The File Viewer’s Scatter Graph is a great tool for exploring relationships between different data channels that may be hard to spot in the time-series graph. With the addition of the newer Running Dynamics, Cycling Dynamics, and SmO2 data channels, the Scatter Graph can even be used to evaluate an athlete’s technique and efficiency.
Comparing the movement focused data channels to the effort-based data channels, such as power, pace, or heart rate, may show at what effort an athlete’s form starts to break down or where an athlete is most efficient. The Scatter Graph can also be used to analyze and compare intervals within a workout. Looking at the variability between intervals can show if the workout was performed properly or not.
Using the Scatter Graph For Running Analysis
The following three graphs are examples of relationships that can be seen in the Scatter Graph that might not be as obvious when the same data is plotted over duration or distance. This particular workout was a half marathon trail run, and we start by looking at the relationships between Pace on the X-Axis and Cadence, Stride Length, and Ground Contact Time on the Y-Axis.
From these graphs we can see that this athlete increases their pace by taking longer strides as opposed to increasing their cadence; and that Ground Contact Time, as expected, decreases at higher paces. Using this information a coach (or self-coached athlete) may decide to incorporate specific running drills into the athlete’s training based on the demands of an upcoming event.
The relatively flat shape of this Pace versus Cadence graph shows that there is very little change in running cadence, even as the pace increases.
When we look at Pace versus Stride Length there is an obvious trend upward to the right, which indicates a highly correlated relationship between pace and stride length; as stride length increases so does pace.
We can also see that ground contact time decreases as pace increases. This can been seen in this Pace versus Ground Contact Time graph by the downward to the right trend of the points in this graph.
Using the Scatter Graph to Analyze Cycling Workouts
The Scatter Graph can be used to analyze cycling workouts as well. This graph shows the relationship between Grade versus Cadence for a bike workout on a rolling course that has a few steep hills. This particular graph shows a significant drop in cadence when the grade goes above roughly 6.5 percent. This relationship can be difficult to spot in the time-series graph, but is very evident in the Scatter Graph.
This could be an indication that this cyclist comes out of the saddle at steeper grades, which could be due to poor pedaling technique or inadequate gearing for the course. A coach can use this information to tailor an athlete’s training for an upcoming event, or help with optimal equipment choices.
The peak two-minute power for the workout has also been highlighted in this graph. When there is a high variation in the data it may be difficult to recognize any useful information in the Scatter Graph. Highlighting a specific area of interest from the workout adds an extra dimension to the graph that can help surface meaningful information. Once highlighted, we can see that the Peak two-minute power occurred on the steepest grades of the ride and with a narrow range of cadences.
There are many relationships that can be analyzed with the Scatter Graph. Here are a few suggestions to start exploring:
- Pace versus Cadence
- Pace versus Stride Length
- Pace versus Ground Contact Time
- Pace versus Ground Contact Time Balance
- Pace versus Vertical Oscillation
- Pace versus Power
- Ground Contact Time versus Vertical Oscillation
- Cadence versus Ground Contact Time Balance
- Power versus Power Balance
- Power versus Cadence
- Power versus Elevation
- Grade versus Cadence
- Heart Rate versus Power
- Heart Rate versus Cadence
Comparing Intervals Using the Scatter Graph
The Scatter Graph can also be used to compare intervals within a workout. Any lap or peak ranges that are selected or highlighted will be color-coded on the graph. This allows you to analyze how specific efforts from a workout relate to each other. Just like the time-series graph, selected ranges will be colored in red, and the highlighted range will be colored in blue.
This Scatter Graph shows Power versus SmO2 (muscle oxygenation) for a trainer workout. The four work intervals are all selected, and are shown in red. The second interval was then highlighted so it is shown in blue. Power and SmO2 initially appear to be highly correlated for all four work intervals. But when the second interval is highlighted, the variation in SmO2 between intervals becomes more apparent. In this case we can see that the second interval had consistently lower SmO2 values than the other three intervals.
The Scatter Graph is available to coaches and athletes with a premium subscription, and can be added to the File Viewer from the Chart Library. From there, all the graphs and charts can be rearranged and resized to fit your needs. The data channels available in the Scatter Graph are dependant on the data that was recorded by the device, so not every workout will include all the variables depending on the type of equipment you used. Additional help on using the Scatter Graph can be found here.