Archinisis Blog: Fresh Tracks

What if you could customize the performance parameters spreadsheet on the webapp? What if you could choose exactly which plot goes where, and select which relationships each one highlights? The good news is that all of this is now possible. The cross-country skiing performance parameters display has been improved to offer greater usability and flexibility. Below you'll find an overview of the new parameters and plots available on the webapp, giving you more control and a clearer view of your performance data.

New Parameters

Elevation based performance insights

We introduce new ways to visualize elevation gain, giving a clearer understanding of how terrain affects technique and performance. Available are two different displays of elevation gain: 1) elevation gain per cycle and 2) elevation gain per minute. This is nothing else than the elevation gain per cycle normalized by cycle duration, which allows a comparison across different cycle durations (e.g., cadence) and sub-techniques.

Screenshot of the elevation gain for each cycle, color-coded by sub-technique

Figure 1 illustrates the athlete's elevation gain per cycle and per minute with respect to total skiing time. Each bar is one cycle, the colours represent the sub-technique. Blue = Gear 2 / V1. Orange = Gear 3 / V2. Yellow = Gear 4 / V2 alternate.

Lateral Excursion

A second set of new parameters helps coaches understand skiing efficiency better in the skating technique: the lateral excursion. This parameter measures how much the athlete moves side to side during each cycle (see Figure 2 just below for an illustration).

Figure 2: Lateral excursion. The blue line is the trajectory the skier's centre of mass is doing. The forward's direction is towards the right. The yellow vertical lines mark the moment of maximum lateral excursion on either side and the black dots mark the start of a movement cycle (corresponding to the start of the pole push).

This lateral movement is necessary to generate forward propulsion, as the skier must push against the snow at an angle. However, it also increases the total distance travelled. Even a small extra movement of one or two centimetres per cycle can add up over time. Over a 2 km course, we have observed differences between athletes amounting to several meters.

For the first time, this parameter can now be measured accurately. We have not found any previous research on this topic, but our observations show that faster, more efficient athletes, cover significantly less extra distance without necessarily reducing lateral excursion. In other words, they achieve forward speed with a more optimized lateral excursion.

For the moment we provide three measures of the lateral excursion: 1) total left-right movement, 2) speed of lateral motion, and 3) total extra distance covered. A good and fast skier is able to have small values for each of these parameters.

Screenshot of the extra distance covered per cycle

Figure 3: Extra distance covered each cycle because of the lateral motion. Each bar is one cycle, the colours represent the sub-technique. Blue = Gear 2 / V1. Orange = Gear 3 / V2. Yellow = Gear 4 / V2 alternate.

Fully interactive parameter plots

Computing Averages

For more reliable feedback it is important to not use single cycles but look at averages. For example, considering all cycles of a 50 m uphill stretch. For this purpose, the user can now select any cycles using the box or lasso select tool and display averages and standard deviations in the corresponding table. See the video below for an example.

Selecting which data to display

With so many new parameters it is easy to get lost. We don't want to show too much data. But each coach may have different needs and wants to see different data. So, we have added the possibility to fully customize the cycle performance parameter plots. It is possible to interactively change what data is displayed in each of the four plots. Moreover, the x-axis can be changed, too. It's not always convenient to show data with respect to total skiing time. For specific uses one may want to display the cycle count or total distance covered, instead of the total skiing time. Of course, all data is still coloured according to the sub-technique used.

Explore Correlations

Two additional plots, also fully configurable, allow plotting one parameter against another. This helps to further understand correlations and dependencies between parameters. Different clusters coming from the different sub-techniques are also clearly visible, further allowing to visualize key differences between athletes or between laps.

This flexibility makes the analysis process more intuitive and tailored to individual needs.

Continuous Data

We also wanted to give our expert users a better understanding on how exactly the athlete moved. For this reason, we give more space to the continuous data. This is data which is measured 200 times per second. In cross-country skiing, the three key data sets are: instantaneous skiing speed, sensor inclination (e.g., upper body inclination), lateral excursion.

Instantaneous Skiing Speed

The instantaneous skiing speed shows the speed of the athlete's centre of mass. The high time-resolution (200 data points per second) allow to see each tiny movement. We can observe speed increase from pole or leg pushing and speed decrease from the swing and recovery phases. It's so detailed that it is even possible to see "slips" in classic skiing due to inappropriate kick wax.

Figure 4 highlights the athlete's instantaneous ground speed. The grey area in the background shows the elevation profile.

Zooming in a section shows the speed fluctuations from the different propulsion, swing, and recovery phases.

Graph showing the instantaneous skiing speed zoomed over a section of 35 seconds

Figure 5 shows a zoomed section of the instantaneous speed (black line). The orange dots mark the start of the cycles.

Upper Body Inclination

The upper body inclination shows how much the upper body is "bent". Because of where the sensor is worn, an inclination of 20 degrees is reached when we are upright. Angles increase and reach over 110 degrees when the athlete goes in a tucked position. For an easier interpretation of the results the webapp automatically classifies the terrain into uphill, flat / mixed, and downhill and colours the graph accordingly. For the downhills, the inclination is especially useful to see when the athletes are in a tucked position. For straight and uphills, one can see how much upper body movement there is and how it changes between sub-techniques and over time (e.g., due to fatigue).

Figure 6 shows the inclination of the sensor or upper body with highlighted terrain.

Lateral Excursion

We have already seen the cycle parameters derived from the lateral excursion. This plot now shows the entire lateral excursion. Changes of lateral excursion between sub-techniques are especially visible. When the athlete has no lateral movement, for example in the downhill parts, this value is undefined and set to zero.

Figure 7 captures the lateral motion. Depending on how sub-technique was changed and the chosen sub-technique itself, cycle starts don't always happen on the same side.

Summary

This update makes the whole analysis process more user-centric, giving coaches the freedom to explore performance data in the way that suits them best. The kinds of performance analysis that can be done have now taken new depths; analysis possibilities are nearly endless. By refining our visual analytics tools and prioritizing user customization, Archinisis continues to advance performance analysis technology. We remain dedicated to helping the cross-country skiing community gain deeper insights, improve training strategies, and achieve their goals.