Firstly, let me say that I have been prone to overvalue the Indians all season and have a negative ROI on them. They have been the worst managed team and their lack of fundamentals has been so far off norm that it I did not fully account for it in my quant model.
That said, when you have an team that has underachieved all season and now has lost 9 of their last 10, the oddsmakers are prone to capitulate with their pricing. Masterson has been hard to hit, and his walk total may not be as vulnerable facing a young lineup in a big park.
I think Mortensen has potential and should be a good pitcher in a couple of years. But he has not shown that he can be such at AAA this year or being called up. It looks like his is being priced for potential and not a predictive performance measure.
QUESTIONS FOR YOU BG IF I MAY..DO YOU YOU USE A 'SIMILIAR' VALUATION MODEL FOR FOOTBALL AS BASEBALL...GIVEN THE DIFFERENCES IN THE SPORTS ??? oN STREAKS....IT SEEMS LIKE A PHENOMENON TO ME THAT YOU CAN GO SAY 2 FOR 12 OR 12 FOR 2 HOW MUCH RANDOMNESS AND NOISE CONTRIBUTES TO THIS????YOU HAVE REPONDED TO ME ABOUT THIS IN THE PAST..BUT NOT SURE (OUTSIDE OF INCREASING OR DECREASING BETS ACCORDINGLY) HOW TO GUESS A "MEAN" TO THIS.. I HAVE BEEN BETTING FOR 35 YEARS AND THIS IS STILL PUZZLING THANKS
The similarities of deriving an intrinsic value to a game, comparing it to the market, and quantifiying the appropriate amount to risk on the game based on the disparity is the same. The quant model that derives the fair value is very different.
There is a lot of randomness in short term performance in both sports. The amount of games in a baseball season allows most of the noise to be weeded out. Football lacks the ideal volume to get rid of a lot of noise, thus you will see a lot of -EV cappers churning plus years, and EV cappers having losing.
Added to the lack of volume, the increased market efficiency, increased randomness within a game, and a higher amount of intangibles that influence a game all lead to pricing error as well as a harder capability of finding a disparity between price and true worth- all of which can also increase variance (noise).
