The Experiment Continues…PART TWO: Power


The experiment continues.

Over the last couple of weeks, my plan has consisted of swimming, biking, running and strength training sessions.  I’ve logged the workouts in an app that I LOVE, called Training Peaks, recording within the application all of the data that comes along with 21st century technology (heart rate monitors, triathlon GPS watches, and my IPrecious).  I’ve completed a number of training sessions in all four disciplines, so that I have a fairly decent-sized sample in order to crunch some numbers that will actually mean something to my training and improvement.  This is the second post wherein I’d like to briefly talk about the data.  In this post, I’d like to elaborate on a number that stares me in the face every time I hop on my bike (I named him Maximus, after a horse from a Disney movie…and with that, let the lambasting commence within the comments…) or take a cycling class at my gym: Watts.

20130626-055155.jpg   (This is Maximus)

If you ride your bike a lot or go to spin classes, you can track the amount of power your legs are generating through the amount of watts shown on your GPS or the device attached to the stationary bike on which you take your spin classes.  Here’s what the device on the bikes used within my usual spin class look like:

image1-1

My spin classes normally go for 45 minutes, but I try to get there early in the hope that they will turn on these devices 10-15 minutes before class starts.  In the example above, you can see that the device was only turned on about 5-6 minutes before the class began, so the only hard data I have to go on for the morning’s effort is captured here.  Normally, I’ll start my morning with a run of 45-60 minutes before transitioning to a spin class, so my legs have already been forced to work for a bit before this 45 minute cycling session begins.  This means I am warmed up and awake – but the tank of energy has already been depleted.  During triathlons I will already be tired by the time I hit the bike – a 2.4 mile swim can do some damage – so hopping on the bike not feeling 100% is a good thing.

When I first looked at this screen, I could understand RPMs (revolutions per minute – how fast those pedals were going around in a one minute time span), MPH (miles per hour, just like a car), heart rate (beats per minute – got that one), calories burned (say hello to an extra Oreo – oh hell yeah), time and miles covered.  The one data point I didn’t really understand was Watts.  So I did some reading and I asked a couple of Ironman athletes in my gym about how to use this data point in my training.  What I learned was freakin’ awesome.

Up until a couple of weeks ago, I focused all of my time and attention on average speed and miles covered.  I used these two pieces of training data to measure my performance.  The faster I went, the bigger my smile at the end of the 45 minute training session.  The other athletes poked holes in my analysis almost immediately.  Here’s the breakdown on what they shared:

  • average RPMS – a nice statistic to track, because the higher your average, the quicker your leg turnover.  That’s nice to know – but it’s not a predictor of future race performance because you aren’t pedaling in wind, rain, on uphills, downhills, etc.
  • average MPH – another fun little statistic – but don’t use it as a predictor because a) you are only going 20-23 miles in an hour on the stationary bike, and b) no elements, heat, hills.
  • Calories burned – nice if you want an excuse to eat another Oreo.  (I do.  I like this number.  So there.)
  • Miles covered – nice little piece of information, but it doesn’t mean you will rack up mileage even close to what you see on the screen when you are riding in a crowd of other athletes on race day.

So there I was, left with only one data point left: watts.  When I asked about this number, I got a solid lesson over awful cups of burnt coffee that left me re-thinking how I attack my cycling workouts from then on.  The average watts figure at the top of the picture above measures the average amount of pure power being created during the training session.  This figure is a more pure measurement of cycling strength because it is immune to the other variables.  It simply states how much power your legs are giving off.  The More power generated, the faster you go.  Simple.

OK – so how the name of Zues’ rear-end do I measure my average watts, comparing the power that I currently generate to the amount of power I need to generate over a 112 mile bike course (leaving some juice in the tank for a marathon)?  Well their obvious first answer was “just try to meet or exceed your average every time.” OK, well that’s easy enough to track.  But how does watts translate into speed in a race?  That’s where the conversation got a little gray.  However, they recommended looking at pro triathletes statistics on-line, since they usually share these data points post-race.  I followed their advice, using my Unicorn as the race of measurement (Ironman World Championships in Kona).

Ben Hoffman is an elite Ironman triathlete.  He came in fourth this year at the Ironman World Championships, as was the top American male finisher.  While I couldn’t find his 2016 stats, I was able to google his 2014 cycling statistics for this race, and the numbers blew me away.  Ben covered the 112 mile Kona bike course in 4 hours and 33 minutes.   He maintained an average speed of 24.4 miles per hour, with a cadence (RPMs) of 89.  He averaged 2:27 per mile.  The average watts he generated for this portion of the race was 274.

Whoh.

While I am not nearly looking to keep up with these beasts, at least it gives me an idea of how watts translates into speed.  Hoffman averaged 24.4 miles per hour and the average watts were 274.  While listening to the live coverage of this year’s Ironman World Championship, the announcers estimated that the leader on the bike (and eventual winner – Jan “Frodo” Frodeno – was probably putting out close to 290-300 watts on average.  He covered the bike course in 4:29.

