Heat. Smoke. Velocity. Stuff. Gas. Cheese.

I’m sure there are other words to describe our beloved “fireballers” (see, there’s another one). Pitchers who throw at high speeds are treated like fine china — see Stephen Strasburg in the 2012 postseason. I’m guilty of falling victim to the allure of a 98-mph fastball, regardless of its location. We love it, and, frankly, we’d like to see more of it. Major League Baseball has created a setting in which if a pitcher doesn’t break 90 mph with his fastball, he’s considered a “finesse” pitcher, or even a “soft-tosser” if left-handed. We love strikeouts, especially when a power pitcher blows a fastball by a hitter. But why?

Matt Harvey was stellar in 2015. He’s not so good anymore. Why do teams keep giving him second chances? Mostly because he throws hard.

However, it’s not entirely our fault. After reading Thinking, Fast and Slow by Nobel Prize-winning psychologist Daniel Kahneman, I began to understand why this happens. It shows how you can overcome cognitive bias, but in order to do so, you have to understand which one of your “thought systems” is making that decision for you. He explains that each human being has essentially two modes of thought.

System 1 – fast, instinctive, and emotional (gut feeling)

System 2 – slower, more logical (critical thinking) Read the rest of this entry »

When Statcast was launched, we were graced with incredible new stats such as Exit Velocity and Launch Angle, which revolutionized how we evaluate hitting. This new information confirmed obvious things like that Giancarlo Stanton hits missiles, but it also gave us a new breed of hitter. Daniel Murphy, Justin Turner, J.D. Martinez, and others looked at the data and made adjustments that started maximizing their power outputs. The standard evaluation method has become to look at EVs mixed with LAs to determine who is one tweak away from stardom. Hitting is a complex beast, with pitchers throwing 95-plus with nasty hooks to go with shifting defenses. Ultimately, a hitter is looking to produce solid contact regardless of where the ball goes. The goal of this analysis is to identify hitters who have an inefficient spray chart and see how they could optimize their profile by hitting more balls in a different direction to maximize production. Luckily with Statcast, we can now try to find these answers.

To do this analysis, I used Baseball Savant to gather 2018 Exit Velocity and xwOBA to Pull Side, Straight Away, and Oppo Side for all hitters with at least 50 plate appearances. I then used FanGraphs to pull the 2018 data for Pull%, Mid%, and Oppo% to discern how often a hitter attacks that field. I used 50 PAs as a filter since this is about where exit velocities become stable and helps weed out pitchers and other noise. This does create gaps in the data because some players didn’t register 50 PAs of a batted-ball direction. This dataset gives us the ability to look at how hard a hitter hits the ball to a field, what was their expected damage (xwOBA) to that field, and how often they went that way.

The first category I looked at was players who could use the opposite field more often. To do this, I looked at players who had an above average Oppo Side xwOBA and a below-average Oppo%. I used exit velocities to each field as a proxy to justify the directional swing change. Read the rest of this entry »

Trading away your team’s best players is never going to make you popular. You’ve probably read plenty about how the return for Marcell Ozuna was pretty good for the Marlins, while the return for Stanton was pretty thin. But savvy baseball fans understand that when you trade players, you’re not only trading their production, but also their contracts – so offloading an insane 13-year $325M contract might not return as much as a team-friendly contract for a lesser player. Add in the fact that Stanton had a no-trade clause (thus, a ton of leverage over to whom he was traded) the fact that the Marlins got anything in return for Stanton is actually impressive. The Yankees took on practically all of Stanton’s remaining contract; so in context, this was a fine deal for the Marlins. Dee Gordon, though contact-and-speed types typically don’t sustain a lot of value into their 30’s (as Gordon enters this year at 30), has put together 3.8 WAR/162 across his last 4 seasons, so maybe they could’ve gotten a little more out of that deal, but again – they were able to get rid of Gordon’s entire contract, which is guaranteed until his age-33 season of 2020.

The trade that stuck out most to me was the one for Christian Yelich. Yelich is an established star in the league who is still very young and has lots of upside, won’t be a free agent until 2023 (accounting for a team-friendly option in 2022), and seems like the type of player you might want to keep, even in a rebuild. They did receive top prospect Lewis Brinson and others in return, but of all the deals they made this one was, to me, the most indicative of “holy crap Jeter has no idea what he’s doing.”

And then, I realized, maybe he’s a genius.

Well, it doesn’t take a genius to recognize that Yelich is a future star, if he isn’t rightfully considered one already. It takes some genius (and perhaps a few gift baskets for your fans?) to say tear it all down. The Marlins could’ve kept any or all of Yelich, Ozuna, and even Stanton, but they’d still have been bad for the foreseeable future. The past four seasons they won 77, 71, 79, and 77 games. It’d have been easy to continue to toil in mediocrity, maybe even make a wildcard or two. But mediocrity is pointless in a business that overtly rewards losing.

You’re saying you want us to lose? No, we’ve BEEN losing. What I want is for us to finish dead last.
-Derek Jeter (probably).

It’s not a secret that tanking is now an actual strategy employed by “rebuilding” teams. I was surprised to learn in my research that tanking is probably not a new phenomenon (the percentage of teams who win 70 or fewer games is fairly consistent over the past several decades) but the game has changed so significantly in the era of free agency, “service time,” and revenue sharing, that the financial benefits of tanking should probably not be legal (but that’s for the CBA to determine). 2018 could be the worst year ever in terms of the number of teams not trying to compete.

Is that wrong? “Tank and bank” isn’t a purely theoretical exercise anymore. As you probably know, the past two World Series winners were responsible for some of the most blatant, disgusting, glorious middle-fingers-to-the-league you could ever imagine – and their paths coincide almost directly.

2008: the Cubs were an aging but solid team that led the NL in wins, with a dangerous lineup and a restored version of Kerry Wood, now a closer. They were bounced early in the playoffs however, in the same year Joe Maddon came up just short of an unlikely World Series title with the Rays. That same year, the Astros were competitive – winning 86 games – but came up short of a playoff birth.

