clear	
clear matrix
set matsize 800
set mem 500m
cd [your drive partition]
use [team_ops_r_1900_1924 data file]

gen rppa=r/pa  // run per plate appearnce

*** create standardized variables ***

bysort yearID: egen mean_ops = mean(ops)
	bysort yearID: egen sd_ops  = sd(ops)
	gen z_ops = (ops - mean_ops) / sd_ops

	
	gen b_z=.
	gen b_r=.
	
	gen prun=.
	gen pzrun=.
	gen cons=.
	
bysort yearID: egen mean_rppa = mean(rppa)
	bysort yearID: egen sd_rppa  = sd(rppa)
	gen z_rppa = (rppa - mean_rppa) / sd_rp
	regress z_rppa z_ops

**** raw and standarized season-by-season regressions
	
	foreach y of numlist 1900/2025  {
		
		regress rppa ops if year ==`y'
		replace b_r=_b[ops] if year == `y'
		replace cons=_b[_cons] if year == `y'
		predict yhat
		replace prun =yhat * pa if year ==`y'
		drop yhat
		
		regress z_rppa z_ops if year ==`y'
		replace b_z=_b[z_ops] if year ==`y'
		predict yhat
		replace pzrun= yhat * pa if year ==`y'
		drop yhat
	}
	
**** export

	collapse b_z b_r cons ,by(yearID)
	
 save [rppa_regresson_coefficients], replace