Posts by ihersey

Tech executive and long-time endurance athlete; 19x Ironman; 2x Kona qualifier; data geek; Big Island resident

Lucky 13

This year’s Ironman World Championship race in Kona was Ironman #13 for me. I came into the race probably the fittest I’ve ever been, at least in the swim and bike. The run was a bit of a question mark due to some persistent hamstring issues I’d had earlier in the year; I did seem to be over them thanks to my miracle worker of an ART specialist, but I didn’t have much of a base — one 20-mile run in a training camp at Tahoe in late August was my one and only run over 12 miles in the past few months. Luckily, running is supposedly my strength.

I got to the Big Island 10 days before the race in order to try to get heat acclimated. The simplest way to describe the protocol is “train 2-3 hours a day in the heat at low-to-moderate intensity.” It worked out pretty well — in particular, I got a lot of afternoon rides in on the Queen K once the wind had picked up, which is pretty much what we athletes would face in the last 30 miles of the actual race. I knew where the climbs were, and I knew to save some watts for this part of the course.

Race week was a blur — lots of stuff to do (registration, expo, bike adjustments), including keeping the muscles loose with some light training. What always surprises me is how many athletes you see out on Ali’i Drive during race week just absolutely hammering their runs and bikes. Not to mention irritating the locals by not stopping at stop signs, weaving in and out of traffic, and generally acting as though they owned the place. Not to single out any particular group, but this behavior seemed particularly acute among the Euros.

Many folks, myself included, seem to walk around town with a look on their faces that showed the weight of apprehension and expectations. In many ways, once you’re on the island, race day can’t come soon enough. I actually slept pretty well — better than I have before many of my races — so I woke up even a few minutes before my alarm clock and thought to myself, “Let’s do this thing!”

Saw a few friends between body marking and the walk to the transition area, at which point I got all my little tasks done pretty quickly. I got in the water after the pros took off, and swam out to the far left of the start where there were fewer swimmers and I could get a nice, uncrowded warmup. As the start approached, more swimmers started showing up near me, so I had to jockey for position a little bit, putting myself almost at the very far left and maybe three rows back.

entering the water

Athletes enter the water

Athletes enter the water

Athletes enter the water

Athletes enter the water

The calm before the storm

The calm before the storm

And...we're off!

And…we’re off!

Aerial view of 1800 athletes

Aerial view of 1800 athletes

The cannon went off, and the race suddenly got very real — I was in the Ironman World Championship! Unlike in the two other times I did this race, I seemed to have seeded myself exactly right, as I was very quickly in clear water and not getting a ton of contact with other swimmers. I found some feet to get on and just tried to keep focusing on having an efficient stroke. I reached the turnaround boat, glanced at my watch and saw 32 minutes, so I seemed to be on a good swim.

There’s often a slight current against the athletes on the way back to the pier, though, but once I was on the way back the field was spread out enough where I could swim very close to the buoys without bumping into people; the only hazards were the occasional paddleboarder volunteers who had actually drifted into the course and were yelling at swimmers to stay left — they were actually in the line between the buoys and were causing swimmers to bunch up needlessly.

You can see the pier for quite some time before you actually get to the swim exit; I entered what I thought was the final stretch at 1:10 and change, but by the time I got to the stairs my swim time was 1:16. Oh well — still an 8-minute Kona PR, and what’s more, it didn’t cost me as much energy as my previous swims had. My technique work had paid off.

The day just gets better from here

The day just gets better from here

Now the fun starts!

Now the fun starts!

The only casualty from the swim at all was some chafing on my pecs from the swim skin rubbing against salty ocean water, and I would definitely feel the sting of that later in the day — splash some Coke or sport drink on a fresh abrasion and let me know how it feels. 🙂

I had a pretty good transition for me — 4:32, ok considering the long run around the pier and taking the time to put on arm coolers and a bike jersey. The main reason for both was to avoid a blistering sunburn; with my fair skin and the intense Hawaiian sun, I can’t put on enough sunscreen to last for the duration of the Ironman bike. The regular bike jersey also gave me some pockets I would turn out to need later. Anyway, soon I was off and riding, feeling good.

Out of transition and straight uphill

Out of transition and straight uphill

The first part of the ride was fast; it wasn’t very hot out and we had a nice tailwind. Being a slow swimmer by Kona standards relative to my bike and run, I was passing more people than were passing me, but I had to do some small surges to avoid being in a drafting position.

Early on the Queen K

Early on the Queen K

"Critique my position," as they say on Slowtwitch

“Critique my position,” as they say on Slowtwitch

I was riding well within my planned power output and feeling good, but around mile 35 (near Puako), disaster struck. A guy I was passing suddenly moved left (without looking) into me. I had a guy coming up on my left so had nowhere to go. I called out to the guy, but he was already touching me; then his front wheel hit my bike, and he went down, which then took my rear wheel out from under me. The next thing I knew, I was sliding on the pavement on my right leg. F**k!