Using the elite athletes’ numbers as a point of reference, I designed a couple of goals for myself going forward:

  • During these 45-50 minute spin classes, my primary goal is to generate an average watts figure that beats my prior workout.  In the picture above, I averaged 254 – so I know cranking out a 250 average watt session is possible.  My next goal will be 255…then 256…etc.
  • I’ll need to attach a power meter on Maximus, and then collect a sample of data to measure my watts for longer rides.  Obviously, the average will be lower than in my spin sessions.  However, I am hoping to begin at around 220 and then get stronger from there.
  • By the time next July rolls around, I am hoping to have an average of 230-240 watts for a 100 mile training ride under my belt.  That should get me back to the transition area in plenty of time to begin my 26.2 mile waddle to the finish line before the clock hits midnight.

The data matters.

 

Day One of the Science Experiment…


October 5th 2016

The Day’s Game Plan:

Up at 4am.

Wednesday is Speed Day, so warm up with a 1.5 mile run around the lower loop of Central Park, until I hit the base of Cat Hill.  The goal is to complete four hill repeats before heaving all over my bright orange Brooks.

Once I wrapped that up, I waddle home, grab my workout bag and head to the gym.  The goal here was to log 1000 yards in the pool, and then hit the weights.

In the evening, the goal is to amp up my metabolism by doing a workout at home that primarily focuses on core strength.  I’m hoping that by amping up my metabolism right before bed, my body will burn more calories that it normally does while I sleep.

Nutrition-wise, I’ll bring lunch to the office so that I’m not tempted to eat what I really want: a chicken parm hero from Luigi’s.  I’m also going to go protein heavy in the morning with some hard boiled eggs and a shake.

The Outcome

Well, I got up in time and knocked out a relaxed swim.  1000 yards in 28:01.  Water seems to be my natural element – although I know it’s a training session, swimming is almost therapeutic to me.  I got these cool-looking new googles too – they make me feel like Fonzi.

the-fonz

I changed into my running stuff and ran 1.5 miles as a warm-up to Cat Hill.  The hill is about .35 of a mile, with a steep incline at the outset which tapers off with about 1/10 to go, so hill repeats on this section of the park are not very enjoyable to a shlub like me.  I got 4 repetitions in before I had to call it a morning – there were too many bikes going in the wrong direction within the running lane, and if one of them hit me this morning I was not in the mood to be Mr. Forgiveness.  Instead, I would have channeled my inner Ric Flair and suplexed the schmuck.

woooo

I knew it was time to call it a morning when one of these two-wheeled whackjobs flew by me – without a helmet – while in the designated runners lane – going opposite the flow of traffic – while texting.  Given the fact that it was before 6am and sunrise still hadn’t provided some degree of natural lighting to the park, this guys was a rolling accident about to happen.  Now don’t get me wrong: I love cycling.  As a triathlete and Ironman hopeful, it’s the one discipline that I need to spend the most time on.  However, when I ride I try to respect the rules of the road and those around me.  I got the work in, so I felt fairly accomplished by the time I got home.

I stuck to my protein-heavy breakfast: a couple of hard-boiled eggs and a shake.  I’m trying to get myself to stop craving sugary awesomeness like Oreos (seriously – Oreos should be a darn food group – it should go Oreos, Pizza, Pop Tarts and General Tso’s Chicken).  Kicking the sugar craving will NOT be easy.  I have absolutely no discipline, so saying no to those round tasty little pieces of Nabisco heaven is going to feel like root canal without the Novocaine.  However, the juice is worth the squeeze.  So the first real experiment that this new adventure has triggered deals with diet.  I’ve come to realize that the things I now need to say “no” to historically have constituted a decent size of my overall caloric intake.   So switching to a much healthier selection will not be easy.  It also didn’t help that I was lazy this morning and forgot to put together a sizable salad for lunch.  As a result, lunch consisted of a couple of handfuls of pretzel pieces.  This will cause my overall calorie count for the day to be less than the total I have budgeted for myself: 2,300.  I’ll need to compensate by having a bit more protein tonight.

Had a simple salad with a couple of ravioli for dinner.  Figured that I am in severe calorie debt today – I can tell from the raging migraine I’ve been dealing with and the stats on Myfitnesspal.com.  (Yes, I am using a website to count my darn calories and make myself more accountable – would much prefer using some Deal-A-Meal cards).  I wanted to stay away from heavy carbs at night, but I think I’ll need the efficient energy that comes from carbs in the morning.

The evening workout, right before I crashed tonight, was annoying.  I am not a huge fan of core work, because it’s a weak point for me.  We’ll see over the coming weeks whether the concept of cranking up the metabolism right before bed helps burn more calories.

I look at the first 2 weeks of this experiment as a data-gathering phase.

Today’s Nugget

October 5th 2011: Steve Jobs passed away at the age of 56.

Crazy Ones