Quote:
Originally Posted by Bongle
Again to go back to the stats I did a few years back, a team's seeding performance in one year is a very poor predictor of its performance in the year following.
Here's a graph: http://www.chiefdelphi.com/forums/at...6&d=1175831673
On the X axis is a team's seeding performance in 2005. Further left is better. On the Y axis is a team's seeding performance in 2006, lower is better. You'll see about the only thing you can predict is that teams who were top seeds in 2005 tended to not be dead last in 2006. Likewise, teams who did very poorly in 2006 tended to not win the following year (but some did). Past behavior predicting future behavior may work well in humans, but not so much in robotics teams.
The teams that do well year after year are very special cases. Out of the 1500ish active teams in FIRST, people can probably only name 50ish 'power houses' who win year after year after year and never hiccup. |
I never said it was a fantastic predictor. I said it was the best. Predicting behavior in humans is very challenging.
The graph that you provide may very well prove that past preformance does predict future behavior. It appears the correlation coefficent would be around .2 or .3 and with a large sample size (around 1,000) I would not be surprised to see the correlation statistically significant. This means that the observed relationship is not due to random varation but because the two samples (results from 2005 and 2006) are in fact related.
Although it is not a perfect correlation or relationship (nearly all relationships in life are not perfect) doesn't mean there is none. It may not be a very strong relationship, but it appears there is one. I cannot think of another relationship (team number, funding...) that is a better predictor than past preformance.
To tie this back into the original topic, there is not perfect predictor for team preformance. Unless someone does a huge multiple regression study and finds a way to predict how teams are (I don't think there is one), the best way is to just randomly assign teams under the perameters (such as time inbetween matches) to ensure the most fair pairings.