You may have noticed, especially if you’re a Baltimore Orioles fan, that run-scoring has been trending up as the season has progressed. This isn’t new, or particularly surprising, as the coming of summer turns up the heat, enabling fly balls to carry farther.
PITTSBURGH — Travis Shaw isn’t caught up in trends.
In a season when so many hitters are investigating their launch angles and trying to lift balls up into the mysterious jet stream that has settled over major-league playing surfaces, Shaw is engaged in the exact opposite endeavor. He is trying to put the ball on the ground, and he’s in the midst of a breakout season.
The Red Sox would love to have a mulligan on the December multi-player deal that sent Shaw and two prospects to Milwaukee for Tyler Thornburg, who is out for the season after surgery to treat thoracic outlet syndrome. Entering play Tuesday, Shaw was slashing .293/.361/.564 with 20 homers, acceptable defense at third base, and a 2.7 WAR. He was tied as the 22nd most valuable position player in the game to start the day.
Of course, this is a different hitter than the one whom the Red Sox traded away.
“Philosophy, honestly,” said Shaw of the reason behind his breakout with the Brewers. “Everyone talks about launch angle, launch angle, launch angle. This year, I’ve tried to hit the ball on the ground more. Everyone is trying to hit it in the air. For me, when I try to hit the ball on the ground, I hit more home runs. I am more consistent with my swing.”
This seems counterintuitive, bizarre. But it’s working. For the first time in his brief major-league career, Shaw is hitting more ground balls (44.5%) than fly balls (36.0%). Throughout most of his minor-league career, he was a fly-ball hitter. And yet the quality of his contact has improved as he has tried to hit balls into the infield turf.
“The air-out/ground-out thing is completely opposite of what it’s been for my career,” Shaw noted.
This is the worst offensive season for pitchers on record. It’s close, and the season isn’t over, and Madison Bumgarner has spent a lot of time on the disabled list, but, league-wide, pitchers so far have combined for a wRC+ of -21. It’s never before been that low over a full season. It makes enough sense; pitchers are presently better than ever at pitching, and they’re less incentivized than ever to know how to hit. This is the age of specialization. Players who specialize in pitching can’t be expected to handle the bat.
Jon Lester has been a bad hitter, even relative to other pitchers. Over his career he’s batted more than 200 times, and his wRC+ is -40. You might remember that he opened his career 0-for-66, which no player had ever done. Lester is bad at hitting, among pitchers. Pitchers are bad at hitting, and worse than ever. Given an ordinary game, you’d expect that Jon Lester, the hitter, would go quietly o-fer. The Cubs wouldn’t even care that much.
Monday night, Lester stole a base. It was the first pitcher steal of the year. Lester also drew a walk. Lester also hit a double. In one game, Lester had a steal, a walk, and an extra-base hit. Here’s the entire table of pitcher-games meeting the same criteria since 1950:
| Pitcher | Game Date | Team | Opponent |
|---|---|---|---|
| Jon Lester | 7/17/2017 | CHC | ATL |
| Edwin Jackson | 8/3/2016 | SDP | MIL |
| Darren Dreifort | 5/1/1999 | LAD | PHI |
| Steve Renko | 5/22/1973 | MON | CHC |
| Jim Kaat | 7/30/1971 | MIN | NYY |
| Don Gullett | 4/16/1970 | CIN | LAD |
| Tom Seaver | 5/17/1967 | NYM | ATL |
| Robin Roberts | 5/20/1951 | PHI | PIT |
| Fritz Dorish | 6/2/1950 | SLB | WSH |
Nine games. Technically, it has been less than a year since the last one, but then you get a spread of 17 years. Then you get a spread of 26 years. Consider this a decently-rated fun fact. Jon Lester, the hitter, kind of filled up the box score.
Pretty much every contender in baseball is looking for a reliever or two right now. The changing strategies relating to playoff baseball mean you can never have too many quality bullpen arms, and as the Cubs showed last year, you can’t necessarily count on guys who were good in the regular season being able to still go in the postseason. Even teams with strong current bullpens are kicking the tires on available arms because you can’t be certain that what you have now will still be ready to pitch at an elite level in a few months.
