Archive for Brewers

Building an MLB roster is anything but simple, to say the least.

It would be very convenient if it was as easy as playing MLB: The Show, but as we are well aware of, there are many complexities to roster construction. Not only do organizations need to have high-end talent, but they also need to have 26 quality big-leaguers as well other players in the pipeline when adversity hits.

In a perfect world, teams would be able to have tons of star talent as well as intriguing depth. However, we do not live in a perfect world, and for that reason, teams need to adopt a specific strategy when it comes to building the best roster possible in the most efficient way imaginable.

Teams have generally two courses: will they prioritize star talent, or will they look to have as deep a team as possible? The first option is typically known as the “stars and scrubs” approach, and it is one that you see often see in basketball. Meanwhile, the latter approach is one that you’ll see with sports with deeper rosters, primarily football. Overall, both methods are used frequently by teams, but it is unclear which one is the more efficient when it comes to roster building.

What good is there to posing a problem if we aren’t going to find the answer for it? We need to dig deep into these two approaches! Should teams prioritize star talent even if it means their depth is lacking? Or is quantity more valuable than quality? Let us try to discover the answer to this critical question! Read the rest of this entry »

The Oakland Athletics and the Colorado Rockies are two of the most productive offenses in the league this year, both ranking in the top 5 teams by wRC+. By contrast, the Brewers and Cardinals have been below-average so far, with a 93 wRC+ and 96 wRC+ respectively. Could the strength of these teams’ early schedules be a factor in these varying levels of production?

To evaluate this, I tabulated the actual innings pitched by opponents of the Athletics, Rockies, Brewers, and Cardinals so far in 2014, and then tabulated the anticipated innings for upcoming opponents in June, assuming 9 innings per game. (You could pick any four teams you wanted; these were the ones that interested me). To evaluate the quality of the pitching staffs faced, I used SIERA (published here at FanGraphs) to evaluate the runs the pitching staffs would have been expected to give up, on average, in light of their actual skill sets. Last year, SIERA explained 63% (by r²) of the variance in runs given up by team pitching staffs, making it a good choice for this exercise. Because the pitchers faced in a game are largely outside an opposing team’s control, I used the current, team-average SIERA for each pitching staff, and weighted each inning of a team opponent by that value. I totaled the weighted values to get an aggregate SIERA for the collective opponents of each team.

Let’s start with quality of opposing pitchers for each team in the two months so far:

SIERA can be a difficult statistic to appreciate because it operates on a tighter curve than other pitching statistics (ERA, FIP), and small differences have a surprisingly large effect on runs allowed.  Remember that as with most pitching metrics, however, lower is better.

Let’s work from the league-average SIERA so far this year — 3.73 — to make some overall observations. First, the Rockies’ production is quite impressive, as they were facing above-average pitching skills yet managed to generate a 110 wRC+. The Athletics, on the other hand, generated the same 110 wRC+ as the Rockies, but the quality of competition was entirely different. For the past two months, they’ve had the privilege of teeing off on opponents with an average staff SIERA of 3.84. That is literally like facing a team slightly worse than the Astros (3.83 SIERA) every day for two months.

Contrast that with the task faced by the Brewers and Cardinals so far. To date, the teams faced by those two clubs have posted an aggregate SIERA of 3.58 (Brewers) and 3.62 (Cardinals). On average, that’s like facing a top-10 pitching staff every day for two months. Is it all that surprising, then, that these two teams, widely thought to be above-average offensively when the season began, have struggled to live up to offensive expectations so far?

How does this difference actually affect runs scored? That is a tricky fact to isolate. Drawing a zero-coefficient, least-squares line, each .01 of SIERA has been worth about half of a run so far in 2014. (That rate is comparable to the entire season of 2013, suggesting that this ratio stabilizes fairly quickly). By that measure, as shown in the above table, we would expect their tough schedule to have cost the Brewers almost a win (8 runs) over average in runs scored so far, and almost a win-and-a half as compared to Oakland (15 runs difference). The Cardinals are not far behind.

But that is just the average runs lost, and does not account for the outliers. It probably won’t surprise you to learn that the largest deviations (residuals, technically) from the relatively modest average tend to come from teams at the bottom half of the pitching barrel. When these teams have a bad day, they are really bad, and they are prone to getting blown out. These teams include the White Sox, the Rangers, and the Astros — teams that, as it so happens, have been well-represented on the Athletics’ schedule to date. Certainly, we should expect good teams to blow bad teams out, but when your offensive success consists substantially of beating up bad pitching, it’s hard to say how good your offense really is. The Brewers and Cardinals, on the other hand, have enjoyed healthy servings of the Braves, the Cubs, the Reds, and also each other. All of those teams are in the top half of the league by SIERA, and none of them has a tendency toward outlier scores that allow an opponent to super-size their run differential.