The good news was that I could tell I wasn’t hurt badly — just some road rash on my right leg, hip and a little on my right elbow, plus my shorts and arm cooler were ripped. Then I looked to see how the other guy was, and what he wasn’t was at all apologetic. In fact, he tried to blame it on me: “why didn’t you tell me you were there?” First off, I did, and second, why didn’t you look before moving left? Anyway, there was no time to get into an argument — I had an Ironman to finish. Now came the bike inspection:

  • Rear bottle cage and tool bag broken off and lying in the middle of the road
  • Chain off
  • Rear tire was flat

I had to wait for a break in the line of cyclists to retrieve my tool bag and bottle holder, and then just as I was getting my rear wheel off, the Bike Works support van pulled up. They were apparently on their way to help someone else, but they saw me first, so they did the tire change and also had a floor pump so that I didn’t have to waste a CO2 cartridge. I put the tool bag in one of my jersey pockets and left them with the now-useless bottle cage, then one of them gave me a nice “pro” push start to get going again. All told, my Garmin says I lost 8 minutes; the Ironmanlive tracker shows I lost more than 150 places in that section of the bike.

I took stock of my situation; I still had a good time going, but now that I was down one bottle cage, I was going to have to approach the aid stations differently, Up until then, I had been taking up to two bottles at each station, but since my front one was a fixed, refillable Speedfil, I could only take one spare bottle each time, but that in my downtube holder, then if I was lucky I could grab another bottle and add to the Speedfil. That mostly worked, unless I missed catching a water bottle in the first pass, which happened occasionally.

After the turn to Kawaihae, I saw the leader (I’m guessing Starykowicz) on his way back (hey, the male pros did start 30 minutes before me), followed by the chasers. Later on, on the rollers toward the turn for Mahukona, I saw a pack of at least 50 guys — this must be the front of the age groupers, I thought to myself. Then came Packs 2 and 3. Ironically, I had draft marshalls near me, and here you had these massive packs going the other way. Hard to say if they were intentionally cheating, but it definitely didn’t look legal, which was disappointing. Short of having more drafting marshalls out there, it’s not clear what Ironman can do to cut down on what seems like blatant cheating.

The good news was that I was almost to the turnaround at Hawi before I even realized it — there were none of the usual winds, either headwind or crosswind. I did pull over briefly after the turnaround to adjust my front quick release; it felt as though my front wheel might have been a little askew after the crash. That cost me another minute, but since there was some fast downhill coming up, I thought better safe than sorry.

The return trip from Hawi is where the work usually begins, and this year was no exception. The wind started picking up on the rollers to Kawaihae, and then we worked the biggest climb of the day — the short-but-steep slog back up to the Queen K.

There's a really nice beach park down there.

There’s a really nice beach park down there.

Once on the Queen K, you’re on the home stretch, but it’s a long home stretch, and the headwinds kick up in the afternoon, which on this day made this the toughest part of the day. A look at my TrainingPeaks file confirms this from a numerical perspective — my Peak 30, 60 and 90 values were all on this stretch:

TP file kona 2013

You’ll also note from my CP 180 that I negative-split the ride from a power perspective. So sometimes I do actually practice what I preach. My VI (Variability Index) was also quite even at 1.04. Moreover, the Queen K section (the last 35 miles) is where I picked up over 200 places, so my “save some watts for the Queen K” strategy worked out pretty well.

Approaching the bike finish with bonus war wounds

Approaching the bike finish with bonus war wounds

My bike time was 5:31, which was over 20 minutes faster than I’d ever ridden in Kona, so I was pretty happy with that considering the 9 minutes I’d lost in total to the crash. What I wasn’t sure of was how well my hydration had gone since losing the rear bottle cage, but I figured I would find out sooner or later on the run.

I got out on the run course at 6:57 into the race — earlier than in any Ironman I’d ever done except for two of my three Ironman Arizona races. So despite everything, this was going to be a quick day if I could put together a decent run. Initial signs were good; sub 7:30 pace felt awesome for quite a few miles.

Mile 2 of the run - oh, to be able to run sub 7:30 pace all day...

Mile 2 of the run – oh, to be able to run sub 7:30 pace all day…

But early enthusiasm often leads to mid-race problems. I had a great first 10 miles, then caught my struggling teammate Matt around mile 11, but I started having my own struggles after the halfway point, which I reached in 1:43. Repeating a theme from countless previous races, it was hamstring cramps — the kind that stop you dead in your tracks. I thought my fluid intake had been pretty good, but Houston, we had a problem.

Rather than focus on the negative, I tried to figure out what I needed (“fluids”) and how best to get enough of them in (walk the aid stations and take whatever it is they were offering). The cramps were pretty stubborn; I had to walk a good section of the Energy Lab, and even the running part was none too quick.

Noticeably more labored stride, if you can even call it a stride

Noticeably more labored stride, if you can even call it a stride

Eventually, the fluid intake did take effect, and I was able to keep myself on the verge of cramping instead of actually cramping for the rest of the run. I did pick up a number of places in the 7 miles from the Energy Lab back into town even though I felt as though I was struggling. At this point, I figured that if I could keep going, I could break 10:50, so that became my revised goal.

Underpromise and overdeliver — it’s not just a business cliche. It turns out I was able to pick up my pace a little, so I kicked it in down to Ali’i Drive and ended up finishing right behind the legendary Ken Glah, in 10:43:41.

