MLB The Show: 15 — The Reformation of Tom Brady

Yesterday, the National Football League announced that New England Patriots quarterback Tom Brady would be suspended four games as a result of his role in the Great Football Deflation Scandal of 2015. This was a big deal, not just to the Patriots or the entire league, but to Tom Brady himself. You see, Tom Brady is an intensely competitive man. You might even call him a “competitor”, if you were an NFL announcer and had to fill several hours of airtime with the sound of your voice without saying anything meaningful. Tom Brady isn’t the sort of guy who will take to sitting on the sideline. Instead, he’s going to do something drastic. He’s going to join the professional sports league where tampering with the ball is a storied and celebrated act.

Tom Brady is going to play Major League Baseball.

MLB® 15 The Show™_20150511213254
Continue reading

Advertisements

Once Upon A Time In The Projections

I’ve been thinking a lot about baseball player projection system lately, which is just a fancy way of saying I’ve been sick and unable to play 3d video games without feeling nauseous or write creatively so my brain had to go off and do something dumb. A few days ago, Fangraphs published Dan Szymborski’s 2015 ZiPS projections for the St. Louis Cardinals. If you follow enough of Cardinals/sabermetric twitter you know that Szymborski took issue with a particular Cardinal blogger who questioned the necessity of these projections and made some fundamental mistakes regarding the ZiPS process. Piling on Cardinals fans is a national pastime for some reasons we don’t bring on ourselves (the media’s terrible Best Fans in Baseball Narrative) and some reasons we do bring on ourselves (I can’t even look at Cincinnati on the map without muttering “kiss the rings”) so the blog post was passed around, ridiculed, and pulled.

Social media drama is the last thing I ever want to care about, but the argument got me thinking. First off, I respect all the hard-as-hell mathematical work that goes into developing projections. I couldn’t do it. I wouldn’t even know where to start learning how to do it. Second, there is clearly an audience for projections–as demonstrated by the anticipation leading up to the ZiPS reveal. So it’s cool someone is putting in the hard work.

But what do good projections really tell us?  I haven’t been able to answer that question and it has stuck with me through a haze of cold medicine.  This isn’t just about ZiPS, or STEAMER, or PECOTA, or any projection system in particular but about the concept of projection systems in general.  What information are they providing?

“They give us a better idea of how players will perform!” you are shouting at your screen while you add my name to a list that includes Murray Chass.  And you’re right, that’s exactly what they do. Maybe.

Bear with me on a thought experiment (groan, I know) while I consider two hypothetical projection systems: the PERFECT system and the BEST system.

The PERFECT system: The PERFECT system correctly and accurately projects player performance. As indicated by its name, it gets nothing wrong. In December of 2013, the PERFECT system projected Matt Carpenter to get 709 plate appearances and a .272/.375/.375 triple slash. How does it do this?  I dunno. Let’s say that, to borrow heavily from the film Interstellar, it tracks batted balls in the future by the minute changes in gravitational fields as they travel backwards through space-time.

Now, the PERFECT system trivializes baseball in lot of ways and calls into question important concepts like free will and predestination.  But it also does one thing really well: it’s the only projection system in the goddamn universe that predicts Allen Craig will have a .266 BAbip in 2014. It’s also the only one that sees Pat Neshek coming.  The really weird stuff–the stuff that has a lot of value to predict–is only truly caught by the PERFECT system.

“That’s not fair!” you reply and move my name above that of noted blogger Murray Chass. “You can’t compare projection systems to literally seeing into the future!” Well I can because this is the internet and on the internet you can advocate for things as crazy as seceding New Hampshire from the Union or SEGA producing Shenmue 3. Also, I need something to compare with the next system.

The BEST system: The BEST system is a bit more realistic. This projection model is top-of-the-line.  Using all that math I don’t understand, it provides the most precise predictions possible without any knowledge of the future. I think we can all admit that (Interstellar notwithstanding) there is no way to measure all the random shit that happens in a baseball season.  And as someone who watched the Cardinals bat .330 for an entire season with RISP, I know for a fact that the sample size of an entire season isn’t enough to weed out all that random shit.

What the BEST system does, however, is successfully weed out all the random shit in the past stats, and uses that to provide an exquisite shit-free stat line for every player in the upcoming season. The BEST system is so good, its creators boast, that if the 2015 season were to be played 1000 times and the results averaged together, the numbers would be exactly what the BEST system projected for them.  This seems like a crazy boast, but the cast of the television series Sliders (which is still running in at least one universe) confirms that it is true.  The BEST system is just that good.

Every year, when you run the numbers, the BEST system is going to be named the most accurate projection system. In aggregate, that will be true. But what about each individual player?  Sure, the BEST system will be the system most likely to come the closest to the real numbers. But, by design, it will staunchly be unable to identify an outlier.  That’s not a bug. It’s a feature of a good projection system.

