A tecnologia no remo
(artigo em inglês)
It’s easy to agree with the statement that measuring performance in rowing is an important part of coaching. Measurements provide objective feedback to coaches and athletes facing a seemingly simple optimisation problem: how to move the boat fastest from the start pontoon to the finish-line. The crew moving their boat fastest over the race distance wins the race. In the following, we will refer to this as the rowing optimisation problem.
Faced with the task to measure performance in rowing, there’s usually a tradeoff to be made between how easy it is to measure something and how much insight can be gained from the resulting measurement data. This article deals with different aspects of measuring performance in rowing. For this purpose, the article will present the properties of measurement a measurement, followed by a discussion of various measurements commonly conducted in rowing and how those relate to the above stated rowing optimisation problem.
What is a useful measurement?
Sports is unthinkable without any kind of measurements. In the case of rowing, the two basic measurements dealt with are time and distance. The history of measuring aspects beyond these two basics goes back to as far as 1940 [1]. In order to support effective coaching, measurements should have several desirable properties. Good measurements should be:
- accurate and precise,
- comparable,
- feasible,
- understandable,
- have a clear relation to the rowing optimisation problem.
The next sections will discuss these properties in detail.
Accuracy and Precision
The value of a rowing performance measurement is directly related to its accuracy. Accuracy refers to the difference between the “true” and measured value of a parameter. When this difference is large, a measurement is said to be less accurate. Related to this is the term precision, which describes the difference in repeated measurements under the same conditions [2].
Accuracy and Precision, source http://en.wikipedia.org/wiki/File:Accuracy_and_precision.svg
If a measurement can’t be conducted in a reliable and accurate manner, it’s utility quickly diminishes because coaches and athletes can’t rely on it. This is even more important when measurements are used to make fundamental decisions like crew selection. However, for each type of measurement there’s a trade-of to be made between the desired accuracy and the effort required to conduct such a measurement. Fortunately enough, most parameters that we deal with in rowing can be obtained with sufficient accuracy and precision using reasonable effort, if the right kind of technology is used. There are many more aspects to consider when taking into account measurement errors [3], but what matters for interpretation of measurement data is how these errors affect the comparability of measurements.
Comparability
Comparability is not only a question of representation (e.g. graph, metrics etc.) but rather about the inherent errors associated with each measurement and whether to measurements can be compared when they were taken in different environment conditions. Measurements are more easily compared when they have good accuracy and precision and are resilient to uncontrollable changes in the environment. Precision is very important as it determines the range in which we need to treat two different measurement values as “similar”, i.e. there’s not statistically significant difference between two values. To illustrate this, assume we can measure boat speed with a precision of 0.1m/s. Now, let’s say we have two measurement values at 4.9 and 5.0 m/s. Is one boat significantly faster? Probably not, because both boats may have actually had a “true” speed of 5.0 m/s and we may have experienced a measurement error in one of the measurements. Again, this is an oversimplified model of “measurement precision” and what it means for two values to be significantly different. Accuracy is important when a measurement is compared to a different parameter or the measurement is used in a model. Sticking with the example of boat speed, when we use the speed to extrapolate the 2000m race times, measurement accuracy is important as any deviation from the true boat speed will lead to a large error in the 2000m time extrapolation.
Comparing different acceleration graphs
The next important aspect of comparability is a measurements resilience to uncontrollable changes in the environment like water temperature, wind conditions etc. As rowing is an outdoor sport, we seldom have the luxury of reproducible, controlled conditions. The more these uncontrollable changes affect a type of measurement, the more difficult it is to compare two measurements taken in inevitably different conditions. This is especially true when the exact influence of uncontrolled conditions is not known or these conditions can not be measured accurately themselves (as is the case with e.g. water conditions).
Feasibility
Even when a measurement is accurate and comparable, it’s not going to be of any use if it’s so difficult to obtain that it is not measured in the first place. The easier it is to obtain a measurement, the more likely it is to make measuring a regular habit.
Instrumented Oar and Gate, source http://www.rudern.de/nachricht/news/2012/02/23/messtechnikertreffen-am-160212-in-hannover/
This is important because regular measurements provide valuable feedback to coaches and athletes and will foster a thorough understanding for the data, which in turn helps developing insights that may ultimately lead to a better solution to the rowing optimisation problem. From an athletes perspective, getting regular feedback on measurement data is very important to develop the ability to take deliberate influence on rowing performance by varying motion sequence and power application. This requires that athletes develop a mental model of how their “feeling” for the rowing motion connects to the measured outcome. This leads to the next important characteristic of a good measurement: understandability.
Understandability
There’s two sides to understanding a measurement. First and foremost, what does the measurement mean (what is measured?)? And second, what influences the measured value (what does an athlete need to change to affect the outcome)?
Comparing motion sequences to understand their effects on boat acceleration.
While understanding what is being measured may sound easy, first hand experience tells us that this is not always the case and a misunderstanding of the basic relations between time, distance, speed, acceleration and forces on the boat may easily result in misleading conclusions. Another aspect to understanding a measurement are the underlying dynamics of the measurement value (i.e. how does it change over time, how is it related to other parameters). Once coaches and athletes understand the meaning of a measurement value, the next step is finding out how to affect this value using a change in motion sequence and power application.
