Pythagorean Theorem and Soccer

[gryfyn1]

How reliable are the coefficients used for each sport in this model, statistically, where it comes to forecasting season wins? Based on results going forward only.

The issue with using it to predict future outcomes, is thats not really what the formula was intended to do and it has limited application in that facet.

Only if you are reasonably sure you can predict the point for/against will the the therom provide you accurate data.

[Pokerjoe]

The issue with using it to predict future outcomes, is thats not really what the formula was intended to do and it has limited application in that facet.

Only if you are reasonably sure you can predict the point for/against will the the therom provide you accurate data.

The theorem isn't supposed to predict future outcomes. Nor is it supposed to provide you with data.

The pythagorean formula (and may I remind you guys that the OP was asking about soccer, for which Pythag is inappropiate anyway) is for translating score estimates into win %. Pythag or Poisson are useful as translators, not predictors, not data generators.

[oddsfellow]

Some interesting work on Pythagorean Theory in relation to soccer can be found here

http://www.soccermetricsblog.com/soccer-pythagorean-theory/page/2/

[luegofuego]

I would have to respectfully disagree.
There is a huge difference between approaches and methodologies of true scientists and those of sport results “predictors”.
In fact, “predictors” move in the exact opposite direction of how science operates.

Scientific theories are designed to incorporate more and more data, absolutely.
But scientists prefer fewer theories which describe more phenomena rather than many theories which each describe very little.

One of the greatest achievements of a human civilization is a simple and very short mathematical formula (E=MC²) which describes a mind boggling range of physical phenomena.
Compare it to mind boggling number of theories all going (still unsuccessfully, I might add) after the same thing – trying to predict an outcome of a simple ball game

if einstein had a good enough database, he would've probably stumbled upon e=mc2 by regression