Remember how I said that playing the season 1000 times would result in averages that equal the BEST system projections?  And how great that was?  The problem is that 1 of those seasons is going to give you the PERFECT system projections.  And then the other 999 seasons are going to drag that pin-point accurate projection straight to the average.

What I’m saying is this: the problem with the BEST system is that it’s incredibly conservative. It will predict a decline from Allen Craig, yes, but not because it knows he will turn into a pumpkin  It is because his 2013 was also an outlier. The BEST system will never predict a collapse.  Similarly, it will look at everything about Pat Neshek and spit out some mediocre numbers, because of course it will.  No one could have seen that coming (and no one should be expected to).

This conservative nature is the problem with any good projection system, because conservative predictions aren’t terribly interesting. With the exception of minor leaguers, the BEST system as described above isn’t going to tell you a lot you couldn’t glean from a glance at the player’s age and MLB stat history. Which is a shame, because developing something like the BEST system that is so (on aggregate) accurate would be an incredible mathematical achievement. It just wouldn’t tell us anything about current MLB players.

This is why the really fascinating stuff in the ZiPS projections for the Cardinals isn’t, say, Matt Holliday’s numbers or Adam Wainwright’s numbers. Someone taking a wild guess or simming the year in MLB: The Show could come up with a triple slash of .275/.348/.456 slash line for Holliday. I don’t mean this a an insult to ZiPS, which of course is way more work than that, and will be more accurate for more players.  But a conservative prediction that Matt Holliday will continue a gradual decline is, well, not exactly a revelation.  And any good projection system will likely come to a similar, conservative result.

The interesting stuff in the ZiPS are projections from guys like Ty Kelly (.254/.333/.358) or Samuel Tuivailala (3.29 ERA, 28.3 K%). Kelly is a journeyman utility infielder with no MLB time projected to be about as good as Kolten Wong.  Tuivailala is a converted position player who rocketed through the system in two years on the strength of a  99 mph fastball. Obviously, a system that identifies guys like these who can be immediately productive at the MLB level would be very valuable. Maybe the BEST system as described above would do that, but the problem is that these projections–which are truly interesting, and the reason I like looking at ZiPS–are the most difficult to verify as reliable. Kelly’s numbers are based on the idea he receives 550+ PAs and god help the St. Louis Cardinals if injuries force the team into that situation.

While I like to look at projections and I respect the hell out of the work that goes into them, I’m sympathetic to the argument baseball old-timers put forward that they are meaningless.  The more accurate a projection system gets, the less it tells us that we didn’t already know.

Of course, projection systems published on the internet are mostly created to give us something to talk about in the off-season and I just wrote 1000+ words about them. So maybe I’ve already lost any argument I was trying to put forth.

 

MLB The Show – World War K: All Stars and aWARs

14header

Start from the Beginning – Episode 1: The History of the First Base War

Previous Episode: Halfway There

A Post on the Future of World War K (and my possible psychic powers)

There was once a time, before MLB.tv and interleague play, when the All-Star Game really meant something.  Most fans didn’t have a chance to see players in the other league unless their team made the World Series.  Seeing the most popular players in the other league, even for a single exhibition game, was a fun novelty in the middle of a much-needed break in the regular season.  But as teams in both league became more accessible to fans across the country, interest in the All Star Game waned and MLB went to great lengths to revitalize it.

First, MLB implemented “This Time It Counts”, awarding home field advantage to the winning league in the WS.  When that failed to bring in the ratings MLB desired, in 2024, the stakes were raised with “No, Really, This Time It Definitely Counts” in which the teams in the winning league were awarded an extra roster spot for the remainder of the season.  People thought that was rightfully stupid, so MLB petitioned the U.S. Congress to pass the “It Counts More Than Ever Act of 2037”, in which Federal highway funds were awarded to cities in the league winning the All-Star Game.  When even that wasn’t enough to get people interested in 2045, the United Nations issued its controversial UN Declaration of Making It Count, which denied human rights protections from fans of teams in the losing league.

Back in alt-2014, most of this was in the future.  The All Star Game was a glamorous spectacle about honoring fan favorites and stupidly determining home field advantage.  And the two starting pitchers for the American League and National League were no surprise.

Allstar showdown

Indeed, the ASG would be a rematch between the deranged mind of Mike Mussina inside of a robot body and the time traveling pitching machine chosen by Mike Trout to save baseball. But they weren’t the only machines chosen to represent their respective leagues in the exhibition game.  In fact, all three position player Robot Masters were in the lineup, with Dixie Dirtbag holding down shortstop in the NL, Preacher Cobra at C and Flash Money at RF in the AL.

