Casey Kotchman as Luck Example

Baseball games are not perfect simulations. They’re not good ones, or even mediocre ones. They’re downright awful. When we design, engineer and execute proper simulations or models, we are often dealing with scales on the order of thousands of repetitions to become comfortable with the probability of the results. Baseball runs through it once.

Granted there are lots of smaller, more repeated samples within the larger single sample. That helps keep some of the noise down, but not nearly all of it, or most of it. Baseball is a noisy game dominated in many ways by what is commonly called luck and people by nature are just terrible coming to grips with that.

Study after study illustrates that people cannot grasp the implications of basic statistical principles such as randomness and regression. It’s why I think it’s always worth talking about, no matter how often it’s been discussed recently. A thought that was on my mind today was the Seattle Mariners’ lack of offense, an almost unprecedented amount of futility for the second consecutive season.

It’s also the second straight time that I, and a number of forecasting systems, pegged them as merely below average at the plate instead of being a unit that puts up less of a fight than a bop bag. Part of that might be due to a systemic error we are making when it comes to evaluating the hitting talent on hand, but I wager that a far larger share of the blame rests on that nebulous artifact called luck.

An example of why I think that is Casey Kotchman, who is now about two games away with the Rays from equaling the number of plate appearances as a Mariner last season. A great aspect about Kotchman, and why I adore him as an example here, is that very little about his approach and direct results changed from 2010 to 2011. Consider the following comparisons:

Strikeout rate (K/PA): 12% (2010), 12% (2011)
Walk rate (BB/PA): 6.3%, 7.3%
Ground ball rate (GB/batted balls): 55%, 56%
Line drive rate (LD/batted balls): 18%, 19%
Home Run rate (HR/fly balls): 9.2%, 9.2%
Isolated Patience (OBP – AVG): .063, .066
Isolated Slugging (SLG-AVG): .119, .126

Those numbers paint a picture of a hitter doing nearly exactly the same things that he did across two seasons. There is one big difference though:

RBBIP (times reached base [including via error]/balls in play): .238, .377

And thus:

AVG: .217, .323
OBP: .280, .389
SLG: .336, .449
OPS: .616, .838
wRC+: 66, 133

Hitters aren’t pitchers and do have more control over how often their balls in play result in them standing on base, but most of that is because they can better control what type of batted ball they hit than pitchers have and Kotchman’s batted balls don’t appear to be demonstrably different from when he was a Mariner. The numbers above are from BIS, but MLBAM’s numbers don’t show a big discrepancy. The most obvious answer here is statistical fluctuation aka randomness aka luck and the impact it has is so vast that it turned one of the biggest hitting jokes of last season into a well above average player.

Matthew Carruth is a software engineer who has been fascinated with baseball statistics since age five. When not dissecting baseball, he is watching hockey or playing soccer.

Newest Most Voted
Inline Feedbacks
View all comments
12 years ago

I believe you meant to say Kotchman rather than Carp at the end there

12 years ago
Reply to  Aesop

Good piece though, Jack Z is ridiculed and Friedman is lauded and they both took a chance on the exact same guy

Sitting Curveball
12 years ago
Reply to  Aesop

So true. You can’t evaluate decision-making ability based on how the decisions end up.

And the beginning of this article was extremely cool. I watch baseball every day, thinking to myself “in a different simulation, what might’ve happened?”

12 years ago
Reply to  Aesop

Jack Z traded for him and Friedman signed him to a minor league contract.

12 years ago
Reply to  Aesop

Jack Z traded away Bill Hall’s salary for Kotchman. It’s not as if he gave away the farm. The acquisitions aren’t all that different.