Sox Machine Book Club: ‘The Inside Game,’ Chapters 4-6

The Inside Game by Keith Law

If you missed the first installment of the Sox Machine Book Club that covered the first three chapters of Keith Law’s “The Inside Game,” check out the discussion here. It might provide some useful context before plunging ahead.

(Bookshop.org link; Sox Machine receives a portion of the proceeds.)

If you’re caught up, comfortable with the material and/or don’t care about spoilers, please proceed.

Chapter 4: But This Is How We’ve Done Always Done It: Why Groupthink Alone Doesn’t Make Baseball Myths True

This chapter centers on the illusory truth effect, which Wired succinctly describes as “a glitch in the human psyche that equates repetition with truth.” The brain appreciates familiarity, because it’s easier to process things it’s already experienced. The problem is that this can be manipulated if the wrong things make enough sense on a superficial level to be accepted after enough loud and distinct encounters.

Law gives a few baseball examples, like the myths of lineup protection and clutch hitters, or the idea of the “riding the hot hand,” all of which cause little harm when people are on the wrong side of the argument, but nevertheless illustrate the both the pervasiveness of information that’s provably false, and the issues in trying to correct the record.

Obviously, high-stakes instances of the illusory truth effect are all around us, which is why baseball is such a nice entry point. There’s a lot less risk in arguing over closer roles than vaccines.

Chapter 5: For Every Clayton Kershaw There Are Ten Kasey Kikers: Base-Rate Neglect and Why It’s Still a Bad Idea to Draft High School Pitchers in the FIrst Round

Law’s summary: “Base-rate neglect is the name for the phenomenon where you have a mountain of evidence saying one thing, but you choose to ignore it in favor of the specific case in front of you. You favor the information that stands out because it’s more recent or it’s more memorable or it’s just the first thing you found, and in the process you forget or fail to check on the larger sample of data over a longer period of time. The former could be misleading, while the latter should be more predictive because of the greater sample size. You know high school pitchers flame out more often than other players do, but dangit, this here kid Joey Bagodonuts — you just know he’s different, right? He’s the exception that proves the rule, or something. Your scouts are just sure he’s the one kid who’s different.”

Josh crunched the numbers and found that 48 percent of the pitchers drafted in the first two rounds of the draft from 2000 to 2015 failed to reach the majors, as opposed to 32 percent of college pitchers. You can see his work here.

Law also extends the argument to poor odds plays like investing money in relief pitching, beating aging curves, and unfavorable-on-paper matchups over small sample sizes.

Chapter 6: History Is Written by the Survivors: Pitch Count Bingo and Why “Nolan Ryan” Isn’t a Counterargument

Survivor bias relates to base-rate neglect, as the success stories (Kershaw, Zack Greinke, Madison Bumgarner) tend to overshadow all the stories of failure, because it’s a lot easier to forget the players that aren’t right in front of you.

As the chapter title indicates, Law uses Nolan Ryan’s legendary durability as a dangerous example to use as a guiding principle for managing pitcher workloads, as history is littered with arms that couldn’t handle it.

Take a second to support Sox Machine on Patreon
7 Comments
Oldest
Newest Most Voted
Inline Feedbacks
View all comments

I agree with the blurring of concepts between chapters. I’m a little bit ahead right now, but quickly note how does recency bias differ greatly from availability bias or the anchoring effect? I mean, they all should be somewhat interrelated I suppose but I’m realizing my memory sure isn’t what it used to be and am regretting not outlining key points after finishing each chapter.

With that said, the illusory truth effect was an interesting dive into why people believe things that are patently false. More interesting to me was the look into how our brains will defend the falsehood because it gets so ingrained in our minds that the negative feeling of changing that point of view is worse than just accepting the truth. Anti-vaccination arguments have always set me off because there is NO argument to support it. Yet, it got entrenched so deeply that trying to steer these folks to the better public health choice seems impossible.