Allstar Lineup

Continue reading

MLB The Show – World War K: The King in the North

6header

Episode 1: The History of the First Base War

Previous Episode: The Frame Game (April Recap)

The theories of the 2010s pitch-framing analysts are lost to history, purged after a reactionary movement seized sports media in 2031 and instituted the Heyman Doctrine, a brutal set of reforms that made the use of any advanced statistic less predictive than ERA punishable by death.  But we do know that these statistics informed the 2014 Kansas City Royals’ decision to acquire Jose Molina from the Tampa Bay Rays.  Molina, a month away from turning 39 at the time of the trade, could otherwise hardly be seen as a trade target for a team that hoped to save the future of baseball in 2014.  He had a career OPS hovering around the low .600s and had never received more than 350 PAs in a season.  If not for the pitch framing craze of the 2010s, why else would anyone trade for Jose Molina?

knowthetruthwhat is thatsoro

ahura

Continue reading

MLB The Show – World War K: The Frame Game (April Recap)

5header

Episode 1: The History of the First Base War

Episode 2: And We Will Always Be Royals

Episode 3: Verland Before Time

Episode 4: The Candyman Can

T.S. Eliot once wrote that April is the cruelest month.  But what the hell did he know?  He wrote a book that inspired the musical Cats.  His hands are  stained with blood.  In baseball, April brings hope and uncertainty.  The passage of the month brings the first significant statistical endpoint to evaluate players or the team as a whole.  However, almost all of these stats–even win/loss record–come with sample size caveats.  You can’t project how well anyone will do based solely on their April.  But that doesn’t keep people from trying.

Late into the month of April, it became clear that the Royal’s catcher, Salvador Perez, was suffering from overuse.  He was hitting worse than anyone else on the team, which caught Player/GM Pat Burrell by surprise.  Perez was supposed to be one of the few sincerely good players on the Royals.  Burrell decided that the team needed a quality backup catcher and veteran presence.  Someone to fill the role that Todd Pratt had during Burrell’s early years in Philadelphia.  Unfortunately, Todd Pratt was now 47 years old, so getting him out of retirement would be more than a chore.  Burrell would have to trade for a backup, and do so without giving up anything of significant value.

With that in mind, he went to the team’s advance statistics department for advice.  Unfortunately, the Kansas City Royals advanced statistics department had been gutted during the Dayton Moore years, and now consisted of nothing but shortstop Alcides Escobar sitting in a small office after every game and browsing Fangraphs.

framing

Continue reading

World War K Episode 2: And We Will Always Be Royals

 

ep2header

Episode 1: The History of The First Base War

 

It is said that nothing worth doing is ever easy, and this is doubly true of time travel.  The fabric of the past resists change, not unlike a stubborn mule or the American South.  To move a human-sized pitching machine from the war-torn hell of the year 2099 to the slightly less war-torn hell of 2014 is a process with many steps, and there are numerous things that could go wrong.  It is thought that the power-crazed Artificial Intelligence K.I.R.K.G.I.B.S.O.N. actually sent back an army of robot masters to destroy baseball, and only the six most hardy even survived the trip.

When the aged Mike Trout programmed the Strike-O-Matic to go back to 2014 to stop the robot masters, he gave it a simple enough mission.  The Strike-O-Matic was instructed to find Mike Trout in the past and join the Angels to defeat the nefarious plans of K.I.R.K.G.I.B.S.O.N.  Unfortunately,  Strike-O-Matic’s memory was stored on a Chinese knockoff “Zandisk” solid state hard drive, which Trout had purchased on eBay.  This flash memory was poorly insulated from the terrible magnetic effects of time travel, and by the time Strike-O-Matic arrived in the year 2014, everything it had been programmed to do was corrupted.

The Strike-O-Matic only had a vague idea that he had to join forces with the best player in baseball and outplay some other robots, but everything else was lost to the corruption.  Ever resourceful, Strike-O-Matic turned to the resource that it assumed was the most reliable–networked crowdsourcing.  Strike-O-Matic didn’t understand that in 2014, the internet was only quasi-regulated and that people still thought “trolling” was fun.  Also, its irony meter had been destroyed by the massive influx of irony created during time travel, so it took the first response it received as the gospel truth.

twitter

Continue reading

World War K: The History of the First Base War (MLB: The Show)

As we venture into the new century, several generations have known nothing but the Base Wars.  Robot versus robot.  Robot versus man.  Man versus man.  It is not news.  It is not history.  It is merely life.  For the young people of the year 2099, it is nothing to go to the ballpark and see a robot with tank treads for a leg attempt to decapitate a floating robot with a laser sword.  The cyber-checkpoints are routine, and the e-police are just another fixture on the street corner, twirling their e-batons and compiling their e-donuts.

There was a time before this neon mecha-hellscape.  Once, you could walk down the street without seeing the roving gangs of hobodroids, shaking down the robourgeoisie for their laser-rubles.  It was a simpler time, before the airs was filled with the scream of holodrones and we lived under the constant threat of quantum terrorism.  How did we get here?  And how will this end?  The answer to both of those questions is one and the same.  Because of time travel.

This is the history of the First and Last Base War.

WWK

Continue reading