#Entropy synonym full#

Pitcher one throws a fastball, slider, and changeup. For example, let’s say there are three pitchers.

What do a high-entropy, medium-entropy, and low-entropy pitcher look like? Look at the visual above again and think of “winning” for a batter as guessing an incoming pitch correctly. This visual below might help get the gist of it across.

The third definition with information theory is the one we want to specifically focus on. Reading through these definitions, a couple words across them stand out (predictability, randomness, disorder) and you can already see how someone could tie this theory into pitch sequencing. (in information theory) a logarithmic measure of the rate of transfer of information in a particular message or language. lack of order or predictability gradual decline into disorder.ģ. a thermodynamic quantity representing the unavailability of a system’s thermal energy for conversion into mechanical work, often interpreted as the degree of disorder or randomness in the system.Ģ. One term frequently brought up in Arthur’s article is entropy, a pretty well-established concept in numerous math and science fields, which goes by the dictionary definitions of…ġ. Some of the methods from this great article were ones I felt needed a more updated analysis on, so let’s get into that. He took a very heavy statistical angle with pitch sequencing to analyze the effects it had on performance. More recently, John Asel at BaseballCloud talked about pitch sequencing with more of a game theory angle, diving deeper into analyzing the strategies of individual pitchers and analyzing the impact that certain sequences had on performance.īut perhaps one of the more deep and complex dives into pitch sequencing was a two-part piece written by Rob Arthur over at Baseball Prospectus back in 2014. This article established a lot of information on league-wide and player tendencies when it comes to two-pitch sequences and how those sequence types may impact performance. Back in 2014 over at The Hardball Times, Jon Roegle looked at pitch sequencing through the lens of two-pitch sequences (consecutive pitches). It’s a complex subject that can really get your brain going, which I think is fun.īut while not as much light gets shed on pitch sequencing in the public realm, there have been a few noteworthy stabs at it throughout the years. You can think about it in countless ways.

The cool thing about pitch sequencing is it really doesn’t have one definition or isn’t one concept. You can interpret than any way you want (two-pitch, three-pitch sequences, etc.) A key part of a pitcher optimizing their arsenal is making sure that the offerings they have interact well with one another, which you can look at through a variety of angles (velocity and movement differentials, spin mirroring, pitch tunneling, etc.). The second way I think of pitch sequencing is through actual sequences. First, simply how predictable is a pitcher? How many pitch offerings do they have? How will do they mix up the offerings that they have? As a hitter knowing the incoming pitch type would be a massive boost, so pitchers that lower the probability of that happening would have an advantage in some way, you would think. Personally, I’ve always thought of it in two main ways. It’s just a tough thing to put one number on.īefore we get into the meat of this, it’s important to actually think about what pitch sequencing actually is.

#Entropy synonym full#

But for all the impact it may have, relatively little public research has been done on the subject, presumably due to its complexity and almost full inability to be quantified. Ask anyone involved in baseball, player, coach, or analyst, and almost all would probably agree that pitch sequencing is one of the more important factors that go into the success of a pitcher.