Power Meter Applications For Ironman
Training and Racing - Part II

We have learned from other sports (rowing, speed skating, running) that the fastest, most efficient and most effective race is by using constant power output. Most of the other sports have to use pace as a metric to assimilate approximate power output. However, through innovations in technology, power meters can be installed on bicycles to give us a very accurate and immediate measure of power output. The athlete that uses a power meter has the advantage of knowing if they are allocating too little or too much force on the pedals during a 112 mile time trial while still trying to preserve enough energy to run a full marathon to potential.

An athlete that makes the transition to power based cycling will quickly learn that riding at a consistent power output is a difficult skill to master as two primary factors present themselves during a long distance ride. The first factor is fatigue and the body’s inability to recruit the same amount of muscle mass as the ride progresses. The second is the inaccuracy of perceived effort while cycling on a course that is not flat. Athletes that lack experience controlling power output while cresting hills typically have frequent power surges that result in expediting muscular fatigue.

During training, the athlete is best advised to practice riding where they maintain the ability of sustaining the same power output at the end of the ride as the beginning of the ride. Obviously there is going to be an eventual decline in power output at some point if the rider continued to ride. The key then is to conclude during training the level of power output that could be sustained for 112 miles and still allow enough muscular energy to run 26.2 miles at running potential. Athletes that practice and master this will quickly realize that the amount of power that could be sustained for 112 miles will feel very easy during the first hour or two and will progress to levels deemed more difficult as the body fatigue’s. Athletes that attempt to ride at a fixed perceived level of effort throughout such a long ride will see power output decrease with each passing hour.

Technical Terms To Assess An Efficient Ironman Ride

Average Power – Average power is the simple average of power output generated over the span of 112 miles (or whatever distance completed in training). Since the power output generated is a constantly moving metric as the power output is recorded every second, there are unlimited ways to generate the same “average power” for a ride. For example; two riders average 200 watts for during a 112 mile ride. Athlete A was on a flat course and rode almost consistently at a power output ranging in between 180 watts and 220 watts with constant pedaling and no coasting. Athlete B on the other hand was on a hilly course and rode with a high rate of power variance cresting hills at over 300 watts and then gliding down the back side of hills at zero watt output. As we know that power spikes increase the rate of muscular fatigue as we approach maximum single repetition power output, athlete B did not ride as efficiently as athlete A even though the average power for both rides were identical.

Normalized Power – CyclingPeaks software (which is an absolute “must have” for analyzing ride data) has created an algorithm to assist in calculating power output that was “normalized” during the ride. Normalized power is a more accurate estimate of the power that a rider could have maintained for the same physiological expenditure if the rider did maintain a constant power output. It is believed that normalized power is a more accurate way of quantifying the actual intensity of a riding session.

Variability Index (VI) – As Ironman athletes, we desire to execute a ride that is a continuous and constant aerobic effort. The greater the variability in power output and aerobic output, the less efficient the ride is. Another important metric to analyze is the variability index which is nothing more than taking the normalized power number and dividing it by the average power number for an entire ride or segment of a ride. A ride with zero variability would be expresses as having a “VI” a 1.00. Rides with a VI of 1.02 to 1.04 would be considered very efficient and low variability. As the number increases further away from 1.00 the less efficient the ride. So a ride with a 1.08 or 1.12 or higher is less desirable than a ride with a VI of 1.02.

What is required to obtain a ride profile with a low VI is to ride in a smooth fashion with constant and consistent power output. What makes this difficult is holding constant power while the rider fatigues and also controlling a constant power output while riding up hills and attempting to hold power while descending on hills.

One last important point to make regarding the VI metric is that it is possible to have a low VI at the end of the ride and still not have an optimum ride. Many Iron distance athletes will look too closely at the VI and if they see a VI of 1.02 for the entire ride they will consider the ride a great success. It is possible to complete a ride with a low VI but still overextend the rider’s capabilities. Take for example a rider that through training has discovered that they can hold 200 watts and still run to potential for a marathon in an Ironman. The key then would be to hold a steady and constant 200 watts where NP and AW were as close to 200 as possible. But if the athlete had a final NP output of 210 watts and an AW output of 205 watts, the VI for the ride would be 1.02 (210 divided by 205). Looking at the VI alone would indicate a very smooth ride, which it was. However, the athlete rode too hard and generated the extra 10 watts during the ride which will impact running a marathon to their potential.

Finally, each metric alone can be misleading. It is the athlete that looks at the complete ride file and looks at how all the factors relate that is in a position to learn to train and race 112 miles effectively in an Ironman.

Assessing Ride Data

One very effective way to assess ride data is to first look at the overall numbers and then break the ride down into smaller increments. For longer rides that are Ironman specific training rides, breaking the ride data down into at least one hour components is very effective at recognizing trends during the ride. The following data files are actual files from Ironman races to learn from (albeit painfully for me) to demonstrate key points that could help you race more efficiently and effectively. Please note, that although there is a tremendous amount of data for each file, the purpose is to identify key metrics rather than achieve “paralysis through analysis.” We are not trying to solve a quantum physics issue but rather learn as easily as possible how to ride 112 miles as efficiently and effectively as possible and still allow us to run 26.2 miles to our potential.