What’s particularly interesting, though, is that this imbalance is about to change in the month of June. Here is how it looks right now:

Things project to be different this month. In June, it is the Brewers’ turn to feast on garbage pitching, as they essentially get to bat against the Astros pitching staff for the entire month (3.87 SIERA). The Cardinals aren’t quite as fortunate, although they still get to face slightly below-average pitching (akin to facing the Rays every day), whereas the Athletics at least have to face a top-half schedule by aggregate SIERA. The poor Rockies, on the other hand, fare worst of all, with a schedule that could not be more grueling: the Braves, Brewers, Cardinals, Dodgers, and Nationals, among others. If the Rockies still come out of June with an above-average wRC+, we can safely say that they are probably a true-talent, above-average ball club, at least when healthy.

The point of all this is not to say that Oakland is some kind of fluke. That team’s out-sized run differential is also a credit to excellent pitching, and it is not Oakland’s fault that it was assigned what turned out to be a favorable early schedule. Yet, this analysis provides yet another reason to be careful when relying upon early-season run differentials.  Before you get too enamored with a team’s production to date, take a close look at the opponents a team has played. You may find that a team’s seemingly-extraordinary results appear to be less so, when you properly weight the skills of the opponents who allowed those results to come about.

Follow Jonathan on Twitter @bachlaw.

Jonathan writes a weekly column about the Brewers at Disciples of Uecker. He has also published at Baseball Prospectus.  

On Friday the Cardinals acquired Brewers reliever John Axford for a player to be named later. While dominant in 2010 and 2011, Axford’s lackluster performance since 2012 has many Cardinals fans uninspired by the move. In fact, most of the media attention has centered around his public farewell to Milwaukee fans.

Bernie Miklasz of the St. Louis Post-Dispatch offered his own analysis of the deal, calling it a “smart gamble” for the Cardinals. In addition to acknowledging Axford’s well documented HR/FB% struggles, Miklasz highlighted that the former closer has been particularly challenged by an ineffective fastball and poor performance in high-leverage situations.

PITCHf/x data on Axford’s fastball:

Axford’s performance in high-leverage situations:

FanGraphs readers will know that Cardinals GM John Mozeliak and his organization’s pitching staff have developed a reputation in recent years for quietly acquiring mediocre pitchers and helping them reach previously unimagined levels of success on the mound. To the extent that Mozeliak and company have similar designs for Axford, one must ask how they plan to help him reclaim his once dominant form.

The Cardinals may suggest any number of tweaks to Axford’s approach, but smart money has them coaching him to focus on throwing more first-pitch strikes. Jeff Sullivan recently reminded us of the importance of pitching ahead, and its import is surely not lost on manager Mike Matheny and pitching coach Derek Lilliquist. Since 2012, Redbird pitchers rank tops in the majors in terms of throwing first-pitch strikes.

In the same piece, Sullivan also noted that since arriving in St. Louis in July 2012, Edward Mujica has established himself as the league leader in first-pitch strikes, increasing that figure from a pedestrian 60.9% in 2011 to an elite 75.6% in 2013. Doing so has no doubt played a large part in his improved performance in high-leverage innings.

Mujica in 2011 with the Marlins:

Mujica in 2013 with the Cardinals:

While Mujica’s 2011 performance in high-leverage situations was not nearly as poor as Axford’s has been in 2012 and 2013, there exists a similar opportunity for improvement.

Specifically, Axford is getting absolutely crushed when behind in the count this season.

Axford’s 2013 pitching splits:

As they did when acquiring Mujica last year, look for the Cardinals to initially deploy Axford into low-leverage situations in which he can regain his confidence and focus on getting ahead in the count. If successful, one would expect the club to move Axford into higher-leverage situations, particularly if Mujica or Trevor Rosenthal wears down or runs into trouble down the stretch.

Thanks to an atrocious month of May, the 2013 Milwaukee Brewers were abruptly transformed from a fringe contender into a rebuilding baseball club.

Most people agree that the Brewers need to build a new core, but what does that mean? Many teams have young players in the midst of an above-average season, but that doesn’t necessarily translate to sustainable success for the roster as a whole. And the opinions expressed about so-called core players are usually subjective and not expressed in a way that allows direct comparisons between teams.

