Organizational Triangle

How do you evaluate the organizational strength of a baseball team?

The first, and most obvious factor is the caliber of players on the team.  The better a team’s players, the better its chances of winning in the short term.  Factor in the risk and upside of the current roster, and you can get a pretty good idea of the team’s present talent level.  Obvious enough.

Next, you have the future talent.  Prospect lists are a part of this, but so are players under team control beyond the upcoming season.  If you have a good team with young players signed for a few years, that’s a good foundation for the team’s future as well as its present.  Even veteran players on big contracts fall under this category; a player may be an undesirable asset if his contract pays him more than he’s worth, but as long as he’s still good enough to play at the MLB level, he’s still talent.  Again, makes intuitive sense.

The third aspect is financial flexibility, which is essentially the gap between the team’s current financial obligations and its potential spending.  This is also a little harder to figure out.  One reason for this is that the financial information of teams – both how much they make and what their ultimate budgetary goals are – is relatively obscure.  The team’s financial flexibility can improve in one of three ways; by increasing revenue, by decreasing cost, or by a shift in the mentality of ownership.  A flexible payroll opens up options for the management, whether that means taking on a new contract, renewing an old one, or covering raises owed to players reaching arbitration.

I envision a concept similar to the triangle used to look at constraints in project management.

Here’s an illustration of the concept.

Organizational Triangle

The present talent is the main factor in determining how likely it is a team will win in a given year, whereas the other two play a bigger role in the team’s ability to improve or sustain the talent level going forward.  The future talent is a random but efficient method of improving the team going forward; you may have three good prospects and have one success out of them, but you don’t know which one will succeed until they prove themselves.  Financial flexibility is a more immediate method of improving, but at a higher premium.  In theory, the strength of an organization’s assets can be determined by looking at the area of the triangle, assuming the weighting of the three branches is correct.

Generally speaking, a team needs to make trade-offs in at least one of these areas in order to improve the others.  Signing a free agent reduces financial flexibility, while improving the present talent and often the future talent.  Trading a veteran for prospects improves the future talent and financial flexibility, while usually decreasing the current talent.  Or, trading prospects for established players is a way to improve current talent at the expense of future talent, often at a lower financial cost that free agents.
The other variable here is time, which can cause a shift in all three categories.  The draft is an opportunity every year to add “free” future talent at a minimal impact on financial flexibility.  As prospects graduate and young players mature, the current talent improves for only a slow decrease in future talent.  A team that wins, particularly if they earn postseason revenue, sees an increase in revenue leading to more financial flexibility.  Time can also deteriorate the three elements.  Players reach arbitration and the same talent costs more.  Veterans age, reducing current talent.  Service time is used up, reducing future talent.

A big part of building a competitive team is about balancing these three elements.

The easiest trade-off is financial flexibility for current talent.  There are always players to be signed, as long as the team’s budget isn’t maxed out.  However, generally speaking, free agents tend to decline in talent throughout the contract, meaning you typically get the most bang for the buck directly after the signing, with the value decreasing over time.  It’s often an expensive way of adding talent, but it works in the short term.  For that reason, teams usually do best to time their major free agent acquisitions when the talent will make the most difference.  A winning team will usually see revenue increases to boost its spending capacity, but a team that uses up its budget too soon will find itself scrambling to cut costs before its revenue streams expand.

From a fan’s perspective, financial flexibility is a bit of a bugaboo.  It’s important for a team to maintain enough financial flexibility to further invest when the team’s ready to contend, but until the team reaches that point, it’s hard to tell the difference between a management that chooses not to expend its financial flexibility for strategic reasons and an ownership who chooses not to spend its money because it’s cheap.  It’s a particularly tough pill to swallow when an organization has gone through multiple rebuilds and an extended stretch without a postseason appearance, to see an ownership spending well below its perceived capacity on payroll, but staying frugal during the building process greatly improves a team’s agility for making the moves to reach the top level and stay there.

This brings me around the the position the Jays are in right now.

Over the last two years, the Jays have reduced costs and improved financial flexibility.  They did so while maintaining, and arguably improving the level of current talent on the field certainly the present talent’s upside is better.  And in the process, they radically improved the team’s future talent.  He somehow managed to improve all three vertices of the organizational triangle without making trade-offs elsewhere.  That’s not easy to do.  They have a solid young core, with significant upside on the roster, and a ton of cost-controlled talent.  It won’t take any breakout performances for them to reach the mid to high 80’s in wins, just reasonably good health.  It’s the type of roster that could easily take a significant step forward with some realistic improvement, especially among young pitchers.  It’s a team that’s teetering on the cusp, and one where an investment in free agent talent could conceivably put them in wildcard contention as soon as 2012.  They’re at the position where a long term commitment is defensible, but risky.  It’s a good position to be in.