Both teams achieved Marlins-esque mediocrity in 2009 and 2010, and that’s when the tanking rebuilding began. The Astros were the most aggressive and flagrant in their process, and many people forget just how bad they were. They won just 56 games in 2011, followed by campaigns of 55 and 51 wins (that’s three straight seasons of 106+ losses). Their payroll went from $77M in 2011 to $67M in 2012 to $25M in 2013 and then – somehow – cut it in half during the season by shedding even more salary. Notably, and not coincidentally, the Astros got a new owner in 2011. That historically bad 2013 for the Astros was actually historically great: they had the most profitable season in MLB history.

While the Cubs also lost a bunch of games during that same time period, they had a pretty big advantage over the Astros: they hired Theo Epstein (all due respect to Jeff Luhnow, whose roundabout career path is worthy of its own article). I’m not going to try and give Jeter or his staff a current/future grade as it pertains to winning lopsided trades but let’s just assume the Marlins are more like the 2011 Astros than the 2011 Cubs. Their “competitive advantage” over teams who may have better guys in analytics/baseball ops is that they can lose lots of games.

Currently, the Marlins are projected to win the fewest games in baseball which would of course net them the #1 overall pick. Picking first is certainly no guarantee of success (ahem, Kris Bryant went #2 to the Cubs in 2013 while the Astros picked up Mark Appel at #1) but it’s objectively better to pick in the top 2 or 3 than, say, outside of the top 5. There is also the correlated benefit of turning a bigger profit by fielding a lower payroll. To put it simply: if you’re going to miss the playoffs anyway, make as much money as possible while getting the best draft pick you can. It’s easy to say “I wouldn’t have traded Yelich/Ozuna/Stanton” in an attempt to appease your fan base (who aren’t coming to games anyway) while not having personally invested hundreds of millions of dollars into a team; but when your expensive team has little chance of even making the playoffs (never mind winning a World Series) the business side of things becomes even more important.

Based on the aggressive trades the Marlins have made to shed payroll, expect them to mirror the ’11-’13 Astros financially: they have about $80M committed this year, about $50M in 2019, but only $23M in 2020; 22M of that is to Wei-Yin Chen who I’m sure the Marlins hope can stay healthy long enough to generate a little interest from a contender. Righty-specialist and all-time home run preventer Brad Ziegler (making $9M) should have enough appeal to anyone who gets tired of giving up homers to the right-handed heavy Yankees or Angels lineups, and Junichi Tazawa (making $7M) might have a few buyers as well. Justin Bour (age 30, $3.4M, arb-eligible) should find a home with a competitor  – possibly best fit with the aforementioned Angels or even Yankees depending on how Greg Bird recovers, given their respective needs for some left-handed power options. Perhaps they can package the no longer desirable Martin Prado (2yr, $28.5M) with the very desirable J.T. Realmuto (age 27, $2.9M, arb-eligible) to shed some more salary.

By year 5 of their rebuild, both the Cubs and Astros blossomed into legitimate competitors, before winning their World Series in years 6 and 7 respectively (and being in great position to compete for years to come). Marlins fans probably don’t want to year “2022” as the best case scenario for their team to begin competing…but competing for a World Series doesn’t come easy. And as I’m sure Astros and Cubs fans could attest, it’s worth the wait.

Amid the snaillike pace of the free agent and trade market this offseason, the argument that MLB owners are in collusion against the players does not hold water. It is, instead, the player’s failure to recognize the swing of the pendulum, and to fight back with some creativity in their thinking.

Owners throughout all of MLB, whether they operate in large or small markets have (finally) figured out they’ve been overpaying players at the top of the wage scale for more than a decade. Correction, the nerds with the analytical skills have figured it out for them, and they’re serving it up to owners on a silver platter.

Of all the stats out there today, the most powerful one is Wins Above Replacement, commonly known as WAR. WAR is a number arrived at utilizing a complicated algorithm which boils a player down to how many wins he represents his team if the team had to replace him.

Writing for Bleacher Report, Joel Reuter put together an impressive coalition of stats to demonstrate what he calls a player’s “Net Value,” which is derived from the player’s WAR value (1.0 = $8 million in salary (see FanGraphs), minus the player’s actual salary. Here’s an example of how a few of the Yankees and Mets rated in 2017.

New York Yankees Best

New York Mets Best

New York Yankees Worst

New York Mets Worst

Now, let’s take Reuter’s accounting one step further. If we total up the Net Values on the plus side benefiting the owners, the Yankees “saved” $43.7 million last season and the Mets saved $48.4 million. On the negative side where the owners took a hit, the Yankees “lost” a total of $28.8 million on those three players and the Mets $25.7 million.

Which, in sum, seems to show that owners are not taking as big a bath as they would like us to believe. And further, that it’s possible players are being underpaid instead of overpaid. To draw any firm conclusions, though, a comprehensive study encompassing the entire payroll of both the Yankees and  Mets would need to be executed, which is something the Major League Player’s Association might want to tackle in making their case to MLB and the public.

My thinking is drawn more to the number of years in contracts rather than the money per year that concerns owners and general managers throughout MLB. Giancarlo Stanton, as an example, will likely be worth every penny he is paid – until he reaches a point when he isn’t. At that point, Stanton will become a reincarnation of Teixeria and Alex Rodriguez, each of whom burdened the team financially as their careers faded.

And if we reach far back into MLB’s past, players were routinely issued one-year contracts based exclusively on last year’s performance. MLB will never go there again, but the point the owners and GM’s seem to be making is the need for the pendulum to swing back the other way, in which two and three-year deals represent the top of the pay stratosphere.

[su_pullquote align=”right”]The game as we’ve known it is over. And the players need to come up with some better ways to fight what is happening – other than saying, “I’m gonna take my ball and go home.”[/su_pullquote]

The players and their union (MLBPA) are balking mainly because they (now) realize they shot themselves in the foot when the signed the collective bargaining agreement (CBA) that is with us until 2021. There was talk of boycotting Spring Training, but that will never happen.

But, is it collusion on the part of the owners? Of course, it is. If you and I and ten other people decide to go to the movies tonight, is that collusion? It could be if we plan to rob the concession stand. But otherwise, it’s just twelve people who had the same idea at the same time, and they are acting on it.

