What Happened to the Moneyball Draft?

One of the most famous scenes in Moneyball is that of the 2002 Draft.  Beane goes all sabermetric, to the riotous chagrin of his old-school scouts.  He drafts Jeremy Brown in the first round and doughnut crumbs spill from the gaping mouths of baseball's old guards.  Beane's draft strategy was centered around minimizing risk.  He targeted college players under the theory that their stats were more reliable and their development more predictable.  In the scene Paul DePodesta cranks out hidden, undervalued players with few keystrokes from his laptop, apparently basing all his decisions on raw college baseball stats.  That year, Oakland didn't draft a player out of high school until the 18th round.

Yet, of all the huge, revolutionary ideas introduced to the general population in Moneyball, one the most dramatized has largely been discarded.  Though college players' development can be more reliably predicted, it has been discovered that college stats don't hold much water.  Today, cutting edge teams acknowledge that scouting reports are still the best available option for evaluating amateur players, and look to integrate their scouting data with statistics.  It's safe to say that the edge the A's believed they had in the amateur market was not nearly as significant as they thought.  To see how little has changed in drafting strategies since the A's famous draft, I looked at the amounts of different types of players who've been picked int the first round of the draft. (College players = dark gray, High school= gray, JC = light gray)

And here's the college/high school ratio by year (first round only)

The A's themselves have, at least partly, reneged on their own strategy.  After drafting exclusively college players in the first round from 2002-2011, they have drafted four high schoolers in the 2012 and 2013 first rounds.  Admittedly, Jeremy Bonderman is still the last high school pitcher to be drafted by the A's.  But maybe that's just because Billy Beane really likes his chair.

Visualizing Statistical Stablization

I was listening to the Effectively Wild podcast from a few days ago, and Ben and Sam were going through the inevitable yearly motions of dismissing early season performance due to small sample size, yet explaining that there is no magical number that stats stabilize etc. etc.  I became interested in seeing what such stabilization looks like.  I decided to dig into the Retrosheet event files, and I graphed out cumulative batting averages over time for various players/other entities.

First I started with individual players, which clearly demonstrates the variability you can have in the first couple months of the season.  Especially a player like Punto,  who didn't play every day, or get full at bats when he did, doesn't seem to attain any sort of stability until July at the soonest.  Below is what all three look like relative to each other, with the league average added in for comparison.

The league looks pretty stable, right?  Here's what that line looks like on its own scale.  Even the league wide batting average doesn't stabilize until late May.  Concerned about Scooter Gennett now?

Finally, I was wondering what variances on the player (Jimmy Rollins), team (Oakland), and league level looked like relative to each other.  The specific team and player were chosen only because both ended up with nearly league average numbers.

Here, also, is a table of the variances of each sample of the cumulative average, subdivided by month.

months	April	May	June	July	August	September
jrollvars	1.2059766	0.7116112	0.4704438	0.3695916	0.3124211	0.2803761
oakvars	2.0644219	1.0208267	0.6871219	0.5282449	0.4226945	0.3568851
mlbvars	0.1070076	0.06255327	0.04570331	0.0372675	0.03044601	0.02613776

I think it's interesting that Oakland's variances are consistently higher than Rollins', probably due to greater changes in the underlying talent producing the numbers.  The league's changes are much less significant, yet tangible in comparison to team and player variance.  It should be noted that I multiplied the batting averages by 100 to compute the variances, i.e. I used 245 instead of .245.  Hope this was interesting. Thanks for reading.

A Formulaic Alternative To Hall-Of-Fame Voting: The bSHI system

With the election of four new players of the Hall of Fame last week, the time of the year when my twitter gets all clogged up with self-righteousness has finally come to an end.  For most of the year, following baseball on the internet is an enjoyable and interesting pursuit.  But when it comes around time to argue about whether a bunch of aging, retired men are worthy to have their old shoes displayed in a museum in upstate New York,  I really just want to stick my head in a deep fryer until the whole thing blows over.  It's not that I'm pro-Sabermetrics and hate how the old-school guys vote, or even the other way around.  I'm tired of the whole ordeal, the ceaseless personal-agenda advancing and general dick-wagging that goes on each year.  I'm done.  I used to care about the Hall, but the very people who are supposed to promote it, and create interesting discussion around it have ruined it for me.

The irrational grudges held by
writers like Dan Shaughnessy
are exactly the kind of rationale
bSHI is designed to emulate.

But fear not! I have a solution. The best thing to do, at least from my perspective, would be to remove the human element entirely from the induction process.  The best way to do this is through a statistical rating system.  There have been attempts at quantifying worthiness for the Hall, most notably Jay Jaffe's JAWS system.  Which is alright.  But mine's better.  Like, way better.  I estimate that it's 257 per-cent better, for those of you who don't question anything that has a number assigned to it.  The problem with JAWS is that it focuses too much on how good the player was.  To only focus on precisely how good a player was, adjusted for era and all those things, is ignoring a much larger truth.  People don't vote like a computer.  People are biased, and are primarily motivated by personal grudges, idiosyncrasies and emotional favoritism.  My system attempts to emulate the voting processes of the average BBWAA voter, and in doing so creates hands down the best of the best system for determining who is in the Hall of Fame.