We could really use a metric to compare the rosters of teams who are developing potentially sustainable talent with those who aren’t. My effort to do this is called Core Wins, which summarizes the extent to which a team’s success is being driven from players most likely to constitute core talent, as opposed to players on their way out the door, probably in decline, or both.

To do this, we need define what it means to be a core player, and specifically the factors by which we evaluate a core player’s respective contributions to the team.

The Core Player

In my view, core players do three things: (1) contribute significantly to their team’s success, (2) do so while under extended team control, and (3) do so at or before they reach their peak ages of likely productivity. Each of those attributes needs to be mathematically summarized to reduce these contributions to a measurable value.

The first factor is the easiest: a core player is expected to contribute, and to do so above what could be found in an entry-level minor-league call-up. A major league player’s ability to do so over the course of a season is commonly summarized in some version of the wins above replacement (WAR) metric, which attempts to combine the player’s batting, fielding, and if applicable, pitching contributions. A counting statistic also fits our needs best, since we are looking for aggregate contributions over the course of a single season. So, we’ll use WAR, as calculated by Fangraphs (fWAR).

The second factor, team control, is more complicated. Player control comes in two primary forms: (1) players under club control due to the terms of baseball’s collective bargaining agreement, and (2) players who have signed freely-negotiated contracts. The collective bargaining agreement keeps players under club control for at least six major league years. Free agent contracts range from one-year stop-gaps to those lasting a decade or longer. Most ballclubs are a collection of young players under sustained club control, long-term (and typically expensive) free agents, and stopgap players on value contracts. But teams with a sustainable core should be drawing significant production from players who will actually be around in future years. If too much production is coming from departing or declining players, the club is asking for trouble.

The third factor — player age — is less significant, but still important. Younger players are cheaper than older players, and thus easier to afford and keep around. Younger players are less frequently injured, meaning they will be in the lineup more often. Younger players who have not yet reached their peak production age will also probably continue to improve, whereas players beyond their peak age will probably decline.

However, age can be overemphasized. The primary advantage of youth— extended club control — is already being considered. Moreover, mature players signed to long-term contracts tend to be some of the most valuable players in the game — Joey Votto, Felix Hernandez, and their peers. And while prospects are important, most ballclubs would strongly prefer Joey Votto over a 22-year old prospect who may, but probably won’t, someday turn into Joey Votto. So while age matters, it is not as important as control.

So to summarize: we need to weigh player value, but do it in a way that primarily emphasizes team control while still placing some value on a player’s age.

Method

Player Contributions

All WAR figures were drawn from Fangraphs. The figures for batting fWAR (which incorporates fielding) and pitching fWAR were combined into one spreadsheet for each team year. When a player generated values for both batting (plus fielding) and pitching WAR, those values were summed, including the effect of any negative values. Once a net value was obtained for all players on a team roster for the year, all zero or net negative WAR values were disregarded.

Player Control Index

Player control numbers were drawn primarily from Cot’s Contracts, and cross-checked with Baseball Reference, other sources, and common sense as needed. Cot’s provides individual player contract data from 2009 onward, so only data from 2009 through 2012 was used. Control years were weighted identically, regardless of whether they arose from the CBA or a free agent contract. A player subject to a club option was considered to be under club control for that year. The author’s best estimate of remaining club control was necessary in a few cases when contract details were unclear, but not surprisingly, most of those players were fringe contributors that would not constitute core talent anyway.

A player was assigned one control year if his contract expired after the current season, two control years if his contract expired after the following season, and so on. For practical reasons — including the frequent shuffling from the minors experienced by young players, and the oft-diminishing returns of the longest contracts — the maximum number of control years considered for a player was 5. A Control Index was then calculated for each player in each roster year, with the number of control years as numerator, and an assigned denominator of 2 — for the minimum years that would constitute extended organizational control. So, for example, a player with an expiring contract would have a Control Index of 0.5 (1 season left divided by 2), and a typical player in their final pre-arbitration year would have a Control Index of 2.0 (4 seasons of control divided by 2). The maximum Control Index is 2.5.

Age Index

A player’s “baseball age” — their age on July 1 of a given season — was drawn from Fangraphs. An Age Index was then calculated for each player using an assigned value for a typical peak performance age as the numerator and the player’s baseball age for each season as the denominator. There has been some debate on the overall peak performance age for ball players, but, taking a strong hint from one of my reviewers, I used 27. To give some sense of the value range, the Age Index in 2012 for Mike Trout would have been 1.35 (27/20) and for Livan Hernandez would have been 0.73 (27/37).