The Players Need To Get Creative

The players can do themselves a favor by stepping up the analytics game themselves. They already have one bullet in their arsenal which is MLB Merchandise. For example, how many Matt Harvey t-shirts have been sold over the years? How many pairs of Yoenis Cespedes batting gloves, Noah Syndergaard headbands, and so on? We’re talking big money here, folks. Last year, according to Forbes, MLB Shop took in $9.5 billion (that’s billion with a B) in revenue, a $500 million increase from 2015. For being #1 in the T-shirt sales department, how much money do you think Aaron Judge collected?

Similarly, the players argue that fans come to the ballpark to watch them perform athletic feats that often challenge gravity. True enough, but why not use that as a means to demonstrate the value some of these players have for, as George Steinbrenner liked to say, putting asses in the seats?

Why not, for instance, issue a card to each fan entering the ballpark with a list of all players in uniform that day with one instruction. Check the names of five players on your ballot who you came to see play today. Total ’em up at the end of a season, and the players have their version of WAR. Only this stat can be called TAP, for Tickets Sold Above Replacement.

Individually and as a unit, MLB players are not political animals. They seek only to play the game they have grown up with and love to play. No one, these days, goes to the poorhouse playing major league baseball. No one needs a second job driving a milk truck during the offseason like Hank Bauer, and Yogi Berra did for years during their playing days.

At the time time, the MLBPA and the players themselves need to understand that owners and general managers are (indeed) drawing a line in the sand. In days to come, Albert Pujols and even, Giancarlo Stanton will be seen as dinosaurs, the topic of conversation in bars across America for the contracts they won.

The game as we’ve known it is over. And the players need to come up with some better ways to fight what is happening – other than saying, “I’m gonna take my ball and go home.”

Footnote: A good follow-up read if you have the time appeared in the New York Daily News, and features MLB player, Brandon Moss, who has some controversial views on the current stalemate (“We Screwed Up”)

It’s been about several weeks since the Pirates parted ways with both Gerrit Cole and Andrew McCutchen, the former to Houston, and the latter to San Francisco. Most fans and analysts expect Josh Harrison to be next, and by the looks of it, that’s what he’d prefer.

Some would consider the Pirates to be rebuilding, while others suggest it may be somewhat of a retooling, hoping that some names that were expected to work out, but suffered setbacks either last year or culminating throughout the last several years (like Marte and Polanco) will bounce back or reach expectations.

That, coupled with players breaking through and reaching their potential (like Bell and Taillon), along with other young players (as though the Pirates have any other type of player now) like Trevor Williams, who showed a lot of promise last year, or Steven Brault, who pitched very well at AAA Indianapolis, perhaps the Pirates can field a winning team. It doesn’t hurt that they inked one of the top relievers in the game, Felipe Rivero, who emerged with a breakout season last year, to a four-year deal.

But most Pirates fans aren’t buying it. There was even a petition started on Change.org for “MLB to force Bob Nutting to sell the Pirates”, and to this date it has reached 59,456 signatures. Of course, there is basically no chance that this petition will actually result in anything.

Before both trades, the Pirates projected win total by FanGraphs was a whopping 81. After the Cole trade, it went to- er- stayed at, 81. It did move, though, once McCutchen was dealt, dropping from 81 to 78, which would still be three wins better than last year’s club, which might cause some to say that technically the team is improving, even if it’s by the most basic metric; of course, most would say that’s nonsense.

Last year, the Pirates were plagued by a multitude of problems, from Marte’s PED suspension, a plethora of injuries to, well, everyone, and even to Taillon missing time due to testicular cancer (which he brilliantly rebounded from, appearing as a starting pitcher just five weeks after surgery). Not to mention Jung-ho Kang’s off-field issues and inability to return to the team. The Bucs suffered a six-game setback from last year’s projections where they were expected to go 81-81. They finished six games below that total, winning 75 contests.

The Pirates were basically destined to fail last year. Now many believe that the Pirates are in store for the same fate this year after departing with two of the franchise’s marquee players.

A lot of the Pirates roster will look strikingly similar to last season, except for those received in the trades, which includes: 3B Colin Moran, P Joe Musgrove, P Kyle Crick, P Michael Feliz, among several other pitchers not involved in either of those trades, Nik Turley, Jack Leathersich, and Jordan Milbrath. It is unlikely that those players will make that big of an impact.

It’s possible, without any major injuries, the contributions the Pirates expected to receive last year will be more likely to reach fruition this year. If Gregory Polanco has the kind of breakout season people felt like he might have when the Pirates first acquired him, it’s possible for him to be a 5.0 WAR player. A litany of injuries prevented him from coming anything close to that last year, registering a 0.5 WAR, but with glimpses of power in his minimal contributions.

The same is true for Starling Marte. In 135 games for the Pirates in 2013, Marte posted a 4.8 WAR and 122 wRC+. We are all aware of Marte’s 80 game suspension following him testing positive for performance-enhancing drugs prior to the 2017 season. When he returned, he failed to be the player the Pirates hoped he’d be, and of course, he’ll have a lot to prove after his suspension in his first full season, but it isn’t completely insane to think he might experience a resurgence.

Josh Bell had a breakout season for the Bucs in his rookie campaign, perhaps positioning himself to be the next face of the franchise. Bell registered a 1.4 WAR last year and 113 wRC+, a .338 wOBA, and an OPS of .800. He hit for significantly more power than was expected of him, blasting 26 cannonballs, which was 12 higher than his 2016 total in AAA Indianapolis, playing nearly every game (159) in 2017. If Bell continued to grow this offseason, it’s entirely possible he’ll repeat in some statistical categories, like home runs wOBA, and OPS, and improve in others, like BABIP (.278), making him a very legitimate threat in the middle of the order.

Joe Musgrove, whom the Pirates acquired from Houston, showed that he may have the stuff for a solid third in the rotation type pitcher. Musgrove appeared in 38 games for Houston last year, starting 10 of them, posting a FIP of 4.38, an ERA- of 113, and an xFIP of 4.03. Those numbers are about in-line for a 5 starter, most likely, but PNC is one of the most “pitcher friendly” parks in baseball. Also, I’m not one to chalk up occurrences to magic, but Ray Searage has worked some serious voodoo in the past, and that could likely be the case here, especially with Musgrove who is by no means a lost cause pitcher to begin with. Additionally, Musgrove throws pretty hard, last year registering his fastball around 93.5 mph, his cutter a tick over 90, and a slider around 92.

