![]() For now, I just want the best analytics.ĭifferent programs have different things that I like, I've actually even made my own app where I download my ride data from strava and I get myself a performance management chart, power duration curve and ride analytics. I don't race, and I am not concerned with getting my FTP to a particular number. In less than 2 years I've gone from being completely off a bike for 10 years due to disc herniations and chroninc sciatic pain to consistently riding 300-400 miles per week (mostly pain free). I'm open to the possibility that needs will change over time, but for now I really want to do my own thing and be able to analyze and track the results. However, I hate the trainer (aka "the torture machine") and really only see myself using it on days when the weather totally prevents me from riding outside.Īt the end of the day my greatest need in a training platform is ride analytics and fitness tracking. Yes, it could be done by doing more on my trainer. Therefore, following a rigid training plan based on pre-planned workouts is not a good option IMO. Thanks in advance for your feedback!īackground: I do 99% of my riding outdoors and have limited ability to plan workouts ahead of time because of the dynamic Florida weather. No complaints, but the analytic tools are pretty basic. I currently have the paid version of Strava as my only cycling platform. Trainer Road, Training Peaks, Strava, etc.), which one has the "best" analytical tools? Stay tuned.For those who are familiar with the various training platforms (i.e. It wouldn’t be perfect, but it would be better than a zero. If a high correlation between training load and TRIMP scores is typical for a wide range of users, it would be possible to automatically make a good guess for the training load of a ride simply based on heart rate data. Sometimes a power-meter using cyclist will go for a ride without a power meter but will then want to assign a training load value to the ride (so that the data for the training load graph will be complete). This chart is for a set of my rides, and it has a correlation coefficient of 0.96. ![]() This makes sense, because they’re calculated in different ways from different data - power data measures what the body does, heart rate measures how the body feels about what it’s doing - yet there can be a noteworthy correlation between the two. Take a look at this Wolfram Alpha graph to see how the intensity factor varies over the range of the heart rate - if the average heart rate is the resting heart rate, the HR ratio is 0 if the average heart rate is the maximum heart rate, the HR ratio is 1.Īt the moment TRIMP scores are being treated as completely different to the training load being assigned to rides with power data. This is the same formula as used by Golden Cheetah, which uses the model of Morton and Bannister with the coefficients given by Green et al., although I haven’t found primary sources for this research yet.Įssentially, it’s duration multiplied by an intensity factor based on heart rate. TRIMP = time × HR ratio × 0.64 × exp(sex factor × HR ratio) HR ratio = (average HR − resting HR) / (maximum HR − resting HR) Sex factor = 1.92 if male, or 1.67 if female There are a variety of ways to calculate TRIMP, and Cycling Analytics uses the following formula: This isn’t ideal, especially if you have one ride with power data and a hundred with heart rate data, so something will have to be done about this. Note that the STS and LTS - short-term stress and long-term stress - numbers can’t be compared between power derived numbers and heart rate derived numbers.Ĭycling Analytics currently always uses power data when it exists, and falls back to using heart rate data when only it exists. Do you have any suggestions for what could fill that gap? This is similar to what a user with a power meter would see, except there is a big gap in the middle where the power curve is shown. Therefore, a user’s rides page will contain more enlightening monthly summaries, and the main training load chart page is useable. Once TRIMP scores have been calculated, Cycling Analytics uses TRIMP scores to generate training load charts. ![]() The formula used (described below) relies on the sex, resting heart rate and maximum heart rate, so users must enter these values before TRIMP scores are calculated. TRMIP, or training impulse, is a metric based on heart rate that is designed to capture the stress of an activity in a single number. Therefore, Cycling Analytics is now calculating the TRIMP score for rides, which, in turn, can be used to generate the training load graph for users who don’t use a power meter. Since a lot of “serious cyclists” don’t have power meters, I have received a number of requests to do more with heart rate data. Better heart rate monitor support 11 October, 2012 by David Johnstone
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