Subjectivity in analytics
As a coach for both track & field and soccer, I can personally attest to the latter being a good deal more challenging to quantify. Track & field, of course, is ruled by only two quantities that are simple to measure: time and distance. We choose a distance, and the runner that covers that distance in the least amount of time is better by definition. This makes it quite easy to rank performances and track improvement over time. Note, however, that we did have to choose a scale for measurement. For example, we could have measured the distance around the track in meters, feet, or yards. The same choice exists for high jump, long jump, and pole vault. Once that choice is made, however, we view track and field as an entirely “objective” sport.
Soccer on the other hand requires capturing more abstract quantities such as a players decision making ability, their communication skills, and even their psycho-social characteristics. These quantities are subjective in the sense that different evaluators (coaches) may very well rate the same player performances very differently . In other words, the reason for the “subjective” label is that no natural scale with which to measure these quantities. However, there is no reason not to develop such a scale and apply it to characteristics like “decision making”. This is precisely what we have done at DSA Labs. We give coaches and players the ability to define their own scale of measurement for any player characteristic. Once defined, that scale can be used to perform objective player analysis, just as we do with a yardstick or stopwatch.
For example, one can characterize a decision in soccer with a simple measuring device: good or bad. The definitions of “good” and “bad” must be supplied by the coach, of course, but once those criteria are set, this method of measuring decision making in soccer is scarcely different from the “meter” in track. So long as it’s applied uniformly and consistently it works as an objective measuring stick for decision making. Moreover, we have found that uniform, consistent application of this type of rating system is actually much easier than might be expected. In other words, player measurements performed in this fashion are repeatable over time and with high precision.
In summary, abstract quantities can be measured and used in objective analyses in sports. The challenge is to develop, and consistently apply, a scale of measurement. That scale is chosen by the coach based on his/her tactics and values. Our StatLink software allows the coach to choose both the characteristic and scale of measurement, thereby giving them the ability to evaluate players objectively and then communicate those results to their players.