Determining Core Win Value

In my formula, Core Win value is a weighting exercise. To calculate a player’s Core Win value to a roster, I multiplied the player’s net fWAR for each season by the Control Index and the Age Index. The Control Index has a greater range (0.5 to 2.5) and thus a greater potential weight than the Age Index, which seems appropriate for the reasons stated above. The combined effect of these indices means young prospects that produce at a level of 2 fWAR or higher are weighted the most heavily. This makes sense: players who promptly adjust to the difficulty of the major leagues, yet still have years of probable improvement ahead of them, all while under extended team control, are those most likely to constitute a sustainable core of talent for the ballclub.

Discussion

Now that we have a formula for Core Win Value, we need to decide what it means to have a winning core. That cut-off is ultimately in the eye of the beholder, but I looked to the gold standard: the Tampa Bay Rays. The Rays are widely acclaimed for their ability to acquire and maintain control of young talent, often through early buy-outs of free agent years, combined with club options that retain team flexibility. This has been particularly true over the years covered by this study: 2009 through 2012.

To provide some contrast with the Rays, we will also consider the roster construction during that same time period of the New York Mets and the Oakland Athletics.

The Gold Standard: The Rays

Not surprisingly, the Core Wins formula likes the Rays very much. Indeed, three characteristics of the Rays between 2009 and 2012 suggest a working definition of a team with a strong, sustainable core: (1) the Rays consistently feature five or more players producing a Core Win Value of 5 or higher per season, which is my working definition of a “Core Player”; (2) they have accomplished this feat in multiple consecutive years (all four years I studied, in fact) and (3) at least two of these Core Players were usually pitchers.

Let’s start with 2009. For ease of viewing, in each of these tables, I’ve bolded wins figures for potential Core Players (five or more Core Wins). I’ve also italicized the names of pitchers who cross the Core Wins threshold, to distinguish them from position players.

2009 Tampa Bay Rays

In 2009, the Rays won 84 games, featuring seven players that delivered 5 Core Wins or more. This depth, plus MVP-level performances from Evan Longoria and Ben Zobrist, prepared the Rays for the eventual departure of Carl Crawford, whose dwindling team control was removing him from the team’s core. Note that the team’s two best pitchers in 2009, James Shields and Matt Garza, were both under team control for 5 more years. David Price generated only 1.3 fWAR in 2009, and thus barely missed the Core Wins cut, but he was on the upswing.

2010 Tampa Bay Rays

In 2010, the Rays maintained 7 players at a Core Win level of 5 or more, culminating in 96 team wins and a first-place finish in the AL East. Only one pitcher (David Price) made the Core Win cut-off of 5 this time, but James Shields just missed it. Matt Garza regressed a bit (and was promptly traded to the Cubs for more prospects, without any negative effect). Carl Crawford, despite an MVP-level year of 7.4 fWAR, is discounted out of the team core by the Core Wins formula, due to his team control ending that year.

2011 Tampa Bay Rays

2011 featured more of the same. Carl Crawford was gone, but the Rays did not miss him, as the formula anticipated. Six Rays met the Core Win threshold, two of them pitchers (Price, Shields). Superstar contributions by Zobrist and Longoria, combined with ascending contributions from four others — including Price and Shields — resulted in a highly-successful season from Tampa Bay’s controlled talent, and others. The Rays won 91 games and made a wild-card playoff appearance.

2012 Tampa Bay Rays

By 2012, the Rays had developed an astonishing eight players that crossed our Core Win threshold. An incredible five of these players — over half the team’s core, under our formula — were starting pitchers with at least four years of team control remaining. This means that the Rays’ entire starting rotation was under long-term control. Despite a hamstring injury that kept him out for over three months, Evan Longoria still contributed 2.5 fWAR to the effort, and his new contract provided the team with the long-term control to keep him in the team’s core. The 2012 Rays won 90 games: not enough for even a wildcard in the American League that year, but a terrific season nonetheless.

Before the 2013 season, the Rays dealt James Shields to Kansas City for the bat of Wil Meyers and other prospects. As of the publication of this article, Fangraphs projects them to win 93 games in 2013, on a payroll of only $62 million. In sum, the Rays have been, and continue to be, the prototypical team that demonstrates what it means to have a sustainable core of controlled talent.

By Stark Contrast, the New York Mets

The Mets have been bad for years, and the Core Wins formula identifies major flaws in roster construction as a possible culprit.