I would like to establish that in this article, I will be evaluating hitters only, since pitching evaluation is primarily subjective.  I prefer to deal in hard data, so I'll leave evaluating pitchers for another time.

To start out, we have to ask ourselves, what do BBWAA members look for when evaluating a hitter?  That question's actually pretty easy.  There are precisely five criteria upon which Hall of Fame candidacy is evaluated: Awards, Classiness, Grit, Fear, and RBIs.  Here's how I came to define each of these five parameters:

What Class!
Completely by random,
Walt Dropo is tied for
most Classy among
all eligible players, with a
100/100 Classiness rating.

• Awards:  Everyone knows that the number of awards a player has won over his career goes a long way to signifying how dominant they were within their own era.  This one was pretty easy to calculate.  I just added up the number of awards a player won in his career and divided that by the amount of years he played.  Simple, but powerful.
• Classiness:  A perennial analytic favorite of sportswriters, the beautiful thing about evaluating the Classiness of a player is you don't need any sort of large sample when trying drawing a conclusion.  Did the player asked you how your wife was doing once in the Montreal visitor's clubhouse in July of 1984?  Well that's enough confirmation for a solid plus-plus Classiness rating.  Did the player want to fly home after a long road trip in 1998 so he declined your request for an interview?  Scum.  Well below average Classiness.  See how easy it is to judge the character of another human being?  Since I felt that I myself was not qualified to make individual decisions on players' Classiness ratings, I opted for the next best thing, assigning each player a random number from one to one-hundred for their rating.



Pound that Cuervo you Gritty
son-of-a-bitch! David Eckstein
ranked first among eligible
post-war hitters in Grit.

• Grit: When I sat down months ago to begin the design of the bSHI system, the word "Grit" was the first thing I wrote when I put pencil to paper.  Grit is a key factor into how BBWAA writers evaluate players, and it's easy to see why.  A player's statistical contribution is all fine and dandy, but we all know what really matters is how he plays the game.  Does he play with heart, with guts?  Does he play an intelligent game?  Does he sacrifice his body to make the play? Does he hustle all the way to first base, and then slide head first for no reason? These are all questions that can be answered with my proprietary new Grit statistic.  As I said, the statistic I developed to evaluate Grit is proprietary, so here it is:

HBP+SF+SH-GIDP+3B+200 = Grit

Tim Raines is mentioned multiple
times during the author's
discussion of the Fear statistic.

• Fear: This is often the most common question asked by BBWAA types in their discussions of Hall candidacy.  Sure, Tim Raines was one of the greatest base stealers of all time, but was he feared?  Did the pitcher quake in his shoes and poop a little every time Tim Raines stepped into the batters box?  Did the father, or father like figure, in your life take you to the ballpark to when Tim Raines came to town?  Sure, Tim Raines was an excellent defensive outfielder, but did the batter mutter, "Damn! Damn it all to heck!" ever time he saw his just-struck'ed fly ball arching in a futile manner in Raines' direction?  I could go on.  The point is, Fear is a key criteria toward determining Hall worthiness, and I have developed another proprietary statistic to accurately quantify it.  Here it is:

.5*BB+IBB = Fear

Abner Doubleday had no
goddam idea what he was
doing.

• RBIs: Of course, I have to throw a bone to the sabernerds.  I acknowledge that there is a significant contingent of voters that does not weight the above four categories heavily during their consideration of their Hall of Fame ballots.  For this reason, I have included a statistic heavily correlated towards value, as seen from the perspective of the statistically inclined.  RBI's is the perfect sabermetric stat, as it tracks very well how many runs scored while a player was batting.  Or, you could say, how many runs the player created?  That being said, RBI's isn't a perfect stat, as a player is credited with an RBI if they walk or are hit by a pitch with the bases loaded.  Whoever the fuck invented RBIs, Abner Doubleday probably, must've been having icepick lobotomy or something.  The stat is literally called Runs Batted In.  You don't bat in a run if you don't hit the ball, dumbass! Anyway, it's a pretty good stat other than that one fucked up part.

Now, it's time to bring it all together.  First, I need my population of eligible players.  My sample came from all player in the Lahman database with 10 years of playing time, and over 2,000 at bats (this filtered out the pitchers, I hope).  As all five statistics are measured on their own scales, I needed a way to standardize them.  To do this, I used a scale much like the one used by stats like OPS+ (aside from the park factors and shit, ain't nobody got time for that).  I took each of the statistics divided them by the amount of years played (except for Classiness, which isn't a counting stat) and then divided them by the average per year of the same statistic across the entire dataset.  Confused?  It looked a little something like this:

Grit+ = (Grit/Years)/ pop.mean(Grit/Years)

Genius.  Now all statistics were measured in percentage above or below the population mean.  This resulted in the (still proprietary) stats Awards+, Class+, Grit+, Fear+ and RBI+. I then took the mean of all five of these statistics relative to each player, and voila!, bSHI is born! (It stands for Batting Specific Hall Induction, in case you were wondering).