It’s also a delicate position.  Fans can see enough talent to get excited, but don’t yet have the results to build confidence.  Is AA avoiding big ticket free agents because it feels the demands of the available players will limit their flexibility too much for the talent they bring, or simply because they refuse to spend big?  Is he waiting to see which players demands drop as the offseason progresses?  Does he feel the team’s roster has too much risk to go all-in now?  Does he see some potential mid-season trade targets, when there’s less teams in need?  Fans get impatient at times like this, but it’s critical that a good GM be able to ignore the criticism and continue on his course he feels puts the Jays in the best position to be a regular contender.

The worst thing a GM can do here is make a move he doesn’t believe is in the best interests of the organization for PR purposes.  If that means he or the ownership need to endure criticism, so be it.  In the end, the only lasting PR is winning, and the best way to build a sustained winner is to pay attention to all three vertices of the Organizational Triangle.

Insert Bad Pun Here

Well, Jays fans didn’t get the Yu-letide blessing they wanted.  The natural reaction, of course, is to kick and scream and shout all sorts of obscenities at Rogers for being cheapskates, but it’s worth taking a step back to gain some perspective.

The first thing to remember is that losing out on Darvish does not make the Jays any better or worse than they were before he was posted.  We can debate the merits of whether the risk is worth the money.  We won’t know the wisdom of the ace-level investment until after we see how he transitions.  However, regardless of how this works out for Texas, ere’s something to chew on:

Signing Darvish for the price he’ll cost would only make sense if you believe the core talent is on the cusp of contention.

Signing free agents to “make a splash” and try to jumpstart the fanbase almost never works.  There might be a short-term attendance boost, but more often than not the team splashing around ends up drowning.  Consider that for a moment: the only way losing out on Darvish ends up looking like a mistake is if the current crop of young, cost-controlled talent ends up performing at a high enough level that Darvish’s arm would have made a difference.  That means the team would need to be at least within four or five games of a postseason birth on, what people are quick to point out, is a low payroll.  In other words, the only way the Jays would be in a better place with Darvish than without is if the organization is already in a really good place.

It’s an interesting conundrum:  disappointment only makes rational sense when mixed with optimism.

How Much Does Payroll Matter in Baseball?

There have been enough studies showing the correlation between payroll and winning in baseball that I’m not going to rehash that.  Plenty of studies have been done by people with more statistical knowledge than I have, and the results are typically what you’d expect: Teams that spend more tend to win more.  There are outliers, both low-budget teams that win and high-budget teams that lose, but over time, money usually leads to winning.

Here’s a nice graphic to show how strong the correlation is.

So if you want to build a winner, the best way to do it is to spend, right?

Not so fast.  The key word here is build.  The 2010 Phillies and 2011 Phillies are two separate data points supporting the correlation between payroll spending and winning, but neither is an example of building a winning team – they’re examples of sustaining a winning team.  If we isolate the teams that have had periods of sustained  high-end success since the wildcard era started – say, at least four postseason appearances without a prolonged absence – we’ll get an idea of how the best teams are built.  I looked at each of these teams, in only the first year in which they made the postseason (or were positioned to in the strike year), to see what their payroll was compared to the league median.  This is just a quick and dirty study, but I nonetheless found some interesting results here.

The teams used in this study are as follows, with the teams payroll as a percentage of the league median in the first year:

– Braves, 1991-2005 – 80.2%

– Red Sox, 1995-2009 – 88.4%

– Indians, 1994-2001 – 84.6%

– Astros, 1997-2005 – 84.9%

– Angels, 2002-2009 – 97.8%

– Dodgers, 2004-2009 – 127.6%

– Twins, 2002-2010 – 64%

– Yankees, 1994-2011 – 127.6%

– A’s, 2000-2006 – 55.3%

– Phillies, 2007-2011 – 113%

– Giants, 1997-2003 – 86.8%

– Mariners, 1995-2001 – 99.3%

– Cardinals, 2000-2011 – 113%

 

The average comes out to 94.1%.  Nine of the thirteen team in this sample started their runs of success with a payroll below their league’s median.  While many of these teams went on to become higher spending teams in order to sustain their success, this suggests that the most successful teams usually don’t reach that point by dumping a bunch of money into their teams; rather, they built a contending team on a reasonable budget, and then start boosting the payroll if the added revenue allows it.

