Quote:
Originally Posted by XaulZan11
Like 171/2194, 1732 recorded the amount of points a team scored per match at Wisconsin. We kept track of lines and balls knocked down in hybrid, laps, hurdlers, herds and balls placed at the end.
I ran a correlation test to see how related the two sets of data are and see how good the OPR is at predicting how many points a team scores per match. There are some assumptions/problems. First, our scouting data isn't perfect so there is some error from that. Secondly, our scouting data doesn't include penalties, but the ORP does account for them. So, when doing a linear regression, I got an R value of .7841 and an R-squared value of .6149. (A perfect relationship would have an R value of -1 or 1 and no relationship would be 0). So, while it is not pefect (not surprising) the ORP is a fairly good predictor of a team's preformance.
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I did the same with 330's scouting data for San Diego and LA. We do account for penalties.
For SD, the R value was .8852 and R-squared of .7836
For LA, the R value was .8490 and R-squared of .7200
When I removed penalties from the equation, the SD R value fell to .8620 and the LA R value fell to .8345