#### TC in Mississippi

##### CCS Staff

I am a computer scientist in the finance field and had to do a project on stats in baseball before graduating, to try to find a new stat that found a new probability. Statistics are just measuring probabilities, that is it. And if you love the sport on a physics level and probability level for all its minutia, the statistics part makes dorks like me incredibly excited

It isn't meant to predict what will happen in the next at bat it is used to put your players in the best position to succeed in each at bat, for each pitch, and in the right spot in the field. Over the course of a 162 game season this will be a net benefit to the team.

BTW, the stat I created was used to measure where each person should hit in the batting order. Eventually when I have time I will make my own site that scrapes data from other sites and has real time updates on this stat for all of baseball. The stat is somewhat aa combination of .OPS and WRC, but used to determine who should bat when people are on base.

People who hate stats are just generally showing their insecurities in their inability/laziness to understanding them.

Exactly right and it's really simple to relate to probabilities if you try. For instance if the weather forecast shows a 80% probability for rain you probably cancel a big outdoor event or move it inside. That doesn't mean that you won't be sitting inside complaining that the sun is shining and the event would have been better outdoors. In talking aobut what the Brewers are doing the probability of them dong what they just did, winning 12 in a row including winning overtaking the Cubs, winning a one game playoff, winning the NLCS and winning the first game of the NLCS was very slim. The fact that they did it anyway did not invalidate the statistics that showed those odds were slim anymore than the decision to move the outdoor event indoors based on an 80% chance of rain invalidates weather forecasting. When you use numbers to foresee outcomes you are

*projecting*while if you just pick, say a winner of a playoff game in the absence of numbers, you are

*predicting*there is a huge difference. Also, going back to the weather forecasting example, if the models for projecting the weather are consistently wrong, the models will be reexamined. In baseball if the numbers show that a hitter can't hit to the opposite field, and you employ the shift to exploit that, and yet the hitter starts to do what you weren't projecting than obviously those numbers change as well. None of this is hard. If you say there's an 89% chance that Houston wins the ALCS if they win tonight and then Boston wins four in a row that also doesn't invalidate the numbers used to project that outcome.