TRANSFORMING RAW DATA INTO INSIGHT & ACTIONABLE INFORMATION After reading the book Moneyball for the first time, I built a factor model in hopes of finding a way to finally be competitive in my fantasy baseball league - which I had consistently been terrible at. It worked immediately. By taking raw data and turning it into actionable information, I was able to solve a problem that had long perplexed me. It was like discovering a new power. What else could I do with this? Today, I build models for everything and have come a long way since that first simple spreadsheet but still use a lot of the same concepts. To build a traditional factor model, you would regress a dependent variable against a series of independent variables and use the resulting beta coefficients as the factor weights... assuming your resulting r-squared and t-test showed a meaningful relationship of course. Variables typically fall into one of two categories... continuous or dichotomous....