EXAMPLE #1 - IRONMAN WISCONSIN – SEPTEMBER 11, 2005

Step #1 – Break the ride down into smaller components to look at trends. I like breaking 112 miles into six components of mileage that are just about equal and add up to 112 in total.

Step #2 – Look for positive or negative trends from the data. It’s easy to see some very negative trends and data points from this ride file. All key metrics have a decreasing trend line as the ride progresses from segment to segment. This clearly demonstrates poor pacing and an unrealistic assessment of actual vs. perceived riding ability. Normalized and average power continues to decrease as fatigue sets in. VI is far above acceptable limits as VI numbers exceeding 1.10 clearly demonstrate very inconsistent and unsteady power output. Cadence is far off from optimal Ironman race cadence to run effectively off of the bike. Speed decreases in proportion to the decrease in power output and cadence to very poor levels.

Step #3 – Assess the ride using the concepts of “The Four Systems” (see related article under the “Racing” section). The essence of the four systems is to execute a race where the athlete pushes as hard as possible without ever crossing important thresholds during the race. The four systems break down important physiological systems related to the aerobic system, the muscular system, the nutritional system, and the cooling system.

The Aerobic System

Based on training and testing numbers, an aerobic threshold number could be determined which was a heart rate cap of 135 beats per minute to ensure that the rest of the systems could work adequately. From the CyclingPeaks graphs on the journal page, the following data was obtained from the file. Note that a “sweet spot” aerobic zone of 15 beats from 120 – 135 should have been a very productive and efficient zone to complete the 112 mile bike. A heart rate of 135+ certainly is a danger zone that would lead to a much higher risk of physiological breakdowns as the race evolved.

It’s very clear that this ride profile was extremely inefficient from an aerobic standpoint. 23.6% of the ride was “too low” but more importantly, 44.0% was “far too high.” It’s the spikes in heart rate and power that will lead to races that are not up to our athletic potential more than anything else. Spending 44.0% of the ride time above an appropriate aerobic heart rate cap is as close to Ironman suicide as one could get.

The Muscular System

Based on training and testing numbers, a muscular endurance power output number could be determined which was a power output cap of 220 watts to ensure that the muscular system was not overtaxed and would allow for an effective marathon. From the CyclingPeaks graphs on the journal page, the following data was obtained from the file. Note that a “sweet spot” power zone of 40 watts from 160 – 200 should have been a very productive and efficient zone to complete the 112 mile bike. A power output of 200 – 220 is approaching red line and a power output of 220 watts + is certainly crossing over the muscular system threshold.

The Cooling System

On September 11, 2005, Madison, Wisconsin had an unusual weather pattern move through its region that resulted in a high temperature on race day of 91 degrees. As we know from research, as the outside temperature and humidity move upwards, athletic performance progresses downwards as it becomes very difficult for the athlete to keep core temperatures below effective thresholds.

So what do you get when you combine an ineffective aerobic strategy, an ineffective muscular strategy on a very hot day? You typically will get a catastrophic athletic explosion and that is exactly what happened in this case. 5:38:00 minutes into the bike at mile 94.35, I was off the bike and lying in a ditch trying to regain my bearings. Eventually I would re-compose myself enough to finish the bike and progress through a very painful 6:26:42 marathon. Do the numbers tell the story? Absolutely! The athlete that has learned their effective and efficient Ironman sweet spots ahead of race time AND properly executes on race day will put themselves in a position to race to their potential. Crossing thresholds of the FOUR SYSTEMS and executing a bike ride with highly variable power and aerobic output is a sure way to have an unproductive race.

RECAP - The ultimate goal of using a power meter is two fold; First, to figure out in training the amount of watts that an athlete can hold for 112 miles and still run 26.2 miles to potential, and second, to use this knowledge during the actual race to assist in executing the cycling portion of the race as flawlessly as possible.

EXAMPLE #2 - IRONMAN FLORIDA – NOVEMBER 4, 2006

Step #1 – Break the ride down into smaller components to look at trends. I like breaking 112 miles into six components of mileage that are just about equal and add up to 112 in total.

Step #2 – Look for positive or negative trends from the data. It’s easy to see some very interesting trends and data points from this ride file. Key power output metrics appear to have a decreasing trend line as the ride progresses from segment to segment. However, heart rate and average speed appear to have efficient trends. This is the result of having headwinds on the first half of the course and tailwinds on the back half of the course. In the third segment of 18 miles, it required NP of 209 watts and a heart rate of 130 to maintain a speed of 19.3mph. On the fifth segment of 19 miles, it only required NP f 176 watts and a heart rate of 131 bpm to maintain a speed of 22.3mph. There was a drop off in cadence below ideal limits as it moved down below 80 for the final 18 miles. Normalized and average power continues to decrease as fatigue sets in. VI is well within acceptable limits as VI numbers were below 1.06 the entire ride clearly demonstrating very consistent and steady power output. One theory to consider is that riding on a flat course like Florida makes it much easier to hold consistent power output and avoid power and aerobic spikes. It is much easier to get into a groove and hold it steady which is very efficient and effective. So not only is riding a flat course faster because of a lack of hills to slow down, but it is much faster to most age-group athletes because by default they don’t have as many opportunities to cross thresholds that are detrimental to their race potential. The course makes it much easier for them to race efficiently.