2009 New York Mets

Dreadful: there is no other way to describe the 2009 Mets. That year, the Mets spent $140 million for 70 team wins, generating only three Core Players under our formula. Even those players gave only ok performances. From a Core Wins perspective, this roster was terrible. One of the three players to meet the Core Wins threshold, and the only starting pitcher — Johan Santana — is heading past his probable prime.

2010 New York Mets

The results for the Mets weren’t much better in 2010 — 79 wins — but their roster at least improved. Six players made Core Player-type contributions, and two of those players were starting pitchers. If these performances proved to be sustainable over multiple years, or at least into 2011, the Mets had some reason for optimism.

2011 New York Mets

But it didn’t work out. In 2011, the Mets were right back to a pathetic three Core Player performances, with only one starting pitcher among them. In fact, the Mets’s strongest core performance in 2011 came from 2.8-win Daniel Murphy. Not good. Ike Davis promptly regressed out of the core, David Wright fought injuries, and Johann Santana didn’t play all year, which is why Core Wins discounts the value of aging players. Although Jose Reyes provided a superstar WAR of 5.8 and a batting title, as a departing free agent, that performance provided no ongoing value to the team, and the Core Wins formula discounts it accordingly. It all amounted to 77 wins, and low expectations for the following season.

2012 New York Mets

Validating this expectation, the 2012 Mets did even worse, winning only 74 games. Only three players could pass the Core Wins threshold, and one of their best players — R.A. Dickey — could not even quality as a Core Player, despite 4.4 fWAR. The Core Wins formula discounts the going-forward value of 37-year-old performances, and Dickey’s 2013 performance with the Blue Jays has validated that skepticism.

But, the Mets get enough bad news, so let’s focus on some positive aspects. In 2012, David Wright performed at an MVP level. And while the Mets had only four Core Win players in 2011, two of them are starting pitchers, which is an important positive from our study of the Rays. In fact, one starter, Jon Niese, was signed to an early long-term contract a very Rays thing to do, putting a competent starter under extended team control. Matt Harvey also looks to be a championship-caliber ace, and remains under maximum team control.

So far, 2013 is not being kind to the Mets either — Fangraphs currently projects them to finish with 76 wins — but there are hints that things may soon be looking up, particularly if their farm system can continue to develop strong rotation talent, as many project that it will.

Trending in the Right Direction: The Oakland Athletics

Finally, let’s conclude with what turns out to be a Goldilocks example: the team that like the Mets, tried and failed to improve their core, but stuck with it and seems to have gotten the hang of it lately: the Oakland Athletics.

2009 Oakland Athletics

In terms of roster-building, the 2009 Athletics took a fairly solid approach: they ended up with six potential Core Players, and three of them are starting pitchers. All these players offered at least five years of team control. However, the 2009 Athletics also underscore that just because your wins are coming from the right place does not mean you are getting enough of them. The best performance in this group is still only 3.9 fWAR — good, not great. The 2009 Athletics won only 74 games, although at least they didn’t have to pay Mets prices to get there.

2010 Oakland Athletics

In 2010, the Athletics were better. Leveraging some of the previous year’s young talent, they ended up 81-81. There were six core-type player performances, and four of them pitchers: ordinarily, a good thing. But notably, there was not a significant amount of improvement from 2009’s core contributors. In fact, the strongest core contributors in 2010, Daric Barton and Cliff Pennington, were marginal contributors the year before, raising the possibility of fluke performances. And, only two core performances came from position players, which didn’t leave much room for error going forward in the scoring department. So, the 2010 Athletics showed hints of a developing core, but a fragile one.

2011 Oakland Athletics

And indeed it was. The Athletics rotation was devastated by injuries in 2011: Dallas Braden needed shoulder surgery, and Brett Anderson needed Tommy John surgery. That would be a tough blow for any team, but particularly for Oakland, which did not have much behind them. What was left of the rotation (and roster) collapsed to three core-type players. The two core bats of consequence in 2010, Daric Barton and Cliff Pennington, immediately regressed and revealed themselves to be one-year wonders. The only developing bat remaining was an average, but unspectacular debut by Jemile Weeks, whose own performance later proved unsustainable.

Although two out of the three core players were starting pitchers, there was little to support it. Brandon McCarthy actually had a very good year (4.5 fWAR), but since he was completing a 1-year-deal at the time, he offered the A’s no core value.

Things looked bleak. Fortunately, the A’s stuck to their guns and kept developing young talent. Then, 2012 happened.