Approaching the finish

Approaching the finish

Which way to the gun show?

Which way to the gun show?

A 32-minute PR warrants the risk of an "excessive celebration" penalty

A 32-minute PR warrants the risk of an “excessive celebration” penalty

Aftermath: chafed, bloody, blistered and tired. But ready to take this one on again in the future and do better.

The tale of the tape

The tale of the tape

Margarita time!

Margarita time!

Kona prep: some big training, some big racing

The Ironman Triathlon World Championship, or “Kona,” as those of us in the triathlon community refer to it in hushed tones, is less than three weeks away. I’ve had several luxuries this year with respect to this race:

  • I qualified back in November of last year at Ironman Arizona, so I haven’t had to “chase” a slot this year. That may be both a blessing and a curse — a blessing because I’m not over-raced and tired, but a curse because I don’t have a lot of long training under race conditions under my belt.
  • I’ve been taking (mostly, with some consulting) a sabbatical from full-time employment since February. This may be the single best thing I’ve ever done — in my previous 25 years in the software industry, I had always gone immediately from one job into another without a break. Regardless of how Kona turns out, this time has been epic.
  • I’ve overcome some chronic imbalances in my body (SI joint imbalances, other spinal mobility issues) thanks to an ART specialist who is an absolute miracle worker. Earlier in the year, I had great swimming and cycling fitness but was struggling in my traditional strength of running — I had one hamstring strain after another, which forced me to DNS my favorite marathon (Big Sur) back in April. But since then things have been on the upswing, and at 51 I feel fitter than I did in my 20s and 30s.

Anyway, Kona. I’ve taken a somewhat different approach to the race than I did in my previous two buildups:

  • More volume/intensity on a consistent basis. You can quantify this in TrainingPeaks as Chronic Training Load (CTL), a numerical value for fitness.
  • More and better sleep. Not working full time helps a lot in that department.
  • Better eating. Less restaurant eating, better choices, and consistent meal times.
  • I’m also heading over to Kona 10 days before the race instead of 5-6 days prior, and I have a heat acclimation protocol to go with it.

I’ve also done a few test races:

  • Back-to-back Olympic and long sprint races in Malibu earlier this month. I’ve never done two triathlons in two days like that before, and it worked out fine. In both races, I was within a minute of PR for each.

    post Malibu

    Post-Malibu redydration

  • Ironman Lake Tahoe this past weekend, where I did the swim, 50 miles (one loop plus a little) of the bike, then a 5-mile transition run. I don’t know if doing this was wise or not — I have never DNFed an Ironman before, and I started this one with specific intention not to finish (my bike-to-run bag, for example, was empty), but I had registered for this race before I got my Kona slot, and the WTC (the corporation that owns Ironman) doesn’t give much of a refund, so I figured it was better to make it an expensive training day. It was pretty epic.
    Friday's pre-race swim was so nice and warm

    Friday’s pre-race swim was so nice and warm

    The exit from the actual IMLT swim...not so much

    The exit from the actual IMLT swim…not so much

    Had lots of fun on the climbs, though

    Had lots of fun on the climbs, though

    Kona should be interesting this year — can’t wait!

Kona, Baby!

As a postscript to my blog post on Ironman pacing, I’m happy to report that Athlete B took his considerable fitness to the new Ironman Canada in Whistler and got himself a well-deserved Kona slot. I’ll leave aside the specific strategies around slot allocation, late-season Ironman races, etc., and look at the numbers:

  • Whistler is an impossible course on which to ride evenly. It is very hilly and rolling in the first half, flat in the third quarter and uphill in the final quarter (by quarters and halves, I mean by time). Athlete B’s VI (Variability Index) was 1.11 for the entire race; NP was 214 (almost exactly the same as he had in IMCdA). Bike time was 5:19 compared to 5:14 at IMCdA.
  • In his division, he had nearly identical placings after each leg. IMCdA: 35th after the swim, 16th off the bike, 11th at the finish. IMC: 36th out of the water, 18th off the bike, 9th at the finish. Of particular note was a 3:22 run at IMC vs. a 3:26 run at IMCdA after what is, on paper, a harder bike course.

Although it isn’t possible to divide the Whistler bike course into comparable segments, we can look at how Athlete B rode the course by looking at peak power numbers. Climbs are usually going to produce the higher power numbers, so as we might expect, his Peak Power for 20, 30 and 90 minutes all come in the hilly first half. What is interesting, though, is his Peak 60:

IMC-AthleteB-peak-60

This graph illustrates the he actually had his best 60-minute power in the final part of the race, which on this course effectively means he rode negative splits (there isn’t enough time in the final quarter of his ride to have his Peak 90 there).

One other interesting data point to look at is cadence relative to power.

First half:

  • Peak 20: NP 253W, avg 247W, avg cadence 80 rpm
  • Peak 30: NP 251W, avg 244W, avg cadence 79 rpm
  • Peak 90: NP 227W, avg 205W, avg cadence 82 rpm

Final quarter:

  • Peak 60: NP 227W, avg 215W, avg cadence 71 rpm

This correlates with the cadence drop that we saw in IMCdA — Athlete B’s natural inclination seems to be to reduce cadence rather than gear. Based on the athlete’s heart rate during this segment and his subsequent solid run split, however, it doesn’t appear as though this had any negative effect on his overall race.