Relatedness
This leads us to the last important property of a good measurement: once we know what a measurement means and how to affect it, coaches and athletes need to decide on the desired outcome for such a measurement in the light of the rowing optimisation problem and implement an appropriate strategy to achieve it. This is not an easy task, given that physiological and mechanical constraints may result in complex interactions with other parameters.
Main forces on a rowing boat, source V. Kleshnev: Boat acceleration, temporal structure of the stroke cycle, and effectiveness in rowing, Proceedings of the Institution of Mechanical Engineers 2010
Most notably, some parameters may have a clear relation to the rowing optimisation problem, such as boat speed, while other parameters relation to the rowing optimisation problem is complex and may involve a number of parameters that have not been measured simultaneously (i.e. the interaction of gate and stretcher force).
The different levels of Measurement in Rowing
After the previous discussion of desirable properties of measurements in rowing, we will now look at measurements that are commonly performed in rowing and how well these measurements satisfy the above-mentioned properties. For this purpose, we will group them by their level of feasibility and insight that they offer into the rowing stroke.
Level 1: Visual Analysis
Visual analysis is the most basis form of everyday measurement and coaching in rowing. Following a set of guidelines for how the supposed “optimal” motion sequence of the athletes should look like, coaches look for deviations from that role-model and work together with the athletes to achieve a correct performance of the motion sequence. While biomechanic modelling indicates that certain patterns in motion sequence prove to be more effective than others (see [4] for a comparison of different rowing styles), the “optimal” motion sequence is a highly debated topic and it is not uncommon to see very successful athletes deviating significantly from the postulated role-model. Leaving aside these issues, effectively using visual analysis in coaching proves challenging in the face of the problems it has to achieve the properties of a good measurement.
One of the problematic aspects of visual analysis is that it lacks precision and detail. Visual analysis is most often of qualitative nature, not based on quantitative data. Even when effort is made to quantify certain parameters (e.g. angle between upper body and legs), the procedure to derive such data is unprecise and cumbersome. Also, comparing data based on visual analysis is very difficult even when recorded on video, since the observer usually does not have a fixed position relative to the boat and so the angle of observation or distance to the boat keeps constantly changing.
Visual analysis lacks detail, because it does not allow direct insight into why a boat it is moving. In fact, visual analysis is not measuring any physical parameter that is directly related to moving the boat forward, it is merely observing outside effects. Any changes to the athletes motion sequence to conform with a role model are speculative at best and without further measurements can’t be proven to improve boat speed. On the upside, visual analysis is very easy to conduct and thanks to the widespread availability of quality video-cameras in smartphones and tablets very cheap.
Even though visual analysis is problematic when used alone, coaches should keep in mind that it is the most important tool to convey to their athletes how they should effect a desired change in a different measurement parameter. Athletes need to perform a certain motion sequence, and changing that is their primary tool for solving the rowing optimisation problem. In order to make any other kind of measurement understandable, connecting it to visual analysis is tremendously useful.
Level 2: Speed
Speed is the raw form of the rowing optimisation problem: travelling a fixed distance in the shortest time possible. However, speed is also the perhaps most misunderstood measurement in rowing. To help clear out this misunderstanding, we first need to define what “speed” means in the context of rowing. While this may sound like an academic sand table exercise, it is highly relevant. There are three different “kinds” of speed that we need to discern based on what they mean. Speed over a distance, Speed over a time and instantaneous speed. When we are talking about the rowing optimisation problem, we are looking at speed over a distance. The distance is fixed, so what is measured is time to travel this distance and then the average speed is calculated based on that. So ultimately, this is the metric that rowers need to improve. On a side note, it is important to point that speed and velocity are not the same thing. Velocity is a vector, e.g. it also has a direction, whereas speed is only a scalar. Therefore, velocity is basically “speed with a direction”. When we refer to the rowing optimisation, it is in fact speed that we are interested in – speed along a straight line from start to finish. As anyone who has ever tried to precisely steer a boat through an albano buoy system knows, that’s unfortunately not how it works in the real world, so the values of speed and velocity can diverge.
Speed over a time is not very relevant in rowing and is calculated by measuring the distance travelled in a fixed time interval. What however is very relevant in rowing is instantaneous speed and its relation to speed over a distance, i.e. the rowing optimisation problem. Rowing boats do not move at constant velocity, as can be evidently observed by boats constantly pushing forth the bow tips during a race.
Bow tips of rowing boats in a 2000m race.
Instantaneous speed is often used to make a projection for speed over a distance. A useful form of such a projection is the speed over a single stroke-cycle, i.e. the distance per stroke divided by the duration of the stroke. This allows coaches and athletes to see any changes in “average” speed that the boat makes on a stroke-by-stroke basis. This type of calculation is also what most rowers are used to based on the visual representation of speed on rowing ergometers.