Colin Moran will likely see the most time at 3B this season, as David Freese’s production levels just don’t quite reach what they should to warrant starting everyday, especially with a young player like Moran waiting in the wings. Jeff Sullivan wrote an article highlighting Colin Moran’s swing change, and some of the numbers were glaring. During seasons 2013-2016, Moran sat around 50% ground balls, and with the way baseball’s evolved, that’s not really a good thing. But in 2017, that number was strikingly different. Moran hit a ground ball only 34% of the time. With his decrease in ground balls came an increase in home runs. He had a previous high of 10 in AAA with far more at bats than his 18 in 2017 during his AAA campaign.

Lastly, Michael Feliz, another piece from the Astros, comes to Pittsburgh after having posted interesting numbers in 2017. Firstly, Feliz throws hard, reaching the high 90s with his fastball, averaging nearly 97 mph in 2017. He posted a FIP of 3.78, an xFIP of 3.58, and an xFIP- of 81. Feliz will likely be a strong complement to Felipe Rivero out of the pen.

Help will have to also come from players being called up from AAA for the first time (Meadows, who suffered setbacks last year on the DL, Keller, perhaps Bryan Reynolds, among others), but if some things break the right way, the Pirates may experience more success than originally anticipated. Don’t misunderstand me, I’m not saying the Pirates will be in contention for the NL Central this year, or even a Wild Card spot. I’m saying the potential is there for them to rebound from last year and finish the season above .500 at 82-80, especially if they can capitalize on a flailing Reds team, as well as in games against the largely inept NL East.

But barring a major outbreak by a lot of guys, the Pirates will likely be an average to below average team (somewhere along the lines of 75-87 to 79-83). It wouldn’t surprise me for them to finish better than last year, if not just for the sheer manpower versus last year, and hopefully not having to deal with such setbacks.

But when is it most likely the Pirates will be able to actually contend? The front office will say 2019 at the earliest, and there’s some credence to that.

Mitch Keller is projected to make his debut sometime this season, ranked 16th overall, and is the Pirates best prospect. Austin Meadows, ranked 45th, is expected to make his debut this season, as well. The last of the Pirates top 100 prospects, Shane Baz (67th) isn’t expected to make his debut until 2021, and hopefully, the Pirates are competing before then.

From the Pirates own top 30 list, several potentially important players are expected to debut in 2018, including Nick Kingham and Bryan Reynolds (the latter of whom came over in the McCutchen trade). 2019 will see a string of more players, and if they make an impact right away could yield a winning ball club, like Ke’Bryan Hayes and Cole Tucker. If you combine their potential productivity with the progression of guys that are already there and guys that are debuting this season, the Pirates could be returning to a similar place as their winning years, 2013-2015, in as little as two seasons.

Although it should be noted, the Pirates most successful years weren’t necessarily fueled by prospects. When Gerrit Cole debuted in 2013, one of the Pirates most successful seasons, he was really the only major prospect getting to play at that time, while the majority of the roster was comprised of veteran holdovers from the season before.

What that could potentially mean is that perhaps 2019 isn’t necessarily a possibility in terms of being competitive. Perhaps a more realistic timetable is 2021. By that time, Starling Marte will be in the final year of his contract at age 32, and likely his last year as a Pirate, and assuming he’s able to rebound, will be in the latter part of his most productive years. Gregory Polanco, if he’s able to reach his potential, will be in his Age 29 season and possibly at the peak of his ability. Moreover, by 2021, most of the players we’ve discussed will have had time to fully develop, like Josh Bell and Jameson Taillon, plus any guys coming up over the next two seasons.

All of these guys won’t pan out, but there’s a pretty good chance some of them will, and that’s the best an organization and fan base can hope for (except for the Astros who have seemed to hit the jackpot in every regard). The team will also need to be supplemented by veterans, and not just the cheap ones. For the Pirates to make a run and win between 2019-2023, the front office is going to need to spend more money than they were willing with Gerrit Cole and Andrew McCutchen.

There are a lot of hypotheticals in the Pirates future, but there truly is a lot to be excited about. I know it’s a difficult thing to request of Pirates fans, but this transition will require patience. That, and the front office attempting to provide more from the outside in free agency or big trades, and probably both. There is a lot the front office has done right in the past; unfortunately, though, there is also a lot its done wrong. We’ve seen the front office make some truly good trades, having the insight to know when guys have passed their peak and flipped them at the right time (like the acquisition of Rivero). But there will have to come a time where they send prospect packages for big-time players; if not, the Pirates may not see a real contender until ownership changes.

This post was originally from my website thekzonenews.wordpress.com, and one image is courtesy of fivethiryeight.com

Every offseason, each team’s GM and front office has a choice to make: should we stock up on depth, or go sign the big fish on the free agent market? Recently, as Travis Sawchik of FanGraphs pointed out, teams have been trending towards the depth route, but when it comes to free agent hitters, teams are far better off allocating their money towards just a few stars. Here’s why:

I. Depth-based teams perform no better than Stars and Scrubs teams

Back in 2014, Jonah Keri and Neil Paine from FiveThirtyEight did some research (they, in turn, cite FanGraphs) to show that the way a roster is constructed has little effect on how it performs. Here is the chart they produced based on the data they found:

On their chart’s x-axis, the data shows how balanced a team is, while on the y-axis, the chart displays how well the team performed. While the article makes sure to note that at the highest extremes, depth works, there is not an overall trend to be found. The teams who had the most total contributions from the sum of their players did the best, whether that came concentrated on a few superstars or it came from every individual. And, when one thinks about it, it makes sense that neither strategy would be perfect. Banking on a few players seems to come with risks of health, but at the same time if they can stay healthy, those stronger players may be more consistent. Jonah and Neil also make an interesting point with regards to the trade deadline and further roster building after its base: It’s far easier and cheaper to replace a scrub at second base or left field with an average player than to replace an average player with a star.