Regardless, now he can put this data to work in Kona, which is the best news of all!

The sweet smell of Kona

The sweet smell of Kona

Ironman power fall-off: is it the gear or the cadence?

First off, this post isn’t groundbreaking exercise physiology research; it’s just numbers analysis brought to you by my friends at TrainingPeaks — they provide the software, and I provide the analysis to my teammates.

What I’ve been looking at is the power files from a recent Ironman race, one in which the athletes involved were well-trained, experienced performers at the Ironman distance:

  • Athlete A, a former pro now racing as an age grouper, who won his division at the 2013 Ironman Coeur d’Alene by a pretty substantial margin.
  • Athlete B, a younger age group male, who set a PR at this year’s Coeur d’Alene race and finished 11th in the most competitive division, but only 5 minutes out of 6th.

Athlete A is very new to training and racing with power — you’d call him “old school” in his training and racing methods. He’s used to racing by feel, and this has served him well over distances from sprint triathlons to Ultraman, yet he hasn’t done an Ironman run split that reflects his considerable ability as a runner. My working theory for this was that he spent just a little too much energy in the bike leg, which is his forté (though he also swims in the low- to mid-50s, so he’s not exactly a slouch there either). A couple of us on the team basically forced him to get a power meter, so with a few rides’ worth of power numbers, including a sprint triathlon the weekend before Coeur d’Alene, Based on what I could see, I guesstimated his “ride-to” power for the Ironman distance at 255W. I could tell he thought that sounded low — in a lab environment back in 2007, the analysis based on blood lactate tests done on a CompuTrainer had him pegged at 325W for Ironman power. But in trying to ride to that in a summer Ironman race, he had cooked himself by mile 70. In the meantime, we have all sorts of real-world data from the pros at Kona, the best of whom don’t even average 300W. “Try it,” was about all I could say.

His race went great, but not perfectly. He was 2nd out of the water, but started cramping and estimates that it took 20-30 minutes into the bike to fully rid himself of the leg cramps. During this time, he was passed by a number of guys and was in the for-him unusual position of having more riders around him than he was used to. Once the cramps subsided, he did some work to get back into his more usual front-of-the-pack position, and ended up coming off the bike in 1st with a 5:07 split. On the run, he was able to run sub 3:30 — something he hadn’t done in about a decade — and win the age group by a comfortable margin. Kona, baby!

So the question was, how did the power-pacing experiment go?

If we look at his TrainingPeaks file, we see a number of things:

IMCDA-AthleteA-entireride

  • Normalized Power of 231W — considerably under the 255W I had suggested for his ceiling.
  • Variability Index of 1.07, which means he rode fairly evenly (1.00 is perfect), especially for an undulating course.
  • TSS of 268 and Intensity Factor of .72, meaning he left plenty in the tank for the run (normal target TSS is 280-310; ideal IF varies according to how long the athlete takes for the ride).

The great thing about looking at Coeur d’Alene is that it is a two-loop bike course, so we can compare his first and second halves to see if the effort was truly uniform. If we zero in on Peak 30 and Peak 120 (best power for 30 minutes and 120 minutes, respectively), we see that those both occurred in the first half:

Peak 120 shows an NP of 250 — much closer to the target 255. Note that the average cadence was 77 vs. 78 for the entire ride.

IMCDA-AthleteA-firsthalf

Peak 30 occurs within Peak 120, and it involves a sustained climb, so there’s a spike in power up to 265W for that period. The cadence for this segment also equals the average cadence for the entire ride, at 78 rpm.

IMCDA-AthleteA-firsthalf-peak30

 

The timing mats had Athlete A doing the first half in 2:32:19 vs. a 2:35:04 for the second half, so there was a slight positive split. Lots of factors could account for this, though — a shift in the wind being the most likely external culprit. However, if we look at the same part of the course where the athlete did his Peak 120, we see a marked difference in power output:

IMCDA-AthleteA-secondhalf

  • NP of 219 vs 250 in the first half
  • Average cadence actually went up from 78 to 80
  • VI identical to that in Peak 120 at 1.04

Athlete A reported being aware that he was not comfortable pushing the same wattage in the second half, and the numbers would indicate that he likely backed off the gear but increased his turnover slightly. This strategy seemed to pay off, as he was able to run sub 3:30 off the bike for the first time in a decade, winning his age group by a massive 24 minutes. He used no watch or heart-rate monitor during the run; his major reported issue in that discipline were foot blisters he sustained early on and had to deal with for the bulk of the run.

Athlete B put together a similarly strong race and reported feeling as though he could have gone a bit harder in the bike. If we look at his data, we can put some numbers to that perception:

IMCDA-AthleteB-entireride

  • A TSS of 219 and IF of .65. This is very low indeed for a guy whose bike split is 5:14 on a hilly course.
  • VI of 1.06, so ridden very consistently given the hills.
  • Cadence averaged 80 rpm, 2 rpm higher than that of his elder teammate.

