Getting started doing baseball research

In this article, I introduce how FanGraphs can be used when doing baseball research.


Research should start with a question.

In an article by Mike Petriello published on April 23, 2019 on titled “These 5 players have opened eyes in April,” he states that Braves pitcher Max Fried’s curveball has the “third-most drop” in the major leagues.

From that information, I generated my research question: How big a vertical “drop” does Fried’s curveball have?

Here is how I found the answer.

Clicking the “third-most drop” link takes you to, an excellent source of baseball information. The displayed FanGraphs page contains a table with these column headings: FA-Z, FC-Z, FS-Z, SI-Z, CH-Z, SL-Z, and CU-Z. The two letters before each dash are an abbreviation for the pitch type. You can find what each pair of letters (e.g., FA) represents on this FanGraphs page.

The “Z” indicates that the columns contain information about a pitch’s vertical movement.

The column that will be focused on is CU-Z, where “CU” stands for curveball. On the day I checked, April 24, the vertical movement for Fried’s curveball was -12.0, the fourth-best in the major leagues.

On the top of the FanGraphs page is the information in the image below. To access it, click the image.

Menu at top of FanGraphs page containing Vertical Movement info

When the FanGraphs’ page appears, while on it click “League Stats.” In the CS-Z column, in 2019 the average curveball’s vertical movement (again on April 24) was -8.3, thus Fried’s curveball drop was almost four inches better than the league average.

More articles about curveballs
The physics of throwing a perfect baseball pitch

Bug in WordPress 2016 Theme

In the Pullquote block, the text color cannot be changed.

Column 1Column 2Column 3

Tables work fine as do regular quotes and list, such as the ones immediately below.

This is a quote.

Jane Doe
Continue reading “Bug in WordPress 2016 Theme”

Introduction to Stat Sources

If you like to view baseball statistics, a variety of sources exist. Among them are Baseball Reference, FanGraphs, Baseball Prospectus, Baseball Savant, and Statcast. Baseball Savant and Statcast are products of Major League Baseball. 

Baseball Savant can be accessed here and Statcast through its search page though Statcast info is also available from the main Baseball Savant page.

On Baseball Savant’s homepage is a menu bar containing this:

  • Gamefeed 
  • Probable Pitchers 
  • Daily Matchups 
  • Leaderboards
  • Search
Continue reading “Introduction to Stat Sources”

One of My Favorite Baseball Stats: RE24

One of my favorite baseball stats is one developed by sabermetrician Tom Tango and well explained by Patrick Jeter of Redleg Nation. It’s RE24, where “RE” stands for “Run Expectancy” and RE24 for “Run expectancy based on the 24 base-out states.”

In brief, it indicates how many runs, on average, a team can expect to score in an inning depending on the number of outs and which bases are occupied. For example, if a batter’s at the plate with the bases loaded and no outs, from that point to the inning’s end his team can expect to score more runs than if the same batter came to the plate with none on and the bases empty. Continue reading “One of My Favorite Baseball Stats: RE24”

Part 1: My First Day Exploring OOTP 17

A description of my first day trying to learn how OOTP 17 works so I could start playing it MLB game.

OOTP 17 is a baseball app that enables you to do much more than play baseball on a computer, where OOTP stands for Out of the Park. How much more I did not realize until began playing with the app on my Mac. And though I’d played many times both the APBA and the Strat-O-Matic baseball board games and APBA’s computer baseball game, I was not prepared for what I encountered after installing OOTP 17.

Read my APBA interview.

When you start OOTP 17, a well rated baseball simulation app, these are the main choices available on the first screen you see. Stumbling through the online manual on my first day of exploration, I found the choice that would enable me to begin playing with the current MLB teams: “New Standard Game.” 

Menu on OOTP Home Screen
Menu on OOTP Home Screen

What I did not know at the time was that in “New Standard Game” OOTP defines game differently than I do, something I did not discover until later. I expected its “game” to mean a typical baseball game, the type I watch on TV. But that’s not how OOTP defines it. It defines it in a broader sense, more like the “game of baseball,” but even then the game played in the Major Leagues differs from the Little League game, and both of them are not identical to the game played in the Gulf Coast League.

In its online documentation’s section titled “Game Universe Terminology,” the closest definition I found was of a “saved game,” which is

one ‘universe’ of baseball in OOTP. A saved game could contain one league, five leagues, one league with multiple ‘subleagues,’ or any other combination of leagues and subleagues.

A “universe” of baseball is such a broad term I’m not going to try to define it; instead I re-viewed “New Standard Game” as meaning “New Game Universe.” And since then, I’ve slowly been learning what that universe includes — and how to play an MLB game the OOTP way.

A Sentence in Need of Clarification

Sometimes I read a sentence so laden with academic jargon that its purpose is defeated. One such sentence appears in Voigt’s The Art of Syntax, a book built on an interesting premise, but one that, at times, is unfilled. Here’s the sentence.

Ordinarily, a coordinated (independent) “but” clause is worth more to a sentence than a restrictive (subordinate) “if” clause; Kunitz’s exactly parallel lines, using a limited and reshuffled lexicon, redress the grammatical power of the rational objection. (30)

Specifically, this is the wording that caused me to pause: “redress the grammatical power of the rational objection.” How can a “rational objection” have “grammatical power”? Somehow, according to Voigt, both Kunitz’s parallel lines and his vocabulary set right the rational objection’s “grammatical power,” but how?

Further, why is a coordinated clause worth more to a sentence than a restrictive one? How much more is it worth? And what determines a clause’s worth?

Finally, what is the connection between the sentence’s first independent clause and its second? The sentence would flow better if its second clause explained “worth more” instead of detouring.

Not Expecting Much from Giant 2016 Draft

Based on their past draft performance, I don’t have high expectations about how the New York Giants will do in the 2016 draft. They have two many needs: defense line, safety, linebacker, offensive line, end, running back. So where do they start? With the “best” player available? Unfortunately, since Joe Don Looney they have not been that good at identifying them. For example, in 2012 their pick of David Wilson seemed to be an overreaction pick after the Bucs selected Doug Martin the pick before. Both Bobby Wagner and Lavonte David were still available, but then the Giants rarely draft linebackers in the first few rounds. (Who’s behind that thinking?) Further, in 2016, the top two linebackers, Jaylon Smith and Miles Jack, are both recovering from significant injuries, which should make them even less attractive to the Giants. They need help NOW. The next highest-rated linebacker, Leonard Floyd, is rated #13 on’s top 100, but he only weighs 231, labelling him “painfully thin.” In 2015, the Giants were the ninth worst against the run, so if they were going to draft a linebacker, they need a run stopper.

Safety? They are as weak at safety as Popeye is without his spinach. gives their top-rated safety, Duke’s Jeremy Cash, only a 5.68 rating. That is not a rating worthy of a #10 pick. Further, states that “Cash is much too stiff to be asked to make a living in coverage and any team considering him will likely view him as a box safety,” something the Giants do not need to spend a high pick on. So, let’s eliminate the safety position as the one to spend a top pick on.

To be continued