ConnectStats let us apply basics statistics technics to analyse our fitness data. We use these techniques to answer questions about the activities. How well did I do on this run? Is my stamina improving? Did I push myself more today that last week?

Raw Data

Before doing any analyses, let’s review the raw data we have access to. ConnectStats relies on the collection of the data is done with a garmin device and a collection of sensors.

The raw data varies by activity type and device.
For outdoor activities, the raw data will be gps coordinates, a timestamp, speed and values from different sensors: Heart Rate beat per minutes, cadence (legs or pedal), Power delivered on the bike, and sometimes more advance running dynamics like Vertical Oscillation, ground contact time. For swimming the data collected will be the time for each length and the number of stroke.

Here is an example of what the raw data looks like

Depending on the activity or the device the raw data will be collected at fixed intervals or at different intervals trying to reduce the amount of data saved. If you move in a straight line for 5s at constant speed, it isn’t necessary to collect the points every seconds as they can easily be interpolated.

From this raw data, there are two main directions for the analysis we can do. The first is analysing a single activities and the second is analysing summary of each activities over time.

Focus on a single activity

The summary statistics are quite simple. Mostly we will want to look at the average of the different measure, maximum and minimum. Where it gets more interesting is to look at the series of data. As for most statistics analysis a first phase will be cleaning the data.

Data Cleaning

Let’s look at the graph of the data collected by the gps. You can see it is quite noisy, there is also large part of the data that is not really interesting to look at to. Some is gps noise, area with bad reception, pause due to stop lights,

To clean the data, we can first use assumption on expected constraints on the data. For example, define a minimum speed considered valid running speed, or a minimum valid heart rate to remove unreasonable spikes. Another technique used by connectstats is to filter points that have unrealistics acceleration.

The last smoothing technic we can apply is a moving average of a few points. Usually the app will use 5 points moving average for data, but it can be controlled in the sliding left settings window.

In the case below the graph start to be more readable now, especially with the 2 minutes moving average overlay, which shows the two short faster run intervals around 30min and 40min.