Payroll matters when looking at teams in isolation, but if you’re looking to build a team that can contend on a regular basis, you usually want to keep your payroll low until after you’ve won something.

 

 

Is Ownership Cheap?

There seems to be a general sentiment growing among a portion of the fanbase that Rogers is a cheap ownership.  The thought seems to be that Toronto is a big market, and payroll has been below average (both true), ergo ownership is cheap.  This is exasperated by the comments made by Beeston that the team could handle a $120-M payroll when it makes sense to spend.  Given the availability of a big bat in Fielder, and the apparent lukewarm interest on the part of the Jays, it’s a logical conclusion to make.  But is it a fair assessment?

Now, I won’t get into the wisdom of Beeston mentioning a specific salary figure without a timeframe, and I’m going to assume that the lack of interest in Fielder is genuine (if they did plan on signing him, they’d use the same tactic; you don’t negotiate with Boras by showing him your open wallet and declaring publicly that you’ll do whatever it takes to sign his client).

I took a look at three factors: Team quality (ranked by winning percentage), fan support (ranked by attendance per game) and financial commitment (ranked by payroll).  While not perfect, these numbers do provide some insight.  Since Rogers took over the team (2001-present) the Jays have had an average rank of 8.1 in winning percentage, and 8.5 in payroll – overall they gotten what they’ve paid for, and a hair more – yet their average attendance rank has been 9.7.  That tells me that, while Rogers hasn’t broken the bank like individual owners sometimes do, their investment in the team has exceeded the fan support.  What’s also worth noting is that while the team has been average over that stretch, the attendance has lagged behind the quality of the team.  hmmm…

Maybe the lack of contending years has reduced the attendance below what you’d expect based on their winning percentage?  Let’s take a look at another large market team, also stuck in the AL East without any years of true contention since 2001: the Orioles.  They’ve been a lot worse than the Jays – average rank of 11.7, and almost 12 more losses per season than the Jays.  They’ve spent a little more, though in a similar spending range as the Jays, with an average rank of 7.9, and gotten a lot less for their dollar.  Their average attendance rank has been 7.5.  Even since Washington split their market in 2005 (which looks to have had a significant effect on attendance) the Orioles have managed to match the Jays attendance figures (a little over 25,000 per game) despite winning fewer games in their best season than the Jays did in their worst.  The Orioles’ attendance rank has been better than their winning percentage rank every single year.

If fans expect the team to spend like a big market, they need to behave like a big market.  That doesn’t mean selling out every game despite not being true contenders, but it does mean drawing in a fashion consistent with their performance.  It’s unreasonable to expect them to top the attendance lists without the product to match, but it’s not unreasonable to expect fan support to match the existing product before taking on high-end salary risks.

While Rogers isn’t the type of ownership that’ll operate at a loss for a championship, they’ve invested in the team at a rate that exceeds the commitment shown by the fans.  Are they risk averse?  Perhaps.  Eccentric billionaires treating their team like a toy?  Nope.  Excessively cheap?  Their track record doesn’t support the claim.

A Tale of Two Princes

With the Hot-Stove period well underway, there’s a lot of talk about Prince Fielder on the blogsphere.  A lot of Jays fans are clamoring for the Jays to sign the big man to a big contract, whereas the Jays brass have been vocal about their reluctance to offer anyone a guaranteed deal of more than five years.  There’s merit to both arguments – one one hand, long-term deals carry a lot of risk, and many have voiced concern about how Fielder’s girth will impact the way he ages.  On the other hand, Fielder’s young, with a track record of performance and durability, and fills a position of need – exactly the type of player who would make sense should Rogers open the bank and act like the big market team that they are.    So, should the Jays open the bank for Fielder?

Before answering that question, it’s worthwhile to look at two players:

Player A:  .268/.386/.489 (.875 OPS, 133 OPS+), 33 HR, 27 2B

Player B:  .299/.413/.584 (.998 OPS, 165 OPS+), 42 HR, 35 2B

If you assume that these two players have their entire value tied into their bats, the second is an elite player based on his bat alone, but what about the first?  He’s certainly a good hitter, and desirable to have, but he falls short of stardom.  Would you give Player A superstar-type money for most of a decade?  I sure wouldn’t.

