What I found was that strength of schedule is still statistically insignificant (i.e. t-Statistic) is less than two in absolute value, meaning that I am not at least 95% confident that strength of schedule (SOS) is different from zero in a statistic sense. In fact I am not even 20% confident that SOS is different from zero statistically. Given the estimated coefficient on SOS is also almost zero, even if it was significant (and it is not) the amount of impact that it has on winning percent is nearly nothing anyway.
Also note that the regression performs well in terms of R-squared and Adjusted R-Squared, and the probability of the F-Statistic is also very low indicating that all the independent variables are not jointly equal to zero in a statistical sense.
Here is the regression results for the 2012 NCAA FBS season run using E-Views.
|Dependent Variable: WINPCT|
|Method: Least Squares|
|Sample: 1 124|
|Included observations: 124|
|White Heteroskedasticity-Consistent Standard Errors & Covariance|
|S.E. of regression||0.095|
|Sum squared resid||1.089|
|Mean dependent var||0.491|
|S.D. dependent var||0.249|
|Akaike info criterion||-1.832|