Market Fantasy 11 - Consistency

Hello and welcome to Market Fantasy!

This May, I spent a week in the Scottish highlands. I seriously recommend it for anyone. The scenery is breathtaking, the people are incredibly nice, and of course, the whisky is unbelievable. I loved it so much, I when I got home, I went directly to my company’s careers site and looked to see if there were any openings over there. I bring this up, however, because of the whisky. I am a whisky fan. Some of the single malts I tasted and brought back from my trip simply have no comparison in the states. The problem is the last part of that sentence; I can’t get a lot of my favorites or limited editions here in the states. When I’m at home, I usually have a bottle of Johnnie Walker Black Label. It’s my go to when I can’t have the really good stuff. Similar to how I have a beer or two that is my go to when I’m out and don’t have the vast selection of Binny’s at my disposal. One of the hallmarks of Johnnie Walker whisky is its consistency. It is a blend of numerous whiskys, yet it tastes the same each time. That is because of master blender Jim Beveredge. And, yes, his real name is Beveredge. This guy gets paid to ensure that every bottle of Johnnie Walker Black Label tastes exactly the same year in and year out. He uses his incredible palate to ensure the blend never changes. He is my new hero.

With that in mind, I give you the Jim Beveredge consistency rankings for the 2012 football season. Two metrics went into creating these rankings: mean weekly points scored and standard deviation of weekly points scored. From there I came up with a formula to blend those two numbers into the consistency ranks. The idea was to find players who score the highest amount of points on average and who consistently score close to that number.

As I said, there were two metrics that went into these ranks: mean weekly points and the standard deviation of a player’s weekly points. The mean is simply an average of the weekly score. Standard deviation is a statistical measure that shows how much dispersion or variance there is from the mean in a data set. A low standard deviation means that there is less variation from the mean, and conversely, a high standard deviation means more dispersion from the mean. Standard deviation is the square root of variance, but since it is stated in the same unit as the data, it can be more helpful than variance.

Now that you know what standard deviation is, let me tell you how to use it. Standard deviation gives you an idea of where data points of a population (weekly fantasy scores) will fall. Use the graph below as a guide.

A couple things about this graph: s = the number of standard deviations, m =  the mean. When looking at a data set (again, weekly fantasy scores), we can see that 68.2% (34.1*2) of the results will fall within one standard deviation on either side of the mean.  95.4% (34.1*2 + 13.6*2) will fall within two standard deviations of the mean and a full 99.6% of all scores will fall within three standard deviations on either side of the mean. What this means is that if Peyton Manning has a mean score of 22.22 and a standard deviation of 6.6, 68% of his weekly fantasy point scores will be between 15.62 and 28.8 points. 95.4% of his scores will be between 9.02 and 35.42 points.  So we can use this information to get a good guess of what a player will do on a given week. Again, look for players with a high mean score and low standard deviation.

Below are the rankings. They are not perfect, as some players with low scores who are consistent about it snuck in the top, but the mean and standard deviation are presented so you can make your own conclusions. I tried to avoid any skewing by cutting off players at certain point levels for last year. QB’s who averaged less than 10 points are not included. WR, RB and TE who averaged less than 4 points are not included and DST who averaged less than 5 points are not included. Also, only the games in which a player played are included in the calculations. This eliminates weeks where a player didn’t play and recorded a zero. By doing this, I hope to get a clear idea of a player’s on-field performance not clouded by injuries or bye weeks.

Thanks for reading!