We all know the drill here, where I reveal, shockingly, that these two guys are actually the same player!  In this case: Prince Fielder’s average season in 2008 and 2010, versus his average in 2009 and 2011.  Does this mean he’ll continue to fluctuate between good and great in the future? of course not.  But what it does mean is that we shouldn’t be so quick to pencil him in as a 1.000 OPS player going forward.  Where Fielder had little speed and is not a good defensive player – perhaps even a DH in the near future – he has to be one of the absolute best hitters int the league to justify the kind of deal he’s reportedly seeking.  If he sustains his 2011 level -which he may; he did improve his plate discipline – he might be worth the money, but if his talent level falls somewhere between the two –  say, .280/.395/.530 (closer to his career numbers) – then the transition from asset to albatross could come a lot sooner than people are expecting.

So which is it: is he a very good hitter who’s made the transition into a great one, or is he a very good hitter coming off a great year?

Unless you’re a scout, the honest answer is “I don’t know”.  And that’s where I take issue with the vitriol we see among some of the fan base on the subject.  In one scenario, you’re taking a reasonable risk that the player will sustain enough value over the course of his deal for the front end of the deal to make it worthwhile, but in the other, you’re limiting your payroll agility by signing a player who’s likely to become an albatross.

Now, please don’t take this as a slam on Fielder.  I’d love the see the Jays sign him – if his contract falls within reason of their evaluation of how he’s likely to perform.  And if they truly feel he’s an elite talent rather than simply a very good one, it would be nice to see Rogers open the bank to get him.  But make no mistake, this is not simply a matter of whether or not ownership is too cheap to sign him; it’s also a matter of player evaluation, both on his true level of talent (which isn’t clear due to the fluctuation in his numbers) and in terms of how they project him aging.  On that front, Anthopoulos and his team are working with far, far better information than the fan base.

Fans are by nature highly invested in the team, and I can’t blame the fan base for wanting to see a big move.  But, I do take issue with things like this silly petition that’s going around.  The fan base is not smarter than the GM.  You are not smarter than Alex Anthopoulos.  The fan base does not have a better understanding of what the current talent is capable of doing, nor is it better informed on player evaluations.  The fan base has no idea what alternatives are available on the trading block, or at what cost in talent.  By asking Anthopoulos to treat the team as a fan-based democracy (and yes, that’s what this petition is), you’re effectively saying that he should ignore the competitive advantage he gains from having a massive and highly acclaimed scouting staff in favor of the (often knee-jerk) opinions of the masses.

I want the Jays to win.  I do not want the team to feel pressured into making moves based on my opinions over that of their player evaluation staff.  And neither should you.

Player Profile: Jose Bautista

Perhaps the most surprising star of the 2010 season, Bautista heads into 2011 with a shiny new contract and a chance to prove 2011 was no fluke. While expectations vary wildly for the starting third baseman, it’s worth looking a little closer at Bautista’s career to get an idea of what to expect from him. I’ll be looking at a number of players on the Blue Jays in this manner, with Bautista as the first.

Bautista was a 20th round draft pick by the Pirates back in 2000. Over his first few minor league seasons, he showed occasional power (.169 ISO as a 21 year old in A ball, up to .181 the following year mostly at A+) but his biggest strength was probably his patience at the plate (over a 100 point spread between his BA and OBP those same two years.) The following year, the Orioles decided to take a chance on him in the Rule 5 draft in 2003. The next year he probably didn’t unpack his suitcase very often, as he was passed around unceremoniously from the Orioles to the then Devil Rays, then to the Royals, then the Mets (though he never played for them) and finally back to the Pirates, all within the span of about 2 months in 2003. Given his Rule 5 status, he was forced to spend the whole year in the Majors despite never having played above A+ and only having moderate success at that level. It was a wasted year, as he received little playing time and was over-matched when he did play.

That year does give us some clues to how he might have been perceived at the time. The fact that he was selected as a 23 year old in the Rule 5 draft despite clearly not being ready tells us that the Orioles must have seen something intriguing there. Given he was only fair even at A+ the previous year, it’s understandable that the Pirates left him unprotected, and the fact that they eventually traded back for him suggests that they liked his potential.

