NERD Game Scores: Yankees-Angels’ Somewhat Urgent Event

Devised originally in response to a challenge issued by viscount of the internet Rob Neyer, and expanded at the request of nobody, NERD scores represent an attempt to summarize in one number (and on a scale of 0-10) the likely aesthetic appeal or watchability, for the learned fan, of a player or team or game. Read more about the components of and formulae for NERD scores here.

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Most Highly Rated Game
New York AL at Los Angeles AL | 19:05 ET
Eovaldi (82.1 IP, 98 xFIP-) vs. Shoemaker (78.2 IP, 101 xFIP-)
The introduction of the wild-card game to baseball’s postseason format in 2012 has problematized slightly what precisely one means when saying that a club has “reached” or “qualified for” the playoffs. Technically, that wild-card game is denoted as a playoff contest. For the team that loses it, however — and for that team’s supporters — the pleasures typically associated with postseason baseball are incredibly short-lived. For that reason, the component of NERD team scores that accounts for a club’s playoff odds — which component is weighted more heavily in direct proportion to the proximity of those playoffs — is informed not by the relevant club’s overall playoff odds, but rather by the club’s odds of reaching the divisional series. Specifically, the closer to 50% a team’s odds of qualifying for the divisional series, the greater positive influence over that team’s NERD score — the logic being that such a club is playing the highest-leverage games in the league.

One finds, in the Yankees and Angels, two of the three clubs in closest proximity to that 50% mark. Regard, the seven clubs within 20 points or less of same:

Team Odds
Astros 67.1%
Royals 65.1%
Yankees 46.2%
Pirates 45.9%
Angels 37.8%
Cubs 32.3%
Blue Jays 32.3%

New York currently possesses the least certain future with regard to the postseason. Pittsburgh trails them by only a slight amount. And then the Anaheims’ divisional-series odds of 37.8% place them third. While it’s probably fair to say that winning or losing this particular game is not of the greatest urgency to either the Yankees or Angels, it’s also accurate to say that urgency is most present in this encounter of all those present on today’s schedule.

Readers’ Preferred Broadcast: Los Angeles AL Television.

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An Unchanging Truth: Positional Offense Through History

Baseball has seen many changes in the past 100 years. Some changes are significant enough, retrospectively, to define an era. There was the Deadball Era from roughly 1901 to 1919, characterized by an emphasis on pitching, defense, and a low run-scoring environment. The Liveball Era began in 1920, ushered in by Babe Ruth, cleaner baseballs that were easier for batters to see, and rule changes like banning the spitball. When the offense started to overpower the game, more changes were made to temper that environment, like the introduction of the ground-rule double in 1931. Before that, a ball that bounced on the field and over the fence was considered a home run.

There’s Jackie Robinson’s debut in 1946, and the following years when African-Americans finally were permitted to play in the majors. There’s expansion, the lowering of the pitcher’s mound, the introduction of the designated hitter in the American League, free agency, more expansion, newer ballparks, PEDs, testing for PEDs, and an ever-expanding strike zone — all marking the beginning of other, overlapping eras. And then there’s the sabermetrics revolution — using advanced statistical modeling and analysis to construct rosters, manage bullpens, and deploy extreme defensive shifts.

All of these changes in baseball and yet, for the last 100 years, the offensive hierarchy among defensive positions has remained pretty much the same. First basemen, right fielders, and left fielders produce more offense than the average player; catchers, second basemen, and shortstops produce less. It was that way in 1914, in 2014, and in nearly every season in between. Clean ball, dirty ball, higher mound, lower mound, PEDs, no PEDs — whatever the conditions in the game and on the field, first basemen, left fielders, and right fielders have dominated on offense.

Let’s examine more closely this relationship between offensive skill and defensive position — both the historical averages and outlier seasons.

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The Second Arrival of Robbie Ray

We keep learning more about baseball. Every year, we learn things we didn’t know. Every year, we have new data to back up things we might’ve already suspected. The level of knowledge is ever-increasing. You’d think that might make baseball analysis easier. The more you know, the more you should be able to say, right? It’s true, now we can say more — and we can say more with data. But if anything, all this knowledge is making everything more complicated. The more we learn about the game, the more we learn about the gray areas. The more we learn about the gray areas, the more we have to hedge against making strong, conclusive statements.