The final thing I needed to do was define the parameters for which I will determine who is in the Hall and who's not.  For this, I came up with an novel idea, predicated on a thought: The Hall of Fame is doomed, due to its irreversible upwards trend of admission.  I mean eventually, if they keep going the way it is, the Hall of Fame will become infinitely big, and then it'll be mathematically impossible to see the whole thing!  My idea, instead, is to keep in the top two-hundred.  Two hundo, no more, no less.  Yes, that means someone gets kicked out ever time someone gets in.  And wouldn't that be awesome!  Imagine the satisfaction if your favorite childhood hero gets in, kicking out some antiquated golden-oldie from your rival's past.  So those are the parameters.  Two hundred hitters. No more, no less.  Ladies and gentlemen, I present your new Hall of Fame, ranked by bSHI in descending order.

Yikes! Zounds! Gadzooks!  Obama could be making an illuminati sign with one hand and legalizing abortion with the other, and generate less controversy than this list.  But the real question is, how well did my formula emulate the decisions of the BBWAA?  Well, of the 73 hitters with over 3,000 ABs elected by the BBWAA as players, 63 of them were also elected by the bSHI system.  That's 86 percent! Pretty much the best you can get, in my opinion.  Let's take a closer look at who's out, who's in, and who's on the cusp.

SNUBS:

• Rickey Henderson and Lou Brock

Now, before you all call poppycock on the bSHI system, remember-- it is a statistical system designed to emulate Hall of Fame voting, not to evaluate how good a player was.  As the bSHI system is now, stolen bases are completely ignored when evaluating a player, and it shows with the omission of these two.  But hey, to make an omelette you gotta crack a few eggs, right?  Besides, Rickey rated very poorly in both Classiness+ (of course) and (surprisingly) in Grit+.  Pair that with an average RBI+, and Rickey ranks at 285 all time, just below Nomar and a little above Mike Cameron.  Brock is much much lower, coming in at 333, between Leon Durham and Gus Suhr.

• Carlton Fisk

Well that's unfortunate. But you can't let everyone in, right?  Also, a guy like Fisk not being in is what really make the bSHI system interesting.  Due to its incredibly arbitrary nature, a couple of random ass good players won't get in, and that sucks for that player and his fans.  For everyone else it's hilarious!

• Tony Perez

He actually wasn't that good! Nice call bSHI! Perez was the worst current Hall of Famer according to bSHI, bringing in a measly 106 bSHI.

• Willie Keeler, Harmon Killebrew, Harry Heilmann, Willie McCovey, Rabbit Maranville and Nap Lajoie.

Meh.

CURRENT PLAYERS:
Due to the top 200 nature of the bSHI system, several current players would have already been elected.  Of course, they're place in the Hall isn't guaranteed, as they could always start sucking and fall back below the threshold.  The players below are presented in order of their bSHI scores.

• Albert Pujols, Alex Rodriguez, Ichiro, Miguel Cabrera, Derek Jeter

All of these are pretty obvious.  Of course, the bSHI system takes into account steroid in its "Classiness" metric, but A-Rod grades out surprisingly well, with a 165.9 Class+.

• Mark Teixiera, Ryan Howard, Joe Mauer, David Ortiz, Chase Utley, Adrian Gonzalez

Interesting.  All middle of the order hitters for competitive mid-2000's teams, (except maybe for Gonzalez), these player's notoriety gives them very high Awards+, and their ability to drive 'em from the middle of the order boosted their RBI+.

• Torii Hunter, David Wright, Matt Holliday, Shane Victorino, Carlos Beltran, Alfonso Soriano

• Jose Bautista

I list Bautista separate, as he is exactly the 200th and final member of the bSHI Hall of Fame.  Imagine how much discussion would be generated if the bSHI system was actually used?  Will Bautista continue to boost his bSHI score and get to a more comfortable place in the rankings?  Will he fall out of the Hall, forever condemning him to "Hall of Very Good" obscurity?  Will he be passed, and knocked out by another up-and-comer?  Will the Blue Jays bat him second, sapping his RBI+?  Will he get caught cheating on his girlfriend, casing his Class+ to plummet?  Aaaah! 

INTRIGUING PICKS

• Travis Fryman
• Red Rolfe
• Jimmy Archer

Hmmm... Intriguing!

Regardless of the actual results, I think we can all agree that the bSHI is probably the best future option for Hall of Fame voting.  At least we wouldn't have to see anything like this ever again.

Data Links:

---Complete bSHI data---    ---HOF Limited data---