Athlete B reported feeling as though he were “holding back” the entire ride. If we look at the Peak 120 numbers, we do see a difference between the halves:

IMCDA-AthleteB-firsthalf

  • NP of 226W, 11W higher than his average for the entire ride.
  • Cadence of 82, or 2 rpm higher than his average for the entire ride.

Peak 30 occurs at approximately the same segment as the Peak 30 of Athlete A:

IMCDA-AthleteB-firsthalf-peak 30

Relative to Athlete A, Athlete B actually held back a little more in his Peak 30: he was 8% higher than his NP for the entire ride, whereas Athlete A was 14% higher than his NP during his Peak 30.

Yet we do see a similar fall-off, both in average speed and power, between the halves. The timing mats show a 2:35:09 first half vs. a 2:39:12 second half, and the power numbers do point to the cyclist’s own output as a significant factor. Looking at the same segment we had in Peak 120:

IMCDA-AthleteB-secondhalf

  • NP of 209W, 17W (or 7.5%) lower than in Peak 120.
  • Average cadence of 78 rpm, vs 82 in Peak 120.

What’s interesting is that this fall-off isn’t simply a “late in the ride” phenomenon; if it were, we would expect a significant drop in power after 90 miles. What we see instead, if we look at the Peak 30 segment during the second half, seems to be more of a conscious “holding back”:

IMCDA-AthleteB-secondhalf-peak 30

  • NP of 213W vs. 233W — 8.6% lower than in Peak 30.
  • Average cadence of 78 rpm, vs 82 in Peak 30.

This suggests that Athlete B used similar gearing in the two halves but simply dialed back his cadence in the second half to keep the same RPE (Rate of Perceived Effort), whereas Athlete A actually increased his pedaling tempo in the second half but decreased his resistance. Athlete B, like Athlete A, did have a very good run split in the mid 3:20s, though it was about 10 minutes slower than he believed himself capable of.

A sample set of two athletes in one race obviously doesn’t hold up to any scientific standards by which one could draw any conclusions. Both athletes are very fit but do not put in the type of volume that professional Ironman triathletes do, but their type of training does correspond well with that of talented “recreational athletes” — those who don’t do it for a living. I believe there are several factors at play:

  • Both athletes ultimately defaulted to RPE as an upper bound for their output. In other words, they maintained the same perceived effort. But natural fatigue and environmental factors (e.g., warmer temperatures as the day went on) increase RPE naturally, so the athletes had to reduce their output in order to keep their effort constant.
  • We don’t have heart-rate data for Athlete A, but we do for B, and we actually see his average heart rate drop 3 bpm in the second half equivalent to his peak 120.
  • Different athletes achieve “output relaxation” in different ways – some drop the cadence and some drop the gear. The fact that the more experienced athlete dropped the gear and increased his cadence is interesting, but we lack sufficient field data to draw any conclusions from that.
  • What I believe this does suggest, though, is that “negative splitting” (increasing effort and output as the race goes on) must be done consciously and must be practiced in training. I’ve now seen many more power files from Athlete A, and this is a technique he has been practicing in his training rides as he prepares for Kona.

On a final note, I also looked at my own race from Ironman Arizona, which is a three-loop course, but one that is much flatter than Coeur d’Alene’s. If we look at Peak 90 (120 would be longer than the loops took me), we see:

IMAZ-firstthird

  • Lower NP than either Athlete A or B by a lot. That’s because they are better riders. 🙂 But they also weigh 10% more than I do, and IMAZ being an easier course, I had a faster bike split (5:04).
  • Higher average cadence than the IMCdA athletes. That might be a function of my coming from a running background, or might simply reflect the course differences between the two races.

Then if we look at the final third of the race, we see this:

IMAZ-lastthird

  • A drop of 8W in NP (from 198W down to 190W).
  • A drop in average cadence from 88 to 85.
  • Time loss of about 60 seconds.
  • Surprisingly, superior VI (1.01 vs 1.03).
  • Rise in average heart rate of 8 bpm (going from 125 bpm to 133).

I definitely recall making a conscious effort to work a little bit hard in the final third, but not by much, since I still had the run to go. Perhaps that is reflected in the rise in heart rate; more probably, though, the heart rate has to do with my high sweat rate and resulting dehydration (my training partners can attest to my “king of sweat rate” claim).

I’ve been making an effort to incorporate negative splits into my own Kona preparation as well. I did actually negative-split the Kona run back on a very hot day in the 2009 race, but the 3:56 run split was nothing to write home about. Due to the heat, I made the decision to approach the run from the outset in survival mode, which meant I walked every aid station from the first one on. With my sights set a little higher for this year’s race, a negative-split run will be a difficult feat to repeat.

Can social media predict tonight’s winner of “The Voice”?