2012 Oakland Athletics

2012 found the Athletics again having restocked their core, this time with a balance of bats and pitching talent. Five core players are represented, and their values are not all projection, either: Josh Reddick produced 4.5 fWAR, Jarrod Parker generated 3.4 fWAR, and two other controlled players produced close to 3 fWAR. Two core players are starting pitchers. Furthermore, in 2012, the A’s finally enjoyed a little luck. They outplayed their Pythagorean expectation by a few wins, got 2+ win performances from non-core starters on short-term deals — Brandon McCarthy and Bartolo Colon — and ended up with 94 wins and an AL West title, on top of what appeared to be developing core.

If you thought that the Athletics were finally getting the hang of this roster-building thing, you may be right. The Athletics have spent much of 2013 on top of the AL West, and Fangraphs currently projects them to finish with 91 wins — on a budget of $62 million. A very Rays-like experience all around, which corresponds with quality roster construction.

Conclusion

The Core Wins metric profiles the extent to which team performances are being delivered by so-called Core Players, and also tracks the progression of players in and out of the club’s core over time. Even herculean performances by impending free agents (see Carl Crawford, 2010) tend to wash out of the metric, while young players who initially impress, but fail to sustain (see Ike Davis, 2011) also fall out of the measured core, despite their built-in advantages of youth and team control. As such, Core Wins strikes me as useful and if nothing else, an improvement over the prevailing practice of eyeballing the roster and cherry-picking performances by younger players.

Because it is based on WAR (a counting statistic), Core Wins is primarily backward-looking. But, the general method can also be used prospectively. For example, if you input projections from your preferred player projection system, you could forecast the extent to which your team is likely to get future contributions from sustainable sources — a useful thing to know when deciding between trades, farm system call-ups, or free agent signings. Similarly, if you want to focus on particular positions of concern — (third base, starting rotation) — or skill sets (batter OBP, pitcher FIP) — you can adjust the Age Index to account for the peak performance ages corresponding with those particular positions or skills. Those analyses can be retrospective or prospective.

Of course, superior roster construction does not guarantee superior performance, as the Oakland A’s can attest. Previously healthy players can be felled by injury, and promising talents too often fail to sustain early achievements. But in general, developing Core Players makes good sense, and certainly seems to be delivering results for the league’s most efficient ballclubs. So if your favorite team seems incapable of stacking success, you might check to see how good of a job the front office has been doing in generating Core Wins.

Special thanks to Paul Noonan and Tom Tango, who both offered helpful comments on the general direction of this article. All errors are entirely my own, including some table pasting errors in the original version. Thanks to Andrew Yuskaitis for pointing those out. They have now been corrected.

Earlier in the month I had an idea. It all stemmed from the idea of quantifying the un-quantifiable. I was going to record grit.

A lot of times we hear about how gritty a player is, but it’s tossed around with no real proof. Sure Nick Punto dives into first a lot, but is that really more gritty than stupid? Is a guy like David Eckstein really the grittiest of all gritty players, or can it be a guy we don’t really notice?

To figure all of this out I, along with some help, wrote a formula. The formula is imperfect, because of a lack of reliable sources for things like headfirst slides and broken-up double plays, but it tries and does its job. The formula is as follows:

(((InfH+1stS3+(.5*CS+SB2+1.5*SB3+3*SBH))(2*P/PA+.5*Foul/S%))/(HR+1)+(.1*PA/Seasons)+PitchingAppearances

Where InfH stands for Infield Hits and 1stS3 means first to third on a single, we have found a way to see a players GRIT (Game Rating In Testosterone.) All this stat is designed to show is who works harder to score a run for their team, it doesn’t show you who is better or worse, but it does show who tries.

Using this formula my small team of experts has found David Eckstein to have a career GRIT of 172.16, which is very impressive over a 10-year career, but it’s no Juan Pierre, who has amassed a career GRIT of, wait for it, 1582.

We also found the difference between Martin Prado and Justin Upton, who was the subject of criticism from Diamondbacks GM Kevin Towers who said he wasn’t gritty enough prior to trading him for Prado. We found out that Kevin Towers may have been wrong.

Using their numbers the formula says that Prado has put together a GRIT of 57.93 in his career, where Upton has a GRIT of 68.65, despite playing in one less season. So, Kevin Towers, you may need to rethink your strategy.

Also invented was TeamGRIT, a stat that uses numerous numbers to calculate how hard a team works for each run.

A disclaimer here before I list the GRITs: I am not trying to say that some teams work harder than others, nor am I saying that a high GRIT is more or less valuable than a low GRIT, all these numbers illustrate is that some teams are more comfortable with power numbers to win games, while others are more inclined to small ball.