I guess this book is also reminding me how primitive our brains really are. Everyone is suspect to these biases and making sure you are vigilant with your own decision making process and willingness to examine that process is all the more important. The problem that I find myself having in reality is that we often don’t have the benefit of time to make those really thoughtful decisions. Just like the umpire who has to make that split second decision, everyday choices don’t often give you a whole bunch of time to consider all the data or potential biases.

If anything, evaluating these concepts is helping me at least be more thoughtful in the aftermath.

DuckSnorting-CanofCorn

I enjoy the pairing. I really miss just having the game on in the background while I tend to the kids or make dinner. Do you think Benetti is with the Sox for the long haul? He seems to appear in other sports and networks somewhat often and I have no idea what his contract status/length with the Sox is.

The Anit-vaxx things drives me nuts too. I’d recommend the book I linked in my talking points. The author humanizes the movement in a way I hadn’t really considered while also properly dismissing the arguments at the heart of it.

The Illusionary Truth bias is a brutal once since over the span of about 30 years we went from only a few sources of ‘facts’, the majority which were well respected (I’m thinking about newspapers and magazine), to a point where the bogus ones outnumber the legitimate ones and are easier to obtain. Trying to process that shift is challenging enough let enough parse through the sources that are out there.

Shingos Cheeseburgers

Chapter 4: But This Is How We’ve Done Always Done It: Why Groupthink Alone Doesn’t Make Baseball Myths True
Essentially, it’s easier to accept than to analyze, particularly if the the ‘fact’ is coming from what is viewed as a trustworthy source. Which in it of itself is an issue because it’s easier to just accept that a source is a reliable one instead of trying to determine possible motives and validity. Baseball is such an insular community that the old guard is held in such high regard that whatever old school notions die hard since no one wants to tell Tommy LaSorda he’s wrong. Tangentially, if you’re some 22 year old rookie you’re not gonna go against what your coach or GM is telling you since it’s likely going to adversely your career even if they’re pushing some old school BS.
A great read on the vaccine side of this issue can be found in Anna Merlan’s Republic of Lies

Chapter 5: For Every Clayton Kershaw There Are Ten Kasey Kikers: Base-Rate Neglect and Why It’s Still a Bad Idea to Draft High School Pitchers in the FIrst Round
Misplaced faith in the idea that ‘I know in general this doesn’t work but *I’m* gonna do this the right way’. This is a tough one to overcome, especially if you’ve put the work into scouting a guy but you have him ranked much higher than others. You want to be able to justify the work that you’ve already invested and by agreeing with the crowd you’d essentially be admitting you’re wrong.
I’d like to see the distributions of WAR for the HS/Uni pitcher breakdown as opposed to the 10+ WAR threshold analysis. Certainly the failure rate is higher but if the average WAR of the picks is near equal then there’s justification for taking the risk (Not that I expect that to be the case, but I’d be interested to see the numbers. Gotta get that granular Google Sheets data into a single dataset.).
This chapter made me feel not great about the Aaron Bummer deal! But I’ll give the Sox some benefit in regards to his pitch behavior that’s more predictive of future success than a single year’s stats.

Chapter 6: History Is Written by the Survivors: Pitch Count Bingo and Why “Nolan Ryan” Isn’t a Counterargument
I hate the Nolan Ryan argument. Pointing to one of the most atypical careers in history actually refutes the point that’s trying to be made. By only naming a single example if emphasizes how rare a case it is.
I like the ‘odds have condensed to 1.0′ comment’. Similar to outcome bias it’s a lot easier to attribute skill improperly when in reality luck played a role in an event once it’s happened – Hello 2005 White Sox! Not that the Sox were lucky to win the World Series, but that season as a whole was clearly a strange confluence of factors that hasn’t been recreated since.
Did Keith miss Rich Hill’s 2017 no-hitter lost in the 10th game when he cited the most recent example of a pitcher going into the 10th?

I in general agree with the challenge of trying to separate out the biases into distinct chapters since there is so much overlap – no once decision is typically influenced by just a single bias. But there’s too much cross over from each chapter for me. If I’m not mistaken he mentions Kasey Kiker in the title of Chap 5 but doesn’t discuss him until chapter 6.