In terms of measurement accuracy the longer the speed and time being measured the more accurate and precise the measurement will be. Even though the measurement errors when using a stopwatch and manual “finish line” detection are quite large, their effect tends to be low compared to the long distances and times travelled in rowing. When looking at speed on a stroke-by-stroke basis however, such measurements cannot be accurately and precisely made by hand, which makes measuring this kind of speed more difficult because measurement hardware in some form is required.
Measuring speed on a stroke-by-stroke basis however is much more demanding in terms of measurement accuracy and precision because the distance traveled per stroke is in the lower 10m range and times in the few seconds range. This is why e.g. even high grade GPS is not suited for stroke-by-stroke measurement of speed, an aspect that many GPS based systems try to hide by using some form of a “smoothing” algorithm. Unfortunately, that means that typical devices used in rowing today can not deliver this type of highly desirable stroke-by-stroke feedback for athletes (was this stroke better than the last one?). Future devices that use a combination of a hull mounted impeller, GPS and inertial sensors should be able to alleviate this.
Aside from these technical issues, speed is also very prone to be affected by uncontrollable environmental conditions, most notably wind and water conditions [5], which makes it hard to compare two speed measurements that were not taken under the same conditions. Nonetheless, speed remains the most important measurement in rowing performance as it is the raw form of the rowing optimisation problem. Coaches and athletes need to keep this in mind when looking at “lower-level” measurements like acceleration and force measurements. Rowing is not a single-dimensional optimisation problem, improving one parameter without simultaneously ensuring boat speed improves (or could potentially improve when combined with other changes) will ultimately not lead to the desired outcome.
Level 3: Acceleration
As we’ve seen in the discussion of boat velocity, rowing boats do not move at constant velocity. Information on the exact changes in boat velocity is highly valuable to derive insights into how boat speed can be improved. Assuming a crew that perfectly reproduced the same motion sequence and power application under constant conditions, we could observe that boat velocity periodically changes around a constant stroke-by-stroke velocity.
These changes in boat velocity are called acceleration that occur as a result of the forces acting on the boat(e.g. drag, gate force etc.). Because acceleration has such a direct relation to boat velocity and captures the result of all the complex interactions of forces acting on a boat, it is a highly important measurement. Thanks to the proliferation of smartphones with built in acceleration sensors, coaches and athletes can measure boat acceleration with sufficient accuracy and precision by simply attaching such a device to the rowing shell.
A typical boat acceleration profile captured using a smartphone.
One important advantage of boat acceleration over speed is that boat acceleration patterns can be compared even when changes in the environment occur. This is especially true when sampling a “typical” acceleration pattern from many strokes. While changes in the environment like wind or water temperature affect the boat acceleration, their impact is mostly reflected in a quasi-linear offset (this is not strictly true, but close enough for most practical purposes). What remains consistent is the “finger-print” of the acceleration pattern that a crew produces.
Typical acceleration pattern of a SMB 1x rower. The measurements were taken 2 months apart in Frankfurt, Germany and Brisbane, Australia in different boats and very different climate.
Boat acceleration is also very easy to understand for athletes, since it is proportional to the propulsive force acting on the boat. This means that any change in the propulsive force that the athlete generates is directly reflected in boat acceleration. This is very useful when combined with powerful feedback mechanisms such as sonification, that allow the athlete to perceive these measurements in realtime.
Level 4: Individual Forces, Angles, Positions
While acceleration is highly useful as a measurement in rowing, it is an aggregate metric for the whole crew and does not allow individual insight into the contributions of each athlete to the propulsive boat force. However, this type of information is highly relevant for crew selection and synchronisation.
To gain deep insight into the rowing stroke and support individual improvement in crew boats, measurements of parameters at each seat in the boat are required. Whereas acceleration was the change in boat velocity and reflected the end result of all forces acting on a boat, this type of measurement gives coaches and athletes into those forces that produce the observable acceleration.
A clear advantage of these individual measurements is that they are very comparable, although interactions between individual crew members in the same boat must be considered. This is why such parameters, especially when they allow conclusions on individual power application in a boat are often used in crew selection on national teams.
Unfortunately, these types of measurements have been historically difficult to conduct and require special sensors and procedures to produce accurate and precise measurements. With recent advancements in measurement technology and wireless communication, this is about to change and the next few years will likely see some exciting advancements in this sector.
Working with individual athlete data in a boat however is challenging. The mechanical interactions in the rowing boat are still not fully understood today (e.g. the influence of vertical seat force [6]), although the scientific literature has proven a set of basic relations between forces acting in the rower-boat system. Through these complex interactions, relating such a measurement to an improved solution to the rowing optimisation problem is a process driven by experimentation and validation. This makes it even more important that such measurement technology becomes widely available and easy to use.
Conclusions
The article presented the rowing optimisation problem and how measurements help find coaches and athletes find better solutions to it. The article presented desirable properties for measurements that make them more useful in the context of rowing. Finally, we presented measurements commonly used in rowing, their properties and relation to the rowing optimisation problem.
We hope this article provided some insight into the aspects of effectively using measurements in rowing. Rowing in Motion is dedicated to provide the rowing community with tools that make producing and analysing measurement data as easy as measuring stroke-rate is today. Why don’t you give using measurements a try to improve the effectiveness of your training?
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