric acid and lactate were measured as well as resting erythrocyte hypoxanthine-guanine phosphoribosyltransferase activity. Simple and multiple regression analyses were used to identify significant contributors to the variance in performance. Hypoxanthine considered alone explained more variance in triathletes, long-distance runners, middle-distance runners and sprinters (r 2=0.81, 0.81, 0.88 and 0.78, respectively) than models based on aerobic capacity and lactate (R 2=0.51, 0.37, 0.59 and 0.31, respectively). Combining purine metabolites and cardiorespiratory variables resulted in the best prediction (R 2=0.86, 0.93, 0.93 and 0.91; r=0.93, 0.96, 0.96 and 0.95, respectively). In summary, hypoxanthine is a strong predictor of performance in highly trained athletes and its prediction ability is very high regardless of sport specialization, spanning the continuum from speed-power to endurance disciplines.
I did a lot of running, riding and swimming 🙂
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