Earlier on in the season, I’d have said an emphatic “no” based on the correlation (or lack thereof) between buzz on Twitter, positive buzz on Twitter, number of followers on Twitter, week-to-week growth in followers on Twitter, Klout score — and just about anything else I could measure — and the actual results. The past couple of weeks, however, have gotten slightly better results, and that could be for several reasons:

  • Better odds in general as the number of contestants declines.
  • More focused social media discussion of the remaining contestants — i.e., less “noise” — overlapping better with voting behavior.
  • More audience engagement as we hit the semi-finals and finals, similar to what we see with big-time sports (e.g., Super Bowl, March Madness, NBA finals, Stanley Cup raise the volume of discussion over what you see in the regular season).

Remember, too, that we are using Twitter buzz only as a proxy for voting behavior — tweets don’t actually count in the voting. What does count is telephone voting, SMS voting (but only if you’re on Sprint), Facebook voting and iTunes downloads, this last category having a disproportionately large effect with sufficient volume. We do not have access to any of the metrics for these sources, so the experiment has been to see how well buzz on Twitter correlates with the outcomes each week. So this is the final week of the experiment for this season.

So let’s look at overall Twitter buzz:

voice all 2013-06-18 at 2.22.52 PM

And now restrict the view to only “positive” buzz:

voice positive 2013-06-18 at 2.25.52 PM

This does change the order between Michelle and Danielle if we look at the Top Entities view; the Swon Brothers are a distant third in both sets of metrics. We could posit that the Swons’ fan base doesn’t tweet, but that actually runs counter to generally observed engagement levels — the brothers are very active on Twitter compared with the other two contestants, not just with posting but also with replies and retweets. Perhaps two is better than one for keeping the chatter high.

Another interesting phenomenon became apparent in the buzz charts if we look at Top Hashtags: Michelle has a hashtag, #4eyesontheprize, that didn’t exist when I set the topic up, so this tag is not being counted in her totals under Top Entities. This means that her numbers are potentially higher than the Entity chart shows, though only for tweets that contain that hashtag and no other reference to her. So we can’t simply add the two numbers together. There’s also another telling phenomenon in that in overall buzz, #teamusher beats #teamblake, even though Team Blake has two of the three finalists. However, those numbers look vastly different if we just look at positive buzz. The thing about the sentiment coding here, though, is that it favors precision over recall, which is a somewhat technical way of saying it undercounts rather than overcounts. So when push comes to shove, I’m going with the old Oscar Wilde adage: “the only thing worse than being talked about is not being talked about.” — any buzz at all trumps positive buzz.

In that vein, however, we do have to remember that Danielle has consistently out-buzzed Michelle in many of the other weeks, and also that Danielle has more than 40% more followers than Michelle. On the other hand, follower counts have not correlated at all well with actual results, neither for “The Voice” nor for “American Idol”. Also, this week’s overall volume is significantly higher than in those previous weeks, so we’ll assume it follows the engagement trend of other finales, in which overall votes or other forms of engagement tend to correlate with viewing audience.

Anyway, it would appear the numbers are telling us that the Swon Brothers get third, and that there’s a somewhat conflicted picture of whether Danielle or Michelle wins, but I’m going with the overall buzz numbers and calling it for Team Usher’s Michelle Chamuel.

One last side note: it appears that “Voice” executives finally ponied up to Twitter, as all finalists’ Twitter accounts are now verified. In Twitter-speak, that means they now count as celebrities. 🙂

Social media numbers for “The Voice” semi-finals

Back from a hiatus on the Big Island to race and relax, it’s time once again to review the social numbers for this week’s “Voice”.” Past weeks have shown a relatively poor correlation between buzz on Twitter and actual results, but as the pool of contestants has decreased, the correlation has improved. This can of course be due to the increased probability of being correct simply as a function of smaller potential outcomes, but let’s see what the numbers say regardless.

For the period spanning last night’s live performances on the East Coast through midday today, we see the following:

the voice overallCompare this with only positive mentions, and we see a similar distribution:

the voice positive

The good news is that there’s a clear separation between the top two and the remaining three, so it appears as though Amber and Danielle are clearly safe. Two will be sent home tonight, though, and while it appears as though Sasha will be one of them, the difference between Michelle and the Swon Brothers is not very large. Both also seem to have a very loyal following that has kept them on the show even when the buzz numbers were relatively low, so at this point it’s just a guess as to which of the two will remain after tonight’s show.

Here I’m going with the Swon Brothers, purely because the novelty of a duo going to the finals vs three female soloists might have gotten the vote out better.

As this season has shown, though, the social numbers have been wrong before, so don’t take it to Vegas. 🙂

Hawaii 70.3 — a hot time was had by all

By some measures, I should be disappointed in my Hawaii 70.3 (“Honu”) result — I got 9th in the M50-54 age group as opposed to 7th last year, I failed to break five hours, and my body betrayed me in the run, which is supposed to be my best event:

honu 2013 result

But I like to take an analytical approach to my racing. Let’s compare some numbers:

2012 Top Male:

Name Swim Bike Run Finish
Armstrong, Lance 00:23:22 02:01:46 01:22:29 03:50:55

2013 Top Male:

Name Swim Bike Run Finish
Alexander, Craig 00:25:11 02:13:59 01:23:08 04:05:43

Now, Alexander is not the cyclist that Lance is, but he is a much better runner, and is a three-time winner of the full Hawaii Ironman to boot. So a winning time almost 15 minutes slower than last year is perhaps an indication that the conditions were more difficult this year.

