The shell script "demo.sh" loads scraped data alias tables between the two data sets (NCAA and Basketball Reference) for schools and players. It then runs sample R code that does a simple stepwise regression to detect some NCAA features that impact NBA playing time 1 year out from the draft. You won't be able to run these without installing PostgreSQL, R etc., but I've included two text files showing the results. The first is "script_output.txt" which shows the output of the "demo.sh" script (including the total time take - about 12 seconds). The file "feature_selection.txt" shows the results of the stepwise regression. This is the final model - no surprise, the pick number dominates in a non-linear way. Also settled on were height, position, games, assists per game and steals per game. I did not examine any interaction terms, nor did I look at other measures of NBA value, but these are straightforward given the database (up to the limitations of my scraped data, of course). I haven't adjusted college performance for NCAA strength of schedule yet.