So, to be clear, there is little correlation between how a team spreads out their roster and how well they do in a season. Both have advantages, and both have disadvantages, which turn out to be pretty equal, as shown by the data. The battle then becomes about value, which I wrote a little about with regard to the current free agent class. Between two teams that get equal contributions from the sum of their players, which roster construction type is cheaper? With the exception of an especially greedy owner, the team who chooses the more cost-efficient makeup should be able to afford an extra player for the same price, pushing them just over their competitor.

II. Stars and Scrubs is a more cost-efficient method of roster construction than Depth

To find this information, I built a Python program that looks at tabular data from FanGraphs and MLB Trade Rumors. Along the x-axis of my program’s graph (below) is the WAR of various position players in their contract years, and along the y-axis is the average annual value of the contract they proceeded to sign. Using a polynomial regression model, I made a curve of best fit (in red), which should show about how much it would cost annually to sign a player of each WAR value. 

The basic red curve takes on the form of an inverse cube function, steep in the middle stretching out lengthwise on either end. That means it costs more money to tack on an extra share of a win to an average player than to a great or a poor player. That concept is best illustrated by the blue graph (the red line’s derivative), which peaks at a 2.51-win player, just above average (2.0), meaning each extra part of a win you want to add is most expensive for players with a WAR between 2 and 3.

The green money line, however, is the most important, and you don’t need calculus to understand it. Let’s zoom in a little.

On the x-axis is the total WAR that a free agent accumulated last season, and on the y-axis is the amount of money that each of those wins costs (contract AAV divided by the WAR contribution). The math says that as a player’s WAR approaches zero, their price approaches infinity, but we’ll assume that a team can get a replacement level player for the MLB minimum wage, around $500,000. The lesson there is simply that buying a player with a WAR under 1.0 is a bad idea (but does buying a player with a negative WAR earn you money per win?). A 1.0-WAR player starts out as a rip-off per win, but the value quickly rises. A 1.6-WAR player represents the local minimum in cost per win, at only $4.18MM. The price of a win then starts to rise again for the average and above average athletes, hitting a local maximum of $4.35MM per win for a 3.3-WAR player. But then, as foreshadowed by the plateauing of the red curve and decrease in the blue curve, the green curve begins to drop. By the time it hits a 5.5-WAR player, a win only costs $3.66MM, which is as far as the data will take the line without overfitting the smaller sample up top.

The local minimum at 1.6 WAR is important for a team that only has money for maybe one very minor investment (namely, do not invest in a below-great player worth much more than 1.6 WAR, or much below, because teams can always promote or claim 0.0 WAR players for minimum wage), but the ever-decreasing price tag per win of the best players is the most important part. To be a top-hitting team in 2017, the nine players in your lineup needed to total around 27 WAR for the season — on average 3 WAR per player. To build this kind of roster of pure depth, that is every player is equal, each player would command an average annual value of $12.9 million, for a total cost of $116.1MM. However, a team who builds their 27 WAR with five 5.5 WAR hitters and four replacement level hitters will only spend $102.5MM. If they want to spend the same amount of money as the first team, they could add an extra 3.25 WAR bat, making their team superior (that’s the difference between the Cardinals’ and Mets’ offense, or the Diamondbacks’ and Braves’ offense) to their depth-based counterpart.

If you exclude the ability to add replacement level players for minimum, a big advantage for more extreme stars and scrubs teams is keeping payroll down. Here are the total payrolls of various 27-WAR roster constructions, with the deeper ones at the top and the shallower ones at the bottom:

There’s a sudden drop-off in payroll once a team gets below a certain amount of depth, which coincides with both the part of the green graph at the end that becomes a really steep downhill and the part of the small valley in the beginning of the curve. If it didn’t already seem clear, this should answer up any questions. A stars and scrubs roster provides much more value for a team than a depth-based one, allowing them additional payroll space to add better players. The FiveThirtyEight data from Part I showed that roster makeup does not affect team record, and that team talent was decided purely based on how good the sum of the players are. By saving money through a stars and scrubs construction, a team can add more good players, therefore adding to that sum, and becoming the better team.

III. Conclusion

The collected data shows a lot, but it’s far from perfect. For starters, I only focus on WAR, which is a terrific statistic, but is in no way completely tell-all (I’ve written about the topic in the past). Additionally, I only look at FanGraphs’ fWAR, which is only 1/3 of the WAR story. Furthermore, the method assumes that free agents will replicate their previous season during the years of their contract, ignoring aging curves, or at least that teams assume they will. Anyone who follows baseball at all knows this is far from the truth. Teams know free agents are incredibly risky commodities, and the suggestion that a team would consider building a roster entirely out of free agents is kind of ridiculous. This is especially true for superstar free agents, who will require a longer commitment than average ones. The best method of player acquisition for value and talent has been, is, and will probably always be player development. That said, a made-up model of teams acquiring only free agents works well to represent a more realistic model, when a team might have to decide if it wants to allocate a small part of the budget to a few hitters, or only one hitter. Finally, the study only looks at hitters. An analysis of pitchers would need a whole new article.

At first, the suggestion that the best teams should be superstar-driven is a little depressing. It’s fun to watch stars play, but part of the beauty of the game is that everyone is the lineup has the same chance to make a contribution. But one could also look at the findings in a much more positive light. Rebuilding teams don’t need every single prospect around the diamond to work out. Having just a few players break out in superstar fashion (e.g. the 2017 Yankees, who continue to add more superstar power) can make a team instantly competitive. Signing just one or two big free agents (teams are shying away, but J.D. Martinez plus Eric Hosmer could turn any franchise around if they continue to grind after signing) can turn a mediocre roster into a World Series contender. It’s all very good for the parity of the game. The power of just one or two stars can light up a whole team.

The shift has taken the MLB by storm in recent years.  Broadcasters love to criticize the shift, despite its numerous advantages.  One potential problem that the shift may cause is an increase in fielding errors.  This may be a direct result of fielders playing out of their normal position.  Using the shift data provided to FanGraphs courtesy of Baseball Info Solutions, as well as batted ball data courtesy of Baseball Savant, I ran a logistic regression to find the likelihood of a batted ball resulting in a fielding error.