Let’s compare the same athletes year over year:

Name Year Swim Bike Run Finish
Wee, Bree 2012 00:27:01 02:29:10 01:32:51 04:32:45
WEE, Bree 2013 00:28:29 02:30:31 01:48:08 04:51:05
Beckmann, Holger 2012 00:32:01 02:33:22 01:33:48 04:44:48
BECKMANN, Holger 2013 00:40:41 02:38:19 01:38:56 05:05:46
Doi, Keish 2012 00:34:52 02:37:38 01:31:37 04:48:58
DOI, Keish 2013 00:36:43 02:35:39 01:42:30 05:00:07
Hersey, Ian 2012 00:38:37 02:40:27 01:47:22 05:13:30
HERSEY, Ian 2013 00:37:40 02:36:16 01:51:05 05:11:33

This isn’t a complete analysis of everyone who competed in both years of course, but it does look at a female pro and a couple of top older male age groupers, and then at me. A couple of things emerge from the numbers:

  • The swim was slower in 2013
  • The run was slower in 2013

It’s not clear to me exactly why the swim was slower, but they did reverse the direction of the course this year, which might have been a factor. I was faster this year than last, but I’ve been swimming a lot faster in workouts this year, so should have been several minutes faster. For the run, it’s crystal clear why it was slower: it was HOT! Last year’s race had some very strong winds, which kept the temperature down.

My own run performance came down to the fact that my run training has been next to nothing since mid April when I strained my hamstring, forcing me out of my planned Big Sur Marathon and making the prospects of even getting through the Honu run iffy at best. Fortunately, the hamstring healed after four weeks, but the damage was done to my run fitness. But that isn’t an excuse — I came with great overall fitness and confidence, and was ready to race.

The swim started well — I placed myself on the right side of the field and swam un-punched and un-kicked for the entire time. The change that the race organizers made to start the age group women seven minutes after the age group men really helped. Fewer bodies, fewer arms and legs. It also made a big difference on the bike, because in years past I’d have to pass a lot of women who were fast in the water but clogging up the bike course (no offense intended — I know I could also solve the problem by “swimming faster”). The only tough part of the swim was after the final turn buoy, heading back to shore — that’s where the wind was coming from, and the chop was noticeable. The sun was also right in our faces, so it was difficult to see where the swim finish actually was.

Once out, though, I noted the time (a little disappointed, but you don’t dwell on a minute or two in such a long race) and headed up the ramp for T1. Though I needed help from a volunteer first to get my swimskin unzipped – the zipper was stuck. She had trouble as well, but eventually got it to unzip. I sprinted up the hill and found my bike, and made one of my faster transitions, other than fumbling with the shoes I already had in the pedals (the course goes sharply uphill right out of transition, so it’s tricky to jump on the bike without your shoes already on your feet — something to practice). Once off and going, I started passing guys (and a few really fast female swimmers) pretty quickly. The wind was going pretty fiercely and was mainly a crosswind, which requires a bit of nerve to ignore and just stay down in the aerobars in.

I was holding around 210-220 watts for the first hour, and averaged about 22 mph. Then the climb to Hawi came, which involves not only a long uphill with a few steepish parts but also a pretty good headwind. At some point near the turnaround, a fellow Wattie Ink guy passed me, but I caught him on the ensuing descent, which was blissfully free of the dreaded crosswinds this year, which meant I could cruise pretty easily in the aerobars at 30+ mph, regaining a lot of the average speed I had lost on the uphill. The Wattie guy and I were exchanging positions every so often, as I would push the uphills a little harder than he did. He turned out to be a younger guy named Dillon, whose dad John was also a racing Wattie (John passed me in the run — it would become a theme).

On the section back to Kawaihae and the Queen K, I continued picking off people, including a few female pros and one or two female age groupers who were swimming and riding like pros :-), but I stopped myself short of really hammering — that’s what makes the power meter such a great tool if you know how to use it. I knew I was on my way to a good bike split, however, and sure enough I ended up notching a four-minute PR for the course. I also noticed very few bikes in the transition area, especially anywhere near my number, which meant I was doing pretty well in the age group (turns out I was 9th off the bike). But now I was venturing into the unknown — the longest run I  would have done since February or March.

It started off well enough, though immediately I could tell that it was substantially hotter than last year. The key was to keep my hydration and electrolytes going, as cramping in the heat is pretty much my standard MO. I had to reset my Garmin because my Auto Multisport mode apparently didn’t have transitions included, so the watch had stopped recording. I use the Garmin for pacing — mainly to hold myself back early on. The first mile was still a 7:0x, but it felt easy enough. That would change pretty quickly once I hit the sections on the golf course, where the spongy grass sucked all speed from the legs. Somewhere in mile 4, the first little leg cramp happened, but I took care of it pretty quickly with some water and an electrolyte cap. I had taken roughly 6-7 of those on the bike, and in hindsight that probably wasn’t enough.