The formula used is

(((InfH+1.5*BuntHits)+1stS3+2ndDH(.5*CS+SB2+1.5*SB3+3*SBH)(Pitches/PA+.5*Fouls/Strike%)+(GIDPinduced+OFAssists))/(HR+.5*HRA))+(.1*PA/GamesPlayed)

The following are the AL leaders prior to games played on August 7th 2013

Royals – 90.57 (9th in wins)

Indians – 74.77 (6th in wins)

Red Sox – 73.92 (1st in wins)

A’s – 70.57 (5th in wins)

Blue Jays – 61.73 (10th in wins)

Rangers – 56.52 (4th in wins)

Astros – 55.70 (15th in wins)

White Sox – 51.62 (14th in wins)

Rays – 51.10 (2nd in wins)

Angels – 48.98 (12th in wins)

Twins – 46.97 (13th in wins)

Yankees – 45.59 (8th in wins)

Orioles – 40.49 (7th in wins)

Tigers – 30.30 (3rd in wins)

Mariners – 25.90 (11th in wins)

The most interesting numbers to me are those of the Royals and the Tigers. On opposite ends of the spectrum, one is a team that absolutely crushes the ball, everything that comes their way, the Tigers hit it, and they’re fine with it. They don’t feel the need to manufacture runs the way that the Royals do. The Royals seem to grind more to score their runs. More than any other team in the league by a large margin. They, like the Astros at 55 GRITs, are doing everything in their power to score more runs. It doesn’t always work, but there’s something to be said about a team that works to get extra runs and extra outs. If anything, they’re less comfortable with a lead than the Tigers. That isn’t to say the Tigers get lazy, just that they tend to not have to try so much.

In the NL there appears to be a negative correlation between GRIT and wins; I assure you, this is just a coincidence.

NL leaders prior to games played on August 7th 2013

Pirates – 80.83 (2nd in wins)

Rockies – 77.08 (8th in wins)

Marlins – 76.31 (15th in wins)

Brewers – 73.57 (14th in wins)

Mets – 67.33 (11th in wins)

Giants – 64.21 (12th in wins)

Padres – 62.53 (9th in wins)

Phillies – 57.06 (10th in wins)

Dodgers – 51.83 (4th in wins)

Cardinals – 47.67 (3rd in wins)

Nationals – 45.03 (7th in wins)

Cubs – 44.79 (13th in wins)

Diamondbacks – 42.38 (6th in wins)

Reds – 39.99 (5th in wins)

Braves – 31.12 (1st in wins)

The only thing these numbers definitively tell us is that there is a lot more GRIT in the American League, which is a deviation from the stereotype of hard-hitting AL clubs. The longball is less important in the American League, whereas manufacturing runs is a lot more emphasized. In the National League one team stands out from the pack: The Pirates.

They have a GRIT of 80.83 while also being in 2nd place, they are the only team in the top 5 of wins who is also in the top 5 of GRIT. The Pirates also hit a fair amount of home runs, but that’s not enough for them. They aren’t comfortable with just a lead. They want more of a lead. They try their damnedest to score more runs than anyone else by any means necessary. Is this because they spent so many years as a losing team? Possibly, but that’s just a theory.

As I said before, these numbers are not proof that any team is better than another, nor are they proof than any player is better than another, just that some teams and players are GRITtier than others.

So there you have it, your introduction to GRIT.

In fact, the Brewers were downright putrid, winning only six games the entire month.  Their record in May was so bad (6-22) that it tied the worst month in franchise history: the August turned out by the 1969 Seattle Pilots, who ended the following season in bankruptcy, followed by a permanent road trip to become the Milwaukee Brewers.

The Brewers ended the month of April only a half game out of first place.  The Brewers ended the month of May 15 games behind the St. Louis Cardinals, managing the impressive feat of losing 14.5 games in the standings in one month.  Now that is a tailspin.

CoolStandings.Com currently gives the Brewers a 1 in 250 chance of making even the wild-card play-in game.  GM Doug Melvin admitted there is no chance the Brewers will be buyers this year at the trade deadline.  Rather, they will either be in a sell mode, seeking high-ceiling prospects a few years away, or keeping the assets they have, presumably only if they cannot get anything in return.  In short, the Brewers are suddenly rebuilding, and are focusing on  stocking up their farm system and developing controllable rotation talent.

