The Game is Afoot: On Sherlock Holmes, Analytics, and Fantasy Baseball

Kody Clawson | June 10th, 2019

There’s nothing more elusive than an obvious fact. – Sherlock Holmes

Everyone has a movie that they love that critics despise. Some call it a guilty pleasure, while others band together over it and give it cult classic status. For me, recently, I happened upon a pair of movies that I had a similar appreciation for but had forgotten about for a time. Nearly ten years ago, Guy Ritchie’s version of Sherlock Holmes came out to much fanfare, an action variant of the classic detective story, complete with then-comeback-actor Robert Downey, Jr. as the lead and Jude Law as Dr. Watson. I had always been an ancillary fan of detective stories, Holmes stories in particular, and Downey’s involvement in the film piqued my interest, with his recent resurgent success coming off of Iron Man in full force. Unlike several critics, the action-adventure turn to the old Sherlock stories, along with Downey and Law pairing together perfectly, made both this film and its sequel (A Game of Shadows) rather enjoyable.

But you’re not here to read about what I stumbled upon via Netflix during a recent sick day. You’re here about baseball, specifically fantasy baseball. So what does Sherlock Holmes have to do with fantasy baseball? Perhaps there’s less of a correlation than I’d like to ascribe to it, but I’d like to think that Holmes would have been a great fantasy baseball player (if he were to even care about such a thing), especially in our world of analytics. Why? Well, there was one quote in particular that stood out to me in the first movie (which was also in the books). I’ll share several different quotes to show my belief that Sherlock Holmes would have been a great sabermetrician, but here’s the first.

– It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.

Numbers are facts, and while they sometimes can lie to you, it’s usually when you look at just one number, or even just one small part of the data, that you find yourself lied to. You cannot go into analyzing a player expecting a certain outcome, or else you will be led astray by the hopes that that certain outcome will be true. Numbers are great, but one data point does not tell the whole story. You have to look at the player as a whole to get the proper outcome.

– I confess that I have been blind as a mole, but it is better to learn wisdom late than never at all.

It’s never too late to learn, and the same can be said with analytics. With time and effort, one can start to wade their way through the data and find useful information out there. Whether you’re using it for fantasy purposes, interest in a certain player, or just want to enhance your enjoyment and understanding of the game, there’s something out there for everyone who wishes to learn from it.

– When you have excluded the impossible, whatever remains, however improbable, must be the truth.

There are times where your eyes or your mind are telling you one thing but the data tells you something entirely different. While it is always good to question everything, you must be willing to assume that what your senses are telling you might be wrong. For instance, at least for last year, Matt Chapman was a better hitter and more valuable bat than Nolan Arenado. Now, at face value, that seems absurd, as Arenado hit .297 with 38 home runs versus Chapman’s .278 with 24 home runs. But, accounting for the parks they play their home games in and adjusting the numbers so, we see that Chapman hit for a 137 wRC+ while Arenado hit for a 132 wRC+. The park adjustments indicate that, if all else were similar, they would have hit about the same line, with perhaps a small advantage going to Chapman. At face value, this makes no sense, but once you realize the environments for these two third basemen significantly skewed their numbers, it makes perfect sense. Still, it’s difficult to tell the mind these things sometimes.

– Problems may be solved in the study which has baffled all those who have sought a solution by the aid of their senses. To carry the art, however, to the highest pitch, it is necessary that the reasoner should be able to use all the facts which have come to his knowledge; and this in itself implies, as you will readily see, a possession of all knowledge, which, even in these days of free education and encyclopedias, is a somewhat rare accomplishment.

There’s a lot of data out there, and a lot of ways to interpret each bit and parcel of data. If one wishes to jump in to try to interpret all of the data that now exists in all of the various avenues with which to consume it, they could find themselves exasperated, confused, and utterly stonewalled by the sheer breadth of it all. Paralysis by analysis, one might say. Another might claim the paradox of choice. Regardless, the flood of analytical data should not keep you from making use of at least some of it. Seek after what you find valuable. You must research different articles that state not only what the analytical devices mean, but also what they can show you.

– Circumstantial evidence is a very tricky thing. It may seem to point very straight to one thing, but if you shift your own point of view a little, you may find it pointing in an equally uncompromising manner to something entirely different.

It’s easy to see certain statistics, or even expected statistics, and assume that a player should be able to perform better (or worse) than current levels. Indeed, statistics like xFIP or xwOBA may try to take some of the noisy variables within a player’s performance away in order to indicate how he should truly be performing. However, one should be wary of these statistics. While they work to provide an idea of true talent level, there is sometimes a reason for the “noise” they try to snuff out. Is there a hidden injury that a player is dealing with? Is their batting stance or delivery out of whack? Are there certain traits to their profiles (i.e. pulling the ball, pitching for more fly balls or ground balls) that might affect the so-called noisy, “luck-based” stats like BABIP? There is not a one-size-fits-all statistic that will tell you everything you need to know about each and every player. It’s imperative that you look at all the variables you can about any player to fully analyze his ability to produce.

– This looks like one of those unwelcome social summonses which call upon a man either to be bored or to lie.

This is simply a quote to remind anyone like me (an introvert) to get out and seek other human life occasionally. Sure, people can be boring, especially if they’re not baseball people, but I implore you, as I implore myself, to go and find solace and entertainment in others. Invite them to go with you to a baseball game, if you must.

– You know a conjurer gets no credit once he has explained his trick and if I show too much of my method of working, you will come to the conclusion that I am a very ordinary individual after all.

I am incredibly simple-minded. Despite my love for stats, I’ve had several others hold my hand through the murky waters that are statistical analysis. Even as I spout out numbers in this and other articles I’ve done, it’s because of several others who have taken me behind the curtain and shown me what is useful for this or that concerning fantasy baseball. If there are ever any questions that you, dear Watson (may I call you Watson, reader?), may have for me regarding any stats or any information that I put out, please do not hesitate to ask. It’s important that we all work together, as we are all indeed simple creatures that are simply trying to take pleasure in this simple game.

– Draw your chair up, and hand me my violin, for the only problem we still have to solve is how to while away these bleak autumnal evenings.

Let’s just not talk about the half a year we have no baseball, shall we? Now come, Watson, come! The game is afoot. Let’s play.

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