Saw a few Wattie teammates out on course: first, the young Dillon that I’d been playing leapfrog on the bike with passed me in mile 3, and I didn’t think there was any way he was coming back to me. Then, by surprise, his dad John passed me in mile 4 and introduced himself. I kept John in sight for a while, and even re-passed him in mile 7 (after having my first solid set of leg cramps, which stopped me dead in my tracks). When I went past him, I joked that my teammates call me “a tenacious bastard.” Just before mile 9, as we headed out on the long, desolate out-and-back section of road, I cramped hard. I tried walking backwards, sideways — anything to use different muscles and work out the cramps. John went past me at this point and told me I’d need some of that tenacity — he was spot on.

Finally the cramps got worked out and I resumed running, until an even worse set happened 20 yards before the next aid station. It was so bad that I had to ask the volunteers to bring the water to me — I couldn’t move. I took my time, took a couple of electrolyte caps, and gradually I could start moving again. It was odd: for a few minutes I could run 7:20 pace, then all of a sudden I was stopped dead in my tracks, then the cramps subsided and I could run again. That’s pretty much how it went for the rest of the race. The last quarter mile I was determined to keep running no matter what, and almost every muscle in both legs was twitching, ready to lock up. But I finally made it over the finish line, and a PR is a PR, no matter how ugly parts of it were.

I met a few other Watties in the finishers area — here’s me with Mickey McDonald from Bend, OR, who crushed the bike with a 2:29 split:

watties honu

My Team Sheeper buddies Mike and Steve finished together, also having tough runs laden with cramping, so I wasn’t alone in my suffering. 🙂 Here’s the happy crew:

sheepers honu

Now it’s on to my Kona prep — if nothing else, I learned from this race how far I still have to go to get my run fitness and my hydration up to the task of double the distance and more than double the suffering. Bring it on!

A big thanks to all of my sponsors: TrainingPeaks, which I use religiously; Wattie Ink, which represents a great set of product sponsors and athletes (and has a very cool-looking kit); and, last but not least, Team Sheeper, the greatest combination of training program, training partners and friends a guy could ask for.

Another Week, Another Set of Live Rounds of “The Voice”

This week on “The Voice,” we’re down to 10 contestants, another two of whom go home tonight, so if nothing else our odds of predicting who’s going home are naturally improving week to week. But let’s look at the social media numbers again. First, overall “share of voice”:

thevoice-overall 2013-05-21 at 10.07.39 AM

Then, positive “share of voice”:

thevoice-positive 2013-05-21 at 10.07.19 AM

For the first week ever, both rankings produce the same bottom two, Amber and Kris.

If we look at week-to-week follower count growth, however, we get a different ranking:

Twitter handle Followers 5/14 Followers 5/21 Delta Percentage
@theswonbrothers 14750 19588 4838 33%
@michellechamuel 21305 27370 6065 28%
@josiahhawley 40894 50517 9623 24%
@dbradbery 45723 55430 9707 21%
@hollytmusic 13454 16273 2819 21%
@ambercarrington 14520 17149 2629 18%
@kristhomasmusik 12130 13966 1836 15%
@sarahsimmusic 25314 28828 3514 14%
@sashaallenmusic 16674 18985 2311 14%
@judith_hill 39953 43041 3088 8%

So the question is whether buzz or follower count (or neither) correlates better with actual results. So far, follower count has correlated a lot less well, so this week I’m going with buzz — especially since overall buzz and positive buzz line up this time.

But social numbers haven’t been right yet this season, which I’m sure make Kris and Amber happy to no end. 🙂

What Did We Learn from This Week’s “The Voice”?

Yesterday I looked at a number of different cuts of social media data and found a number of candidates for the Bottom 2 on “The Voice.” The interesting thing about the actual results was that none of the data I had access to correlated with the outcome, at least in a discernable pattern that you could build any sort of rule or model off of. I could try using a stats tool like R to find non-intuitive features that better predict an outcome, but that is probably like using a bulldozer to pound in a nail — there aren’t enough samples to make that approach meaningful. So I’m left with hypotheses:

  • Twitter isn’t a good proxy for voting behavior in the case of this show due to either a demographic skew or to the fact that the audience gravitates in general to other channels of interaction.
  • I haven’t found the right features yet. I used growth in Twitter followers as one potential proxy for “momentum,” and that correlated with one of the results — Vedo had by far the lowest percentage growth in followers week to week (he started of course with the highest number, so it gets harder to maintain the same growth rate), but in the case of the other ousted contestant, Garrett Gardner, we saw the highest percentage growth in followers, so that piece of data doesn’t correlate at all. Garrett, in fact, by any of the numbers I had access to or derived, should still be on the show. (Though I personally found his vocal performance on Monday weak, despite an interesting arrangement.)
  • The vote tallies among the bottom half of the contestants are actually fairly close (which the counts I had showed as well), so until we get to a point where we see either much greater volume or much greater differences between contestants, the best we’re going to do is random guesses over a larger pool of contestants with similar numbers. In other words, absolute rankings don’t work until you start to see larger gaps.

One thing is for sure — pure follower count is meaningless in this show (as it was in last week’s “American Idol”). A lesson for all who use follower count as a proxy for influence.