So it’s more complicated to do player analysis, and it’s more complicated to do transaction analysis. At least, it’s more difficult to assign the winner and the loser of a transaction. There are generally too many different things at play. I think it’s notable, then, when strong conclusions are still reached. It’s notable to me when the analytical community comes down strongly on one side of something, because situations are grayer than ever. It must mean something when a firm consensus is reached despite all the complexities.

With decreasing frequency do writers come out strongly against a given transaction. So it’s worth reflecting on the trade that sent Doug Fister from the Tigers to the Nationals. That one didn’t make any sense. That was a pretty clear steal, on the Nationals’ part. Everybody agreed the Tigers didn’t get enough. I know, because I was one of them. The deal looked terribly lopsided at the time, which is something we don’t get to experience so much anymore.

And you know what? It probably was lopsided. The Tigers probably didn’t get enough. The trade legitimately sent waves through the industry. But you have to look at where we are now. Regardless of whether this could’ve been predicted: Robbie Ray looks like he might be emerging. Ray’s talent is coming to the surface.

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FanGraphs Audio: Kiley McDaniel on the Second of July

Episode 577
Kiley McDaniel is both (a) the lead prospect analyst for FanGraphs and also (b) the guest on this particular edition of FanGraphs Audio — during which edition he discusses, among sundry matters, baseball’s looming international-signing period.

Don’t hesitate to direct pod-related correspondence to @cistulli on Twitter.

You can subscribe to the podcast via iTunes or other feeder things.

Audio after the jump. (Approximately 1 hr 19 min play time.)

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FanGraphs After Dark Chat – 6/30/15

3:22
Paul Swydan: Hi everybody!

Join Jeff and myself tonight at 9 pm ET for all the baseballing action you can act on.

It’s Jeff’s last chat for two weeks, so get in all the fancy Royals questions you’ve dying to ask! See you soon!

9:01
Paul Swydan: Hi guys! Let’s do this.

9:02
Comment From Jung Ho Kodos
Head to head league where I’ve taken second place 5 years in a row. Should I trade Joc for Stanton if I’m comfortably in the playoff picture and can survive the time between now and when Stanton comes back, or should I be worried about Stanton’s power when he gets back?

9:03
Jeff Zimmerman: I would worry if Stanto makes it back at all

9:03
Paul Swydan: I would absolutely be worried about his power when he comes back, because hand injuries tend to take longer to get over.

9:03
Paul Swydan: That’s another good point. Stanton’s injury is a clear sign that the Marlins can sell.

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Billy Hamilton, As Advertised

Monday, against the Twins, Billy Hamilton stole four bases. In so doing, he reached 40 steals on the year before anyone else reached 30. Probably even more impressive: Hamilton now has more steals than exactly half the teams in baseball. He has more than the White Sox and Dodgers combined. Over the course of the past month, Hamilton has stolen 20 bases, and second and third place on the leaderboard combined have stolen 19 bases. Over that same month, Hamilton has more stolen bases than he has hits.

It’s funny now to reflect on some of the things I wrote in 2014. Early on, when Hamilton started to hit, I decided he wasn’t a caricature. When it all ended, I asked why Hamilton hadn’t been a base-stealing dynamo. Now Hamilton is a base-stealing dynamo. And he’s a terrible hitter. He can’t hit, but he does run, and when he’s on the other side of things, he can play a mean center field. Which means, in a way, Billy Hamilton now is something of a caricature. He’s an exaggeration of a player type, which is exactly how he was advertised.

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Tempering Expectations for Atlanta’s Matt Wisler

Matt Wisler’s big-league debut went about as well as anyone could have expected. The 22-year-old tossed eight innings of one-run ball two Fridays. His performance was good enough to outduel Jacob deGrom, as he led the Braves to a 2-1 victory over the Mets. His second start didn’t go as swimmingly, however: the Nationals tattooed him for six runs in four innings of work. He didn’t strike out a single one of the 21 batters he faced.

Wisler’s primarily a fastball-slider guy, and both pitches have the potential to be plus, according to Kiley McDaniel. His fastball was clocked as fast as 95 mph in his big-league debut, but it’s averaged closer to 92 overall thus far. Both of Wisler’s strikeouts — yes, he’s only had two — came by way of his low-80s slider. The first victim was Curtis Granderson.

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MLB Urges U.S. Supreme Court to Deny San Jose Appeal

Overshadowed by last week’s series of momentous decisions by the U.S. Supreme Court, Major League Baseball recently filed a brief with the Court urging it to reject an appeal by the city of San Jose, California in the on-going dispute over the future home of the Oakland Athletics. As I noted at the time San Jose filed its appeal back in April, the city is hoping to challenge MLB’s refusal to approve the proposed relocation of the A’s to the city in court under the Sherman Antitrust Act.

Over the last two years, however, both the trial court and court of appeals have dismissed San Jose’s suit in light of professional baseball’s nearly century-old antitrust exemption. The city is now asking the Supreme Court to take its appeal and overturn the controversial doctrine in order to hold MLB accountable under the Sherman Act, like all of the other major U.S. professional sports leagues.

As one might expect, MLB’s brief instead argues that San Jose’s appeal should be rejected for several reasons. In particular, MLB devotes much of the first half of its brief to the contention that San Jose lacks standing to sue — a requirement in which the plaintiff must show that it has a personal stake in the outcome of an actual legal case or controversy (as opposed to a hypothetical, future dispute) — and therefore can’t sustain its case against the league.

MLB challenges San Jose’s standing on several grounds. The primary basis of MLB’s attack, however, focuses on a recent California state court decision holding that an option agreement between the city and the A’s for the land on which a new stadium is to be built is invalid under various state and municipal laws. Specifically, the California court determined that San Jose had illegally transferred the land to a governmental authority in an attempt to circumvent laws requiring that a public referendum be held to approve the use of any tax dollars to build a sports facility.

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Stats Diagram: Pitching Stats

If you enjoyed the previous diagrams for position player WAR and offensive stats, then you’ll enjoy the diagrams for pitching stats. Just like the previous two diagram posts, the best instructions on how to precisely calculate the stats are in our library. However, the diagrams provide a visual conceptual overview of what affects the different pitcher stats.

The first set of stats are divided into three subcategories, based on denominator. The first is balls in play (BIP) and the pitcher batting average on balls in play (BABIP) stat. This is the same as batter BABIP except it’s calculated from the pitcher’s perspective. Total batters faced (TBF) is the second subcategory, where there are two stats: K% and BB%. These again mirror the batter’s version.

The innings pitched (IP) is the subcategory with the most familiar pitching stats. Innings pitched effectively counts every out the pitch has made, divides that by three to get IP. The most basic stats IP-based stats are K/9, BB/9, and HR/9. Walks plus hits per inning pitched (WHIP), a stat we don’t use a lot at FanGraphs, divides the total number of hits and walks by the number of innings pitched. Earned run average (ERA) does the same thing but also scales it to a full, 9-inning game. Fielding independent pitching (FIP) and expected FIP (xFIP) both use defensive-independent outcomes to estimate ERA. The FIP constant scales the stat to be comparable to ERA. xFIP is the same as FIP except for the HR input is change to fly balls (FB) and converted to HRs by multiplying FB by the league average HR/FB ratio.

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Picking the 2015 American League All-Stars

Yesterday, we tackled the National League’s 34 most deserving candidates, so today, we’ll do the American League. When it comes to picking players, I lean very heavily towards in-season performance, as I tend towards the camp that sees the game as a reward for the players more than a showcase for the fans. It is both, of course, and trying to serve both masters can make for some tricky decisions, but I’d rather reward a deserving player for a big first half than simply invite the same players every year based on their legacy. I know others see it differently, and that’s fine; I personally just find it more interesting to recognize performance than name-value.

In putting this together, I broke the 34 roster spots into 21 position players and 13 pitchers, and I also held to the rule that every team had to be represented. Injured players were not considered, so while Andrew Miller will likely be picked and then replaced, I didn’t bother with that formality. And while the only stat listed is a player’s WAR, it’s just there for reference; I didn’t select the players based solely on their WAR totals. Oh, and for pitchers, the WAR listed is a 50/50 blend of FIP-based and RA9-based WAR.

Okay, on to the team. We’ll go position by position, with the starter listed first.

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