“This doesn’t have to be the traditional method of forming a hypothesis and then answering one direct problem, seeing how much data we have today, in my opinion, you don’t have to rush to find the issue to solve. Look at the big data sets first to find direction…”
He was very easy to converse with as he was polite and cordial over email. I discussed with him what I found and how I thought googling was a very rudimentary way of finding research articles. Surprisingly, Professor Mario said it was a good place to start…
I told him how most of the sports that have looked into the left handed advantage are baseball, cricket, tennis, and fencing. Also most of the angles that they have been looked at have also been from the more psychological side, for example how left handed people are more agile on one side of their brain that also controls rapid reflexes and spatial reasoning (both traits of a good athlete).
I also found general articles using the scarcity of left handed folks as a reason why they are better, because the typical opponents will not be used to playing against a left-handed athlete. Professor Mario suggested that I look at maybe matchups of LH v LH, RH v LH, RH v RH to see if there is significant difference.
Finally Professor Mario did tell me my first objective now is not to find a bunch of factors and “R^2 it” like I thought to find the most significant factor, but be patient and data mine for where there were big pools of data first before determining the direction to take this question. I guess he could tell I was a little concerned only having narrowed down my topic of interest to the left handed advantage in the NBA with no specific factors.
Professor Mario suggested that I start looking for these data points by contacting NBA managers or even the Purdue Athletic office since I already work there. This brought me to share an anecdote with him about how in Scorecasting-The Hidden Influences… By: Tobias Moskowitz and L. Jon Werthem there was a story of an old lady who wrote down every time the ref would make a call on how much time to allot to an injury in professional soccer, just because. And her son or grandson (I forget) eventually found that data and used it to justify whether or not referees were bias in home field. My point of sharing this story was to make a parallel of me being just as willing to collect data from watching replays as the diligent old lady was. However, Professor Mario brought up the point that there maybe some verification issues with how I got these numbers and open source data is probably best.
In my next post I will be about my search for the big accumulations of data. I will try to actually take care of that at the BoilerMake Hackathon (at Purdue ) this weekend!