The approach I used to find the probability of a batted ball being a fielding error was to run a logistic regression.  The variables included in the regression were release speed, hitter-pitcher matchup (dummy variable with a value of 1 if the pitcher and hitter were both righties or lefties), runners on base dummy, launch speed (exit velocity), effective speed, launch angle, and dummy variables for both traditional and non-traditional shifts.  The model only included batted balls that were hit in the infield, as the majority of shifts occur in the infield.

Above are the results of the logistic regression used to determine the probability of a batted ball being an error.  The dependent variable is whether or not the error occurred.  Two results that logically make sense are Exit Velocity (Launch Speed) having a positive coefficient and Launch Angle having a negative coefficient.  Both of these variables are significant on the 1% level.  Exit Velocity having a positive coefficient shows that the harder the ball is hit, the harder the ball is to field.  Launch Angle has a negative coefficient, meaning that the lower the angle (meaning a ground ball over a fly ball) the more likely the fielder is to commit an error.  Both of these results are logical, and are consistent with research that has been conducted in the past. The most interesting results from the model are both traditional and non-traditional shifts leading to an increased likelihood of an error occurring.  Both variables were statistically significant on the 5% level, and prove that players struggle more in the field when playing out of their normal position.

While teams are unlikely to change their shifting patterns (more good comes out of the shift than bad), they must take into account which fielders are worse when playing out of position.

Despite the increased probability of an error occurring, I still believe that the positives out weigh the negatives when it comes to shifting.  In future research, it would be interesting to look at this data on a minor league level, as well as seeing if fielders who shifted more in the minors are more prepared to field out of position in the majors.

If you play in a traditional 12-team 5×5 roto auction league with 25-man rosters and a $200 FA budget per season, you might constantly feel like there is solid waiver-wire talent out there, but your roster is too stacked to cut anyone. So, you offer your league-mates a trade of two or three mediocre players for one of their better players, but they are facing a similar roster crunch and immediately see right through your pernicious plan. It can be tempting to cut the lowest-production, lowest-upside player on your roster, which in many cases is the $1 catcher you drafted. But is that catcher really providing value to your roster? Let’s break it down.

Let’s say you draft Realmuto this year for $10 and expect a line of 13 HR, 53 R, 58 RBI, 7 SB, .275 AVG (Steamer projected line, ~500 PA).  The other cost of drafting Realmuto is the opportunity cost of his roster spot. In a typical fantasy week, there are three or four days where your typical starting lineup is not intact. Whether it’s because a team is having an off-day or one of your regular starters is DTD with a bruised toe, holes in your lineup are bound to happen. A smart streamer can look for good matchups and plug those holes. If you have unlimited pickups allowed in your league, then there is no cost to picking up a player if you have an open roster spot. In my league, I can pick up players for $1 on free-agent days (M/W/F).

This begs the question: if you are streaming to fill in holes four times per week over 26 weeks of the regular season, and each game you plug in a streaming player you get 4 PA, then that is going to equal just over 200 PA and cost you around $78 FAAB (assuming three pickups per week * 26 weeks, and one of your streamed pickups fills holes twice in one week for a total of four fill-ins). What does a slash line of 200 PA for a waiver-wire bat look like?

Kevin Pillar screams waiver-wire bat. His Steamer projection reduced to 200 PA looks like: 5 HR, 25 R, 20 RBI, 5 SB, .270 AVG. That’s quite worse than Realmuto’s line in every way excepting AVG. It amounts to a little less than 50% of Realmuto’s line at the cost of $78 FAAB. Now you could argue that maybe amidst all your streaming you end up picking up a Jonathan Villar 2016 breakout type of bat and end up sticking with him and getting immense value, but that’s easier said than done. Maybe you are also going to research pitcher vs. batter matchups on a daily basis and you get an edge there, but that is also easier said than done.

How does the 200 PA of Kevin Pillar compare to a $1 draft day, bottom of the barrel catcher’s line? Even poor Jonathan Lucroy is projected by Steamer to beat this line: 10 HR, 44 R, 46 RBI, 2 SB, .268 AVG. Other such luminaries projected to outshine it include Tucker Barnhart, Christian Vazquez, and Tyler Flowers. Pretty much any catcher who is a starter and can bat .250+ for a season will put up much better counting stats than the Pillar line.

Long story short — even though your catcher’s line may look meek, and they don’t play every day, making your roster look thin, it will still likely be better than waiver-wire lineup hole streaming. Better to save your FAAB cash for other needs. If you play in an unlimited transaction league, you would still need about 500 PAs of Pillar to exceed the Realmuto line. That’s a lot of transactions, and you might not have time to get all the necessary PAs in. Punting C is like heeding the siren calls — it can be very tempting, but also a dangerous and costly exercise. Staying the course with the catcher you drafted is usually the best call in terms of value per FAAB dollar spent.

Earlier this season I set out to build a tool similar in nature to my dSCORE tool, except this one was meant to identify swing-change hitters. Along the course of its construction and early-alpha testing, it morphed into something different, and maybe something more useful. What I ended up with was a tool called cHit (“change Hit”, named for swing changers but really I was just too lazy to bother coming up with a more apt acronym for what the tool actually does). cHit, in its current beta form, aims to identify hitters that tend to profile for “impact production” — simply defined as hit balls hard, and hit them in the air. Other research has identified those as ideal for XBH, so I really didn’t need to reinvent the wheel. Although I’d really like to pull in Statcast data offerings in a more refined form of this tool, simple batted ball data offered here on FanGraphs does the trick nicely.

The inner workings of this tool takes six different data points (BB%, GB%, FB%, Hard%, Soft%, Spd), compares each individual player’s stat against a league midpoint for that stat, then buffs it using a multiplier that serves to normalize each stat based on its importance to ISO. I chose ISO as it’s a pretty clean catch-all for power output.

Now here’s the trick of this tool: it’s not going to identify “good” hitters from “bad” hitters. Quality sticks like Jean Segura, Dee Gordon, Cesar Hernandez, and others show up at the bottom of the results because their game doesn’t base itself on the long ball. They do just fine for themselves hitting softer liners or ground balls and using their legs for production. Frankly, chances are if a player at the bottom of the list has a high Speed component, they’ve got a decent chance of success despite a low cHit. Nuance needs to be accounted for by the user.