But, rebuilding is a complicated topic in small markets like Milwaukee.  As Wendy Thurm has noted, the Brewers, with their limited geographic reach, have one of the smallest television contracts in the league.  Thus, the Brewers rely upon strong attendance to deliver profits for Mark Attanasio and his ownership group.  In recent years, the Brewers’ attendance fortunately has been some of the most impressive in baseball, particularly in comparison to the size of the Milwaukee metropolitan area.  Over the last five years, the Brewers have consistently approached or exceeded three million fans, despite challenging economic times.  So, one thing the Brewers cannot afford is a collapse akin to the mere 1.7 million fans they drew in 2003 during a terrible season — not if they want to make the investments in future talent required to make the franchise a perennial contender.

So, the Brewers face an obvious challenge: the team needs to lose enough games to obtain a prime draft position, and thereby maximize its chances to draft a top-ceiling player with minimum bust potential.  At the same time, the Brewers need to avoid losing in any drawn-out fashion, because a corresponding and sustained decline in attendance could hemorrhage desperately-needed cash from their balance sheet.  As Ryan Topp and others have argued, this need to maintain attendance in the short term seems to be one reason why the Brewers have systematically traded away what previously was an excellent farm system, with the apparent goal of maintaining the aura of a competitive team.

How does one navigate this problem?  Well, the best solution could be to experience a May like the Brewers just suffered.  Doing so addresses two problems: (1) it abruptly puts the team on course to get a top 5 draft pick, and (2) it achieves this result so abruptly, and in this case so early in the season, that the fan base can still — at least in theory —enjoy much-improved baseball for the remainder of the season without jeopardizing that draft slot.  In short, when you can take your medicine over the course of one month, instead of over an entire season, you really ought to do it.

As to the draft:

Thanks to May, the Brewers currently have the fifth-worst record in baseball at 23–37.  As of the morning of June 8, 2013, FanGraphs predicted that the Brewers will end the season tied for baseball’s fourth-worst record with the New York Mets at 73–89.  Provided that 2013’s top five draft picks all reach agreement with their teams, the Brewers are on pace for a top-5 draft slot in 2014.

The Brewers have not had a top-5 pick in the Rule 4 draft since 2005, when they picked some guy named Ryan Braun.  Before 2013, the top five slots in the draft provided, among others, Buster Posey (#5, 2008), Stephen Strasburg (#1, 2009), Manny Machado (#3, 2010), Dylan Bundy (#4, 2011), and Byron Buxton (#2, 2012) — the types of superstar prospects the Brewers have been denied for years, and which they need to anchor their next generation of players.  At the end of April, and before May occurred, the Brewers were on track for yet another mid-round pick slot.

As to the rest of the season:

It is unlikely that the Brewers will continue to suffer the combination of injuries and dreadful rotation pitching that helped ruin their May.  FanGraphs seems to agree, predicting that the current Brewers roster (or something like it) will essentially play .500 baseball for the rest of the season, even while maintaining one of the five worst records in the game.

Average baseball is not contending baseball, but average baseball at least would offer Brewers fans — already pleased with Miller Park’s immunity from rain delays — a reasonable likelihood of seeing a win on any given day.  In 2009, the Brewers were able to bring in over three million fans, despite finishing under .500 overall.  In 2010, the Brewers ended up eight games under .500, but still brought in 2.7 million fans.  It remains to be seen whether playing .500 baseball for the rest of the 2013 season would be sufficient to keep fans coming through the Miller Park turnstiles, but if so, the increasing remoteness of May could be a significant factor, particularly if the team can convince fans that “one bad month” does not represent the current Miller Park experience or true caliber of the team.

Of course, it is also possible that the Brewers will be able to trade significant assets at the deadline in exchange for the prospects Doug Melvin wants.  If so, their projected record could, and probably would decline.  (This is necessarily not a bad thing, given that 68.5 wins is the average cut-off to secure a top 5 draft spot from 2003 through 2012).  If that happens, the Brewers will have a further challenge on their hands in trying to provide even average baseball for their fans, and maintain the attendance they need.

That said, the Brewers’ remarkable close to 2012 — an incredible .610 winning percentage from August through October — was accomplished after trading away Zack Greinke and calling up minor league talent to plug gaps in the rotation left by Greinke’s trade and Shaun Marcum’s injuries.  If the Brewers are once again able to make advantageous trades at the deadline, and also able to play even .500 ball for the rest of the year, they are still in a position to do so without hurting their chances to get the impact player they need in the 2014 Rule 4 draft.

If they can pull both of these things off, much of the thanks should be given to the horrible month of May.