Which is why the price for relievers is always pretty high this time of year. And while there aren’t many Aroldis Chapmans or Andrew Millers available right now — Zach Britton would qualify if he were definitely healthy, but the Orioles sticking with Brad Brach as their closer right now is a pretty big red flag — we’re going to see a lot of bullpen arms traded over the next two weeks. The Nationals already paid a real price to add Ryan Madson and Sean Doolittle to their beleaguered pen, and they probably aren’t done adding relievers.
With all this demand and a somewhat limited supply, it’s not easy to find a decent arm to help for the stretch run that doesn’t cost something a team really doesn’t want to give up. But I think there might be one reliever who could probably be had who might not cost a fortune and could really help a team this year and maybe in the future as well. If you’re bargain hunting for a reliever right now, I’ve got one name for you: Danny Barnes.
When Marlins reliever Brad Ziegler made the switch to throwing out of a submarine motion, his new mechanics made him sore. In the hips, as he remembers it. Ask fellow submariner Darren O’Day if his delivery was related to his hip labrum surgery, and his answer is succinct: “Absolutely.” Now fellow side-slotter Andrew Triggs is headed for that same surgery and it’s fair to ask: is the sidearm or submarine delivery hard on the hips?
It’s never easy to answer these sorts of questions because of the problem of sample. There might be two true submariners in baseball today (O’Day and Ziegler), and then a few who others who live low — a group that includes Steve Cishek, Pat Neshek, Joe Smith, and the like. Head any higher on the release-point list, and you’re already at Chris Sale, nobody’s idea of a sidearmer.
If you just take the list of pitchers who have recorded hip problems in the last 10 years, you get 33 different names. Hardly an epidemic. Take those 33 pitchers, and look at their average arm slot, and you might think you’ve found something.
| Player | Height (in.) | Vert. Release (in) | Difference |
|---|---|---|---|
| League Average | 75 | 71.2 | 3.8 |
| Average Hip Problem | 76 | 68.7 | 7.3 |
Pitchers with hip problems release their pitches, on average, three-and-a-half inches lower than the general population.
This is Matt Swartz’ fourth 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.
The most distinct feature of my approach to calculating the cost per WAR on the free-agent market is my inclusion of the draft-pick-based costs to signing free agents, in addition the more obvious monetary costs. This requires a greater collection of assumptions than a simple focus on the dollars spent on free agency, but provides a more robust estimate of what teams give up when they dip into the free-agent market. It also requires a logical economic framework, including opportunity costs, so it also requires estimating the foregone costs of draft picks that a club could have received had they not re-signed their own players.
The gap between my actual estimates of the cost per WAR and the same calculation absent draft-pick compensation is not trivial. While it normally is only around 7%, it reached as high as 20% in 2015. Of course, with the new CBA lowering draft-pick compensation, this difference is likely to drop, making this part of the analysis somewhat less important. However, it remains essential to consider changes in draft-pick compensation to understand changes in cost per WAR over time. What may appear, in some years, like a collective decision by clubs to spend more aggressively in the free-agent market is frequently just a product of lower opportunity cost of foregone draft picks, leading teams to pump more dollars into free-agent contracts.
The biggest challenge when utilizing this framework is determining the appropriate discount rate to use. This isn’t easy to do and can easily vary from team to team and over time, as well. This article won’t pin down a perfect number; it’s almost certain that a better estimate of the discount rate requires a more detailed analysis of trades and other decisions that teams make when considering how to value player performance at different points in the future. It’s also challenging to use this approach to determine if the discount rate that teams use has changed, because it appears that the method of estimating said rate is noisy enough that it varies over time within a very large range. However, it’s worth understanding the approach.
In this article, I attempt to present that approach. Before I begin, one note: some of what follows is rather technical. I feel much of it is necessary, though, to establish the entirety of my methodology before moving on, in later posts, to actual illustrative cases.
The simpler part of using this analysis is looking at draft-pick bonus money saved. While this pales in comparison to lost WAR values from missing out on draft picks, a full picture does require netting out how much a team saves by not paying bonuses on those draft picks. I’ve performed a slightly more sophisticated nonlinear approach to estimate bonuses for this series than in my previous work, basically assuming that bonuses paid to draftees have the same exponential structure (relative to pick number) as the WAR they produce varies by pick number. I’ve also found better estimates of the specific slot values for draftees by pick, leading to a better estimate.