Here’s how I use it to identify swing-changers (and/or regression candidates): I pulled in data for previous years, back to 2014. I compared 2017 data to 2016 data (I’ll add in comparisons for previous years in later iterations) and simply checked to see who were cHit risers or fallers. The results were telling — players we have on record as swing changers show up with significant positive gains, and players that endured some significant regression fell.

There’s an unintended, possible third use for this tool: identifying injured hitters. Gregory Polanco, Freddie Freeman, and Matt Holliday all suffered/played through injury this year, and they all fell precipitously in the rankings. I’ll need a larger sample size to see whether injuries and a fall in cHit are related or if that’s just noise.

Data!

Okay, so here’s the breakdown. I pulled all 2017 hitters with 400 at-bats or more so I could capture some significant hitters that didn’t have qualifying numbers of ABs due to injury. Ball-bludgeon extraordinaire Joey Gallo is a pretty solid name to have heading up this list, as he’s pretty much the human definition of what this tool is trying to identify. JD Martinez, Aaron Judge, Cody Bellinger, Miguel Sano, Trevor Story, and Justin Turner all in the top 10 is pretty much all the proof-of-concept I needed.

Interesting notes:

Brandon Belt at 12 — Someone needs to tell the Giants to trade him to literally any other team, stat.

Giancarlo Stanton at 46 — Surprisingly, the MVP fell off from his stats in 2016. His grounders and soft contact rose by 3 or more percentage points, and shaved off the equivalent from hard and fly balls. His output was fueled by adding almost 200 ABs to his season — he could actually get better if he can stay healthy and add those hard flies back in!

Francisco Lindor at 58 — The interesting part of this is even though Lindor is still a decent way down the list, he actually was the biggest gainer from last season to this, adding 9.52 points to his cHit. We knew he was gunning for flies from the outset of the season, and it looks like his mission was accomplished.

Mike Moustakas at 87 — Frankly, being bookended by Jose Ramirez and Andrew Benintendi should, in a vacuum, should be great company. But this is a prime example of how cHit requires users to not take the numbers at face value. Ramirez and Benintendi aren’t slug-first hitters like Moose. They’ve got significantly better Speed scores, plus aren’t as prone to soft contact. I’d be very wary of Moose regressing, as he seems to rely on sneaking some less-than ideal homers over fences. If he goes to San Francisco I could see his value crater (see Belt, Brandon).

Eric Hosmer at 206 — Nope, negative, pass, I’m trying to sign quality hitters here <— Suggested responses for GMs when approached this offseason by Scott Boras on behalf of Hosmer.

Final Notes:

•  Batted-ball distribution data is noticeably absent. In one of my iterations I added in those stats, and found that they actually regressed the accuracy of the formula. It doesn’t matter where you hit the ball, as long as you hit it hard.
• Medium% and LD% are noisy stats. They also regressed the formula.
• I may look to replace BB% in future iterations. For now though, it does a decent job of capturing plate discipline and selectivity.
• K% doesn’t seem to have much of an impact on cHit (see Gallo, Joey).
• R-squared numbers over the last four years of data hold pretty steady between .65 and .75, which is really encouraging. Also, the bigger the pool of data per year (number of batters analyzed), the higher R-squared goes; which is ultimately the most encouraging result of this whole endeavor.

Input is greatly appreciated! I’m not a mathematician in any stretch of the imagination, so if there’s a better way of going about this I’d love to hear it. I’ll do a writeup about my swing-change findings at a later date.

Of the pitchers hitting the free-agent market this winter, Alex Cobb is not likely to receive the most fanfare.

Aces Yu Darvish and Jake Arrieta will command contracts north of $100 million. Closers Wade Davis and Greg Holland will do their best to secure four-year deals with big price tags. The whole world is watching every development in the Shohei Ohtani saga. Hell, among midmarket starting pitchers, MLB Trade Rumors predicts Lance Lynn to receive a more lucrative contract than Alex Cobb.

Cobb, who broke in as a full-time starter with Tampa Bay in 2012, has historically shown great promise and good-but-not-great results. He averaged 2.5 fWAR from 2012-2014, lost the next two seasons to Tommy John surgery, then came back with a 2.4 fWAR season in 2017. Cobb has never started 30 games in a season, nor has he ever thrown 200 innings. These facts are concerning to some, but I would argue that he is one of the wisest investments one can make this offseason.

Alex Cobb has evolved as a pitcher through pitch selection. Cobb has a great curveball. You either already know that, or you’re about to find out. He also mixes in a four-seam fastball, a splitter, and a sinker. Right now, curveballs are all the rage in baseball, resulting in tremendous success for pitchers like Rich Hill, Trevor Bauer, and Lance McCullers. They throw their curveballs so often that we can consider the breaking ball, not the fastball, to be their primary pitch. Like Hill, Bauer, and McCullers, Cobb has a quality breaking ball, so it stands to reason he should throw it more often and perhaps eschew his mediocre offerings. With Brooks Baseball, we can track the usage rate on each of his pitches throughout the season.

Look at the first couple data points for the usage rates on his pitches, and then compare them to his points at the end of the season. It’s clear that Cobb began to realize he works best by using the fastball and the curveball exclusively, so he increased his usage rate on those pitches and gradually phased out the splitter and sinker.

The question for Cobb is whether this was a good idea. In Cobb’s career, he’s only posted a strikeout-to-walk percentage (K-BB%) above 15% twice, and only ever so slightly so. He’s not bad in that regard, but it’s not where he makes his bread and butter. Fortunately for Cobb, he is one of the better pitchers in the league at inducing ground balls, which we know is favorable contact. The more grounders Cobb induces, the better he gets, and his curveball is a ground-ball machine. Consider the correlation between the rate at which Cobb increased his curveball usage and his ground-ball rate (GB%) throughout the season:

That’s a pretty strong correlation. It seems that Cobb is ready to join the Hills, Bauers, and McCullerses of the world and ride a high breaking-ball-usage rate to breakout success. Of course, it’s never going to be that easy for Cobb or anybody, but let’s go through one of his starts and parse what we can from the good and bad.