He spent most of the following season back in the minors, mainly at AA with a taste of AAA, where he started to show more power potential. He hit .280/.359/.490 between the two levels, with 24 HR and 30 2B in 130 games. He did little in his September call-up that year.

After about a month in AAA in 2006, Bautista got his first extended chance in MLB. He got regular playing time as a utility player over the next three years for the pirates, mostly at third and in the outfield, but really only approached everyday status through the 2007 season. He was traded to the Blue Jays in August of 2008.

At the time of the trade, Bautista seemed to have an established level of performance. He was 27 at the time, coming off three years of similar performance. While his offense was below average (.243/.330/.413) over those three years, he did show some moderate power (20 HR and 31 2B per 162 games) despite never hitting more than 16 HR in a given season.

Taken as a whole, his 2009 looks like more of the same – batting average around .240, slugging a bit over .400, and a decent number of walks – yet there are clues of a possible change as the season went on. His power surge of 2010 actually started in September 2009, when he hit .257/.339/.606 with 10 of his 13 HR.

Then, in 2010, he exploded, clubbing 54 HR, with career highs in BA, OBP, SLG, RBI, BB, and even SB.

Clearly, his performance was well above anything he’d done before, but how much of that performance is he likely to retain?

Now, there’s always a chance the year was a total fluke, and that he’ll fall back to his .240/.335/.415, 20 HR level of his previous years. There’s no reason to completely ignore his 2010, though, so what do his numbers look like if we include last year without giving it any special weight?

From the time he became a full-time MLB player, Bautista’s hit .246/.346/.465 (113 OPS+), with 28 HR per 162 games. That serves as a reasonable baseline for his performance. It’s a solid player still, if well shy of his career year.

However, it’s worth looking at 2010 in more detail, to see what kinds of changes there were in his performance beyond the raw totals.

The first thing that jumps out is a combination of a very high FB% (54.5%), and a very high HR/FB% (21.7%). Bautista was hitting more balls in the air than he’s ever done before, and more of those balls were carrying. Regression in both areas is likely, but by how much?

Since 2007, no player has sustained a FB% over 50%, so it’s unlikely that Bautista will. Bautista’s rate during that stretch is about 46%, which isn’t far off the most extreme flyball hitters (Soriano’s tops at 49%). While his mechanical changes may have impacted his flyball rates to an extent, when you include his 2010, he’s not far off the upper limit of where MLB hitters seem to find success as FB hitters. I’d expect he’ll be between 45% and 49%.

Surprisingly, his HR/FB% isn’t quite as extreme as his raw HR%. Since 2007, Ryan Howard and Jim Thome are the clear leaders in this category, with a ridiculous 27%. There are more players players with HR% between 20% and 23.5%, including Carlos Pena, Jack Cust, Adam Dunn, Alex Rodriguez, Prince Fielder, and Mark Reynolds. Next are serious hitters with major power like Cabrera, Pujols, Votto and Hamilton around 18-19%. Between 16% and 18%, the field starts opening up. Adrian Gonzalez, Ryan Braun, Mark Teixeira, Jason Werth, Lance Berkman, Jason Heyward, Brad Hawpe, David Ortiz, Paul Konerko, Jay Bruce, Kendry Morales, Nelson Cruz, Carlos Gonzalez. Next up between 15% and 16% includes Dan Uggla, Evan Longoria, Matt Holliday, Jermaine Dye, Adam Lind, Hunter Pence, Pat Burrell, and Tory Hunter. Bautista, with 2010 included, comes after this grouping.

So where should we expect Bautista to fall in? One thing we can look at is HR distances, to get an idea of what kind of raw power he generates.

I don’t want to look at averages (we don’t want to penalize a player for extra HR in friendly parks) so instead, I’ll look at the following 2010 numbers for some of the following:

• The longest HR
• The fifth longest HR
• The tenth longest HR
• The number of 400 foot HR
• Other tendencies

Jose Bautista, 2010: Long: 453 ft; fifth longest: 441ft; tenth longest: 430 ft; Number of 400: 33 400ft+ HR; Extreme pull hitter

Jose Bautista, 2007: Long: 427ft; fifth longest: 413ft; tenth longest: 393ft; Number of 400: 9; Extreme pull hitter

Ryan Howard, 2009 (2010 was a down year): Long: 473ft; fifth longest: 447ft; tenth longest: 432ft; Number of 400: 34; All fields