Of course, the larger issue is analyzing the picks themselves. While the average pick surrendered has been around roughly the 30th overall, this has varied significantly and has been higher (at times) in the past. It also will certainly be lower in the future due to the new CBA rules. To estimate the value of picks, I continue to use the Draft Pick WAR Calculator developed by Sky Andrecheck way back in 2009. While the precise outputs have possibly changed over time, they probably haven’t changed much, and Andrecheck’s model is certainly the best publicly available one.
In addition to this estimate of the WAR produced by players according to their draft pick, I’ve also found (in my own research) that prospects tend to debut roughly three years after being drafted. Therefore, a player’s WAR tends to accrue to the team who drafted him from three to nine years after said player is drafted, after which the player is a free agent. That’s roughly equivalent in value to all the WAR accruing exactly six years after the player is drafted, so that’s what I use in my estimate. I also had to net out the actual salaries through arbitration that successful draft picks will eventually receive, knocking down the net value of the WAR created by about 20%.
I decided to continue using a 10% discount rate (meaning that teams currently value the ability to obtain future WAR 10% less each year into the future). This is still my best guess about how teams are valuing draft picks. This means the team values the WAR 56% less than they would if it all came right away. And since they have to pay roughly 20% of market value due to arbitration in the latter years, they value the WAR 20% less than that.
In the three tables below, I’ve split the free-agent market data I have available into three time periods: 2006-09, 2010-13, and 2014-16. I’ve looked at all players who earned salaries at least $2 million in excess of the league minimum and compared the cost per WAR for those free agents with and without draft-pick compensation attached.
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
Arizona at Cincinnati | 19:10 ET
Ray (106.0 IP, 86 xFIP-) vs. Romano (8.0 IP, 125 xFIP-)
The author’s haphazardly constructed algorithm indicates that no single game on today’s schedule is demonstrably more promising than the others. As for this contest between the D-back and Reds, it has received the honored designation of Most Highly Rated largely because of the dumb author’s own interest in young, right-hander Sal Romano. Not unlike other Reds starter Luis Castillo, Romano entered the season with something less than universal praise as a prospect. Also like Castillo, however, he features a plus fastball. Consider: over two starts, Romano has recorded an average fastball velocity of 96.3 mph. That mark would place him fifth among the league’s 71 qualifiers.
Readers’ Preferred Broadcast: Arizona Radio.
Not just anyone can close a game. The ninth inning is different than the first eight innings. Along with quality “stuff,” a certain mentality is needed to walk out to the mound and get those last three outs with your team leading by three runs or less.
Or is it?
Managers are typically averse to using someone other than their designated closer in a save situation — they do so only when necessary — but should that really be the case? Could most teams not realistically expect their “second-best reliever” to get those final outs if their “best reliever” was used in a high-leverage situation earlier in the game, and it was prudent to not have him return for the ninth?
I recently asked that question (albeit not always in those exact words) to a cross section of relievers, pitching coaches, and managers. Here is what they had to say.
———
Cody Allen, Cleveland Indians reliever: “I understand that teams want to keep guys in roles — for the most part, even us — although I feel we’re kind of ahead of the curve in terms of usage. There are times we put guys in different situations, because it might be a bigger point in the game.
“If you have guys who have been here for awhile, or if you bring somebody over who’s proven, like we did last year with Andrew [Miller]… that’s a luxury we have that a lot of teams don’t have. [Bryan] Shaw has been here long enough that Tito knows he can handle just about any spot — any part of the lineup, any inning, any circumstance.
Ben Lindbergh and Jeff Sullivan banter about Mike Trout’s return, the Nats-A’s trade, a Matt Holliday play, and a Jon Heyman tweet, then bring on Mike McIntyre of the Winnipeg Free Press to talk about a borderline unbelievable independent league game and an even more beautifully fake-sounding indy league franchise.
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The All-Star Game and its various related events are behind us, and the game has collectively taken a breath for a couple of days (except for the Cubs and White Sox, but I digress). The numbers for the first half are in the books, giving us an opportunity to reflect on what has already happened and what it might portend for the second half of the season.
In this space I will often analyze players by examining plate appearance frequency and contact quality (for hitters) and contact management (for pitchers) information for pitchers, using granular data to see how players “should be” performing to get a better handle on their true talent and performance levels. Today, let’s use some of this data in a slightly different manner, identifying players with common statistical markers that can tell us something very good or very bad about those player “families.”