Step #3 – Assess the ride using the concepts of “The Four Systems” (see related article under the “Racing” section). The essence of the four systems is to execute a race where the athlete pushes as hard as possible without ever crossing important thresholds during the race. The four systems break down important physiological systems related to the aerobic system, the muscular system, the nutritional system, and the cooling system.

The Aerobic System

Based on training and testing numbers, an aerobic threshold number could be determined which was a heart rate cap of 135 beats per minute to ensure that the rest of the systems could work adequately. From the CyclingPeaks graphs on the journal page, the following data was obtained from the file. Note that a “sweet spot” aerobic zone of 15 beats from 120 – 135 should have been a very productive and efficient zone to complete the 112 mile bike. A heart rate of 135+ certainly is a danger zone that would lead to a much higher risk of physiological breakdowns as the race evolved.

It’s very clear that this ride profile was much more efficient from an aerobic standpoint. Only 1.4% of the ride was “too low” but more importantly only, 11.6% was “far too high.” This shows that there is still room for improvement to race to full potential. Time spent above this threshold only reduces our chances of an effective marathon. It’s the spikes in heart rate and power that will lead to races that are not up to our athletic potential more than anything else. Spending 11.6% of the ride time above an appropriate aerobic heart rate cap is still leaving room for improvement.

The Muscular System

Based on training and testing numbers, a muscular endurance power output number could be determined which was a power output cap of 220 watts to ensure that the muscular system was not overtaxed and would allow for an effective marathon. From the CyclingPeaks graphs on the journal page, the following data was obtained from the file. Note that a “sweet spot” power zone of 40 watts from 160 – 200 should have been a very productive and efficient zone to complete the 112 mile bike. A power output of 200 – 220 is approaching red line and a power output of 220 watts + is certainly crossing over the muscular system threshold.

The Cooling System

On November 4, 2006, Panama City Beach, Florida had an unusual weather pattern move through its region that resulted in a low temperature on race day of 43 degrees and a high temperature of 71 degrees. As we know from research, as the outside temperature and humidity move upwards, athletic performance progresses downwards as it becomes very difficult for the athlete to keep core temperatures below effective thresholds. These race day temperatures allowed athletes to keep cool and allowed all blood flow to move towards aerobic, muscular and nutritional systems rather than the cooling system.

So what do you get when you combine a more effective aerobic strategy, a more effective muscular strategy on a very cool day? You typically will get a race that is much closer to true athletic potential. In this case a 1:14:10 swim combined with a 5:33:30 bike and a 3:52:27 marathon resulted in a new PR of 10:48:12.

There is still room for improvement, so as fitness increases year over year along with better race execution, one should hope for continued personal records (PR’s) as we move towards our true athletic potential.

Frequently Asked Questions

Question #1: What three metrics are most useful in determining a consistent power output?

Answer: The three most useful metrics available for determining a consistent power output are normalized power (NP), variability index (VI), and average power (AP). Combining these metrics with a knowledge of our muscular/power output threshold will allow an athlete to race most efficiently and effectively.

Question #2: Why should I analyze my data in segments? Won’t looking at the totals tell me the same thing?

Answer: Analyzing the data in segments tells a more accurate description of the ride profile as trends emerge. This allows the athlete to quantitatively assess whether a consistent power output strategy was applied during the ride. If power metrics are decreasing segment over segment, it usually demonstrates that the athlete started out too aggressively or had an unrealistic assessment of their athletic abilities.

Question #3: Are perceived efforts and power outputs perfectly correlated?

Answer: Perceived efforts and power outputs are not perfectly correlated. Athletes often underestimate the amount of power that they are generating either at the beginning of rides or while climbing hills. This often results in them riding above their muscular system power thresholds thereby reducing their chances of racing to their potential and running an effective marathon.

Question #4: What is the most important assessment tool when riding with power?

Answer: The most important assessment tool when riding with power is the ability of dissecting the ride file. There is no better way of analyzing a ride file other than using CyclingPeaks software as it allows the athlete to obtain all key metrics very efficiently and clearly.

Question #5: A VI close to 1.00 always means that the athlete rode an efficient ride?

Answer: Not necessarily. It is possible that the athlete consistently rode above their abilities to run the marathon to potential. If the athlete rode the entire 112 miles generating only 5 to 10 watts above their efficient target wattage, it may result in a faster bike split much a much slower run split thereby negating the benefits of the faster ride.