On September 4, Cobb pitched against a red-hot Minnesota Twins lineup and had one of his better starts of the season. His first batter of the game was second-half monster and fly-ball connoisseur Brian Dozier, and he managed to get him out on the first pitch.

It’s been proven that batters from the “fly-ball revolution” can be neutralized if you throw them high fastballs. These hitters are swinging up to lift the ball, but it’s difficult to put much lift on a high pitch coming in fast.

We’re going to focus on the curveball throughout this piece, but here is a fun fact about his fastball. Cobb’s heater sits at 92 MPH and had a spin rate of 2101 RPM this season, which seems pretty pedestrian. However, among starting pitchers with at least 100 batted-ball events involving fastballs, Alex Cobb’s has the 31st lowest exit velocity (87.1 MPH). To put this in perspective, that’s a better mark than James Paxton, Chris Sale, Max Scherzer, Jon Gray, Justin Verlander, and Luis Severino.

Cobb was smart to bait Dozier here, and he reaped the benefits with a first-pitch out to begin the ballgame.

In the second inning, we see Cobb pitching out of the stretch and unleashing a curveball that Ehire Adrianza buries into the ground. This will be the common theme today.

I mentioned earlier that Cobb doesn’t have the K-BB% of Chris Sale or Corey Kluber, so every once in awhile he walks batters. The common thought is that Cobb, who throws so many breaking balls, might end up behind in the count thanks to misplaced curves. Then, to get back in the count, he throws his 93 MPH fastball in the zone, which gets crushed by every hitter expecting it.

This would be a bad habit for Cobb to fall into, but he certainly didn’t in 2017. Consider the list of pitchers who threw the most curveballs while behind in the count this season (via Baseball Savant):There’s Cobb, in fifth place, not far behind Rich Hill himself. All five of these guys have great curveballs, so it makes sense for them to Trust the Process™ and continue dropping the hammer rather than submitting to doom and throwing a predictable fastball in the zone.

After walking the leadoff batter to start the third inning, Cobb knew Joe Mauer could make him pay. So rather than giving Mauer the fastball he wanted, Cobb began the at-bat by dropping a curveball for a strike that even froze the great Mauer.

This changed the whole at-bat, because now Mauer didn’t know whether Cobb would be coming at him with the curve or the fastball. Cobb took advantage of his opportunity, used the fastball to get him in an ideal 1-2 count, and then he went back the curveball and got Mauer to ground into a double play.

Cobb is comfortable throwing the curveball both behind in the count and with runners on base, so he can reap the rewards and induce quite a few double plays. That is an asset. Additionally, Cobb is comfortable throwing his curve from both the stretch (as we saw against Adrianza and Mauer) and from his big windup, as you can see here.

Eddie Rosario is a good hitter who made great strides late in the season, but even he found himself to be another ground-ball victim of Cobb’s curveball.

By the fifth inning, Cobb was almost through his second time against the Twins’ batting order. At this point, they weren’t sure whether to expect the curveball or the fastball, so Cobb was often ahead in the count. Here, he has Eduardo Escobar in a 1-2 count and throws a high fastball that Escobar swings right through.

Everyone in the park was expecting Cobb to throw the curveball to finish Escobar off. From a look at Escobar’s swing, it’s safe to say he was expecting a curveball himself. Cobb’s fastball isn’t necessarily anything special, but the way he uses it to pitch off the curveball can be.

With two outs in the inning, Cobb faced his 18th batter (which would complete his second time through against the opposing batting order). He quickly got Ehire Adrianza into an 0-2 count and then unleashed his best curveball of the night, which Adrianza pounded into the ground for another easy out.

At this point, Cobb had gone through the opposing order twice, pitched five innings, and only given up one run. Teams around the league are beginning to realize that most of their starters simply shouldn’t go out for the third time through the order, even if they are rolling. The Houston Astros just rode using Lance McCullers, Brad Peacock, and Charlie Morton in tandems all the way to the World Series. Those three guys are valuable pieces, and if Cobb is utilized liked this, so is he.

Unfortunately for Cobb, his pitch count was at 85, so his manager decided to bring him out for another inning. The Twins got their third look at Cobb, and I don’t need to cite the statistics to you about what happens at this point. Hitters are smart, so they can pick up on the tendencies of a pitcher if they see him so many times. Alex Cobb, as great at he was through five innings and two times through the order, is no exception to this rule.

Here is Joe Mauer taking an 0-2 curveball from Cobb and driving it into the gap in center for a double.

The important question here is, “was that Cobb’s fault or just a good piece of hitting from Joe Mauer?” Of course, the answer in baseball is always going to be both, but you can see in the embedded GIF that Cobb doesn’t necessarily leave the pitch up. In fact, if you compare it to the curveball that Cobb threw earlier in the game to get Mauer to ground into a double play, it doesn’t look much different — maybe an inch or two higher, at worst. The bigger change is Mauer, who swings like a guy fighting to stay alive in the first GIF, then like he knew exactly what was coming and how to handle it in the second.

This is the “third time through the order” effect in a microcosm. Pitches that fool batters earlier in the game become cookies, so the key is to relieve your pitcher while his pitches still fool the batters. Cobb should not be penalized by us for giving up a double to Mauer there; in 2018, analytical teams will be bringing in a new pitcher in these situations.

In this sense, Cobb is the first free-agent test case for the newest pitching trend in the industry — the tandem starter — one who pitches twice through the order, hopefully gets 15-18 outs, and then gives way to someone else. The Mets, who hired progressive Indians pitching coach Mickey Callaway to be their new manager, have made it clear that all starters not named deGrom or Syndergaard will be shielded from facing lineups more than twice in a game. Baseball has never experienced a shortage of five-inning pitchers in its history, but these changes in pitcher usage are leading to new premiums for these specialists.

It’s as simple as this: every team wants to stock their pitching staff with Alex Cobbs. To be clear, every team wants a Justin Verlander, but there is only one Justin Verlander; even horses Chris Sale and Corey Kluber showed significant wear and tear in October. To combat this dilemma, the Houston Astros deployed Lance McCullers, Brad Peacock, and Charlie Morton in five-inning tandems and rode them all the way to the last out of Game 7.

I expect Alex Cobb will fit into this role quite nicely for whichever team he signs with.