That Saints is made out of a VW bug.

I've been drinking buffalo trace and 100 proof absolut all night so I'm not sure what I just read, but I read it and my interest is piqued.

Just went through my first read and my head is spinning...

Bottom line is writer used regression analysis of several factors to determine those with the greatest impact upon QB success in the NFL and then combine the top factors into a predictive model.

... the best model overall had years out of college (ExpBin), hand size (Hand), throwing velocity (Vel), logarithm of draft position (Log.D.Pos), final college year AYA (Last.AYA), and the film grade (Film) as inputs.

It is important to note that the prediction is the percent probability of a given QB having a "successful" season in his career.

While I am not sure the above output is the be all measure, the results are interesting... and the interest goes well beyond this year's QB class, e.g., last year's class plus Jimmy G. Interestingly AJ McCarron is not in the data base, but as I recall he did not throw at the Combine, so the velocity data it generates is missing. This was mentioned in the article as the reason why Matt Ryan is not in the database.

http://rotoviz.com/2017/03/modeling-qb-success-2017/?hvid=5y57MG&utm_content=buffer99cfb&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

I still don't quite know what happened to Josh Freeman, he looked really really good for a while. Would stand in the pocket while it crumbled around him and deliver, career fell apart very easy

Just went through my first read and my head is spinning...

Bottom line is writer used regression analysis of several factors to determine those with the greatest impact upon QB success in the NFL and then combine the top factors into a predictive model.

... the best model overall had years out of college (ExpBin), hand size (Hand), throwing velocity (Vel), logarithm of draft position (Log.D.Pos), final college year AYA (Last.AYA), and the film grade (Film) as inputs.

It is important to note that the prediction is the percent probability of a given QB having a "successful" season in his career.

While I am not sure the above output is the be all measure, the results are interesting... and the interest goes well beyond this year's QB class, e.g., last year's class plus Jimmy G. Interestingly AJ McCarron is not in the data base, but as I recall he did not throw at the Combine, so the velocity data it generates is missing. This was mentioned in the article as the reason why Matt Ryan is not in the database.

http://rotoviz.com/2017/03/modeling-qb-success-2017/?hvid=5y57MG&utm_content=buffer99cfb&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer

Holy smokes someone has some time on their hands:

.... To build the model, I took the complete data set, which included the following data: height, weight, age, 3-cone, shuttle, hand size, throwing velocity, and a film grade, and added on final college year AYA, draft position,

1

and a bin for the number of years out of college.

I’ll spare you the details, but the most statistically significant split for the out of college bin was between four and five years removed from college. In other words, players who have completed four years post-college fall in one bin, and players who are going into their first through fourth years out of college fall in the other bin. This is important because it’s certainly much easier to hit the criteria of one year of a 7.0 AYA if you’ve played several years, compared to having only one or two years of playing.....

Kind of has the Econ Stats feel but does cover some good QB requirements.