Ryan Howard, 2010: Long: 445ft; fifth longest: 432ft; tenth longest: 417ft; Number of 400: 19; all fields

Adam Dunn, 2010: Long: 473ft; fifth longest: 448ft; tenth longest: 430ft; Number of 400: 28; Mild pull tendencies

Mark Reynolds, 2009 (44 HR): Long: 471ft; fifth longest: 449ft; tenth longest: 443ft; Number of 400: 33; pull tendencies

Mark Reynolds, 2010 (32 HR): Long: 481ft; fifth longest: 448ft; tenth longest: 439ft; Number of 400: 24; moderate pull tendencies

Miguel Cabrera, 2010: Long: 468ft; fifth longest: 433ft; tenth longest: 416ft; Number of 400: 19; Mild pull tendencies

Albert Pujols, 2010: Long: 465ft; fifth longest: 443ft; tenth longest: 433ft; Number of 400: 36; Strong pull tendencies

Prince Fielder, 2010: Long: 444ft; fifth longest: 437ft; tenth longest: 424ft; Number of 400: 23; center/pull tendencies

Josh Hamilton, 2010: Long: 485ft; fifth longest: 444ft; tenth longest: 435ft; Number of 400: 26; Center tendencies

Jason Werth, 2010: Long: 448ft; fifth longest: 425ft; tenth longest: 412ft; Number of 400: 14; Mild pull tendencies

Paul Konerko, 2008 (22 HR): Long: 430ft; fifth longest: 414ft; tenth longest: 400ft; Number of 400: 13; Extreme pull tendencies

Paul Konerko, 2010 (39 HR): Long: 426ft; fifth longest: 410ft; tenth longest: 403ft; Number of 400: 13; Extreme pull tendencies

Dan Uggla, 2010: Long: 429ft; fifth longest: 411ft; tenth longest: 399ft; Number of 400: 9; Extreme pull hitter

Vernon Wells, 2009: Long: 449ft; fifth longest: 421ft; tenth longest: 395ft; Number of 400: 9; Extreme pull hitter

Vernon Wells, 2010 (31 HR): Long: 453ft; fifth longest: 422ft; tenth longest: 415ft; Number of 400: 18; Extreme pull tendencies

One thing that’s clear is that Bautista wasn’t fluking into HR in 2010; he was crushing the ball. Bautista’s raw distance in 2010 was much more comparable to the big sluggers as opposed to the more typical power hitters. One thing that’s also interesting is that the correlation between distance in a good power year versus a bad power year is often surprisingly weak. Reynolds and Konerko show no real difference here between their big power years and their off years, and for Wells, the difference only shows up on the low end.

Based on this data, it doesn’t seem unrealistic to think that he could be around 20% again, and it seems likely he’ll be at least in the 17-18% range going forward.

So, power-wise, I’m going to estimate a 47% flyball rate and a 17.5% HR rate in 2011, both above his career averages (it’s clear he’s a different hitter from in 2007) but both regressing significantly.

There’s more than just power here, however. Bautista’s BB rate was up, and his K rate was down last year. Neither is an extreme jump, but both are far enough from his established levels to suggest there’s some real improvement. His BB rate in particular started to climb in 2009, his first full year with the Jays. He could retain those skills, but it makes sense to regress him toward his career levels as pitchers may well adjust. I’m going to project a 22% K rate and a 13% BB rate, which falls somewhere in between his old and new levels.

At 640 PA (down from last year, as he started in the leadoff spot), I estimate that to give 427 fair balls, 200 of them flies, for an estimate of 35 HR. I also estimate 83 BB and 120 K.

What’s also notable about Bautista’s year, however, is the extremely low BABIP. As a flyball hitter, he’s always been on the low side, but last year’s .233 is extremely low. As noted above, he’s almost certainly going to lower his FB%, which is also likely to raise his BABIP. Using his career BA for flies, liners, and GB (not a great estimate due to his adjustments, but the best we have) I estimate a BABIP around .273, right around his career average.

All things considered, this is the estimate I come up with for Jose in 2011:
640 PA, 547 AB, 142 H, 32 2B, 3 3B, 35 HR, 83 BB, 120 K, 10 HBP, .260/.367/.522 (.889 OPS)

Note that while that estimate does assume that his breakout was real, it’s not a best case scenario. His raw power wasn’t out of place for a true 19% HR/FB hitter, and my estimates assumed that all the lost FB became GB rather than LD For a worst-case (barring injury) scenario, