There was a time when Griffin Canning looked like a sure-fire first-round pick in this year’s draft. The UCLA ace had a dominant 2017 season, ranking sixth in the nation in total strikeouts while exhibiting promising stuff, good command, and smooth mechanics. He seemed like the type of pitcher who could fly through a farm system and quickly make a big-league impact. Three days before the draft, Baseball America predicted that Canning would be selected by the Yankees with the 16th-overall pick.

Yet when draft day came on June 12, dozens of picks passed by without his selection. Every team in the first round passed on him, as did every team in the competitive-balance round. In the latter stages of MLB Network’s draft telecast, Canning was chosen by the Angels with the 47th-overall pick. On June 9, he appeared destined for a $3,458,600 bonus — that is, the value MLB had assigned to the 16th pick. Instead, he took the $1,459,200 earmarked for the 47th selection. In a matter of days, Canning watched his expected price tag get slashed by 58%.

The cause of Canning’s draft-stock plummet was an ominous MRI that revealed a vulnerable pitching elbow and shoulder. These injury concerns are not a surprise; last month, I examined the workloads of the draft’s top college pitchers and found that the star UCLA Bruin was used very heavily. His alarming usage rates and murky MRI warrant a deeper investigation of how longtime UCLA head coach John Savage manages his pitchers. Is Canning’s case emblematic of a culture of overuse in the program? Let’s check.

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No trade-deadline need has ever been clearer, has ever been more obvious, than the Nationals’ need to acquire some help in the bullpen. It’s been an annual concern, which means you could call the Nationals front office experienced, but the bullpen this year has been a disaster. They still have a massive lead in their division! A playoff entry is all but guaranteed. Yet the Nationals want to someday get beyond just making the playoffs. They’d like to win a damn series, and these last few months, they haven’t had good relievers.

Do you consider yourself a fan of our in-house statistics? The Nationals bullpen ranks last in baseball in WAR. Do you prefer to give more credit for events that have actually happened? The Nationals bullpen ranks last in baseball in RA9-WAR. If you’re bigger on storytelling statistics, the Nationals bullpen ranks 26th in baseball in WPA. To address the area, the Nats have swapped with the bullpen that ranks 27th in baseball in WPA. Here are the players:

Nationals get

• Sean Doolittle
• Ryan Madson

Athletics get

• Blake Treinen
• Jesus Luzardo
• Sheldon Neuse

On paper, this is a big double-get for the Nats. On paper, these were some of the better relievers available. Certainly, moving forward, Dusty Baker can feel better about his bullpen than he did yesterday or the day before. The risk is that things aren’t always as promising as they look on paper. The Nationals know that better than most teams.

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Devised originally in response to a challenge issued by sabermetric forefather 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.

How are they calculated? Haphazardly, is how. An explanation of the components and formulae which produce these NERD scores is available here. All objections to the numbers here are probably justified, on account of how this entire endeavor is absurd.

Most Highly Rated Game
New York AL at Boston | 20:05 ET
Tanaka (102.0 IP, 88 xFIP-) vs. Price (53.0 IP, 104 xFIP-)
Were the season only a month or two old, the author’s haphazardly constructed algorithm would have likely identified this afternoon’s Giants-Padres games as the day’s most promising — based, that, on what appears to be that contest’s superior pitching matchup (based on 2017 performance, at least). However! As the season continues, the aforementioned algorithm weighs more heavily the seasonal leverage of the clubs involved. San Francisco and San Diego, possessing no reasonable chance of qualifying for the postseason, are playing what amounts to a well-attended exhibition game today. As for New York and Boston, however, each possesses a very reasonable chance, thus making the consequences of any one game (such as this one) much greater.

Readers’ Preferred Broadcast: Boston Radio.

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When I first spoke to Clint Frazier, he was 18 years old and playing in the rookie-level Arizona Summer League. A few months removed from being selected fifth-overall by the Cleveland Indians, he had a sky-high ceiling and a lot to learn. He also had — as I wrote in the introduction to the interview — “as much power as any player who was taken in the 2013 draft.”

The Loganville, Georgia native is now a Yankee, having gone to the Big Apple as the centerpiece of last year’s trade-deadline deal that sent Andrew Miller to Cleveland. He made his big-league debut thirteen days ago.

On Friday, I asked the colorful outfielder if he is essentially the same guy I interviewed four years ago.

“I’m a more experienced guy,” answered Frazier. “When I was younger, I was seeing beyond the fence — I was trying to hit a lot of home runs. Now it’s more of just being a hitter, trying to square up the baseball and letting the tools that I have play.”

I reminded the rookie that he’d talked about the importance of using the whole field in our earlier conversation. Read the rest of this entry »

Devised originally in response to a challenge issued by sabermetric forefather 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.

How are they calculated? Haphazardly, is how. An explanation of the components and formulae which produce these NERD scores is available here. All objections to the numbers here are probably justified, on account of how this entire endeavor is absurd.

Most Highly Rated Game
New York AL at Boston | 16:05 ET
Severino (106.2 IP, 69 xFIP-) vs. Sale (127.2 IP, 61 xFIP-)
This game features one of the best pitchers in the American League by every reasonable measure against the actual best pitcher in the American League by every reasonable measure. What else it features is a pair of clubs with encouraging but inconclusive postseason futures. This, like almost anything including bufala mozzarella, is a very promising recipe.

Readers’ Preferred Broadcast: Boston Radio.

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Each week, we publish north of 100 posts on our various blogs. With this post, we hope to highlight 10 to 15 of them. You can read more on it here. The links below are color coded — green for FanGraphs, brown for RotoGraphs, dark red for The Hardball Times and blue for Community Research.
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Nearly a month ago, Dave Cameron opined that the Red Sox ought to cut ties with Pablo Sandoval. On Friday the Red Sox acquiesced.

Just two-and-a-half years into a five-year, $95-million deal, Sandoval was designated for assignment on Friday. In parts of three seasons in Boston, Sandoval produced three below-replacement-level marks, totaling -2.6 WAR. He’s owed about $49 million.

Dave noted many things on June 15, including Sandoval’s deterioration against left-handed pitching, but it’s interesting to note Sandoval is also a player quite effected by defensive shifts.

Wrote Dave:

In San Francisco, before every team started shifting on nearly every play, Sandoval was reasonably effective when hitting grounders, hitting .261 with a .282 SLG on GBs. Since arriving in Boston and having to adjust to life without the ability to pull the ball between the first and second baseman for a single, he’s hitting .188 with a .197 SLG. Without enough power to offset the GB-heavy batted ball profile, Sandoval is probably going to struggle to run a BABIP over .300 again.

If you’re looking for a silver lining here, if you’re looking for a reason to believe the Panda is not finished, Sandoval’s 96.2 mph average exit velocity on fly balls and line drives ranks 30th in the sport this season. But Sandoval posted the most extreme GB/FB ratios of his career in Boston — a 1.51 ratio in 2015 and a 1.68 mark this season — since his rookie year in San Francisco.

While Sandoval isn’t a slugger, he perhaps would have benefited from getting more balls off the ground.

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Rob Manfred seems intent on expanding Major League Baseball’s footprint north and south of the contiguous United States, and he again stated that desire during the All-Star break as reported by CBSSports.com’s Dayn Perry.

When asked about expansion he reiterated to reporters his support of Montreal and Mexico City as candidates and added a domestic option in Charlotte. Said Manfred:

As much as I hope that both Oakland and Tampa will get stadiums, I think it would be difficult to convince the owners to go forward with an expansion until those situations are resolved.

Once they’re done, I think we have some great candidates. I know the mayor of Montreal has been very vocal about bringing baseball back to Montreal. It was not great when the Expos left. The fact of the matter was baseball was successful in Montreal for a very long time. Charlotte is a possibility. And I would like to think that Mexico City or some place in Mexico would be another possibility.

Baseball is currently in the midst of its longest expansion drought in the modern era. The sport has not grown since admitting the Diamondbacks and Rays in 1998. Eventually, in order to grow business, new markets are required. And there are significant untapped markets remaining in North America. Baseball would figure to jump from 30 to 32 teams, which would also help on a number of logistical fronts.

So if this is a game of musical chairs — three cities for two spots (though Las Vegas, Portland, and San Antonio might also be among the domestic candidates) — let’s examine the cases of the three cities Manfred cited.

Montreal
Metro population: 4,098,927
City population rank in North America: 8th
Elevation: 122 feet
GDP per capita: $38,867 (2013)
Nearest MLB cities: Boston, 220 nautical miles; Toronto, 273 nautical miles

Montreal seems to be the most serious about bringing the sport back to the city, and unlike any other candidate, it has hosted a major-league team before, bettering 2.1 million in attendance four times in its history. Montreal would give the sport a new geographic footprint, a natural rival for Toronto, and a new language (French broadcasts!). The recent exhibition games played in Montreal have been well supported.

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This is Matt Swartz’ third piece as part of his July residency at FanGraphs. A former contributor to FanGraphs and the Hardball Times — and current contributor to MLB Trade Rumors — Swartz also works as consultant to a Major League team. You can find him on Twitter here. Read the work of all our residents here.

In this series of articles, I analyze the average cost per WAR on the free-agent market, as well as looking back at previously discovered market inefficiencies to see how they have changed over time. However, in doing this analysis, it is important to ensure that any assumptions I make have theoretical and empirical backing, including perhaps the largest such assumption — namely, the linearity of the Cost per WAR on the free-agent market. Does a four-win player earn twice as much as a two-win one? Some analysts have argued that, due to scarcity, a 4-WAR player could earn more than twice as much, although I have shown in the past why I believe this is not likely. Today, I will confirm linearity is still a fair assumption to make.

First, it’s useful to discuss the economic implications in theory. The question of linearity comes down to how easy it is to replace a four-win player on the free-agent market, and if teams would be better off going after two 2-WAR players. If so, teams would drive up the price of 2-WAR players and drive down the price of 4-WAR players as they got smarter over time, until both methods of acquiring 4 WAR cost the same. However, perhaps teams cannot upgrade at any enough positions to enable this kind of arbitrage. As revealed by analysis I’ve performed in the past, there are, in practice, many different options a teams has. Nearly every team has a lineup spot, a rotation spot, and a couple of bullpen spots open in any given offseason. Many have more, and teams also have the option of conducting trades, as well, to make room for upgrades if so desired.

None of this says that some teams would never choose to take the approach of going after more 2-WAR players in lieu of going after big names. Individual teams are bound to have different assessments of replacement level both for their own team and the market in general. A team that felt that they had a high replacement level internally would be more inclined to go after big-name players and fill in the remaining spots with their internal high-replacement-level players. Alternatively, a team that felt replacement level was much lower than the market suggests would spread their spending across multiple players to avoid having to fill a vacancy with such a poor player.

As mentioned, my previous findings suggested that Dollars per WAR was linear. To see if this is still true, I split the market into three periods — 2006-09, 2010-13, and 2014-16 — and looked at the cost per WAR using my framework discussed in the previous article in different ranges of salaries (net of the league minimum). This does lead to some sample-size issues, but here is the relevant table:

And here’s that data rendered into visual form:

As you can see, the dollar amounts per win retain a general proximity to the overall averages for each time period. Early numbers did show some non-linearity in the very low-$ part of the market (under $2 million net AAV) but that was probably related to measurement error. Such deals are often one-year deals with sizable incentives that are poorly reported. They also overwhelmingly go to players just above 0 WAR, and therefore are highly vulnerable to measurement error of WAR itself if replacement level isn’t measured correctly. A slightly higher approximation of replacement level could lead to a much higher $/WAR estimate in this range.

I probably was less likely to miss out on incentives in more recent deals when collecting data, and there is actually a large over-correction where $/WAR is very high in the lowest salary bucket for 2014-16. Overall, I think it is best to focus on deals more than $2 million above the league minimum. You will see that the above issue led me to focus only on deals in excess of the amount for much of the subsequent analyses.

But once we get past that first row, we can see strong evidence of linearity in all ranges. The most recent years (2014-16) do show a little bit higher cost per WAR in the high-salary ranges, but since they also do in the low-salary ranges, I suspect this is just noise, and I am comfortable using a linear framework to Dollars per WAR in subsequent articles. This jump in $/WAR at high-$ levels (in the last column) is probably also a function of the small sample sizes as well. There are just 80 and 74 player-seasons respectively in the top two salary groupings for 2014-16.

Any non-linearity in cost per WAR would severely complicate the analysis of the free-agent market. I would certainly welcome this complexity if it were warranted, but I think the evidence and theory both clearly point to linearity making far more sense.

In my next article, I will explain the calculation of draft-pick cost in the Dollars per WAR framework, and the importance of discount rate while doing so. Once that piece is finished, the framework will be defined clearly enough that we can begin looking at the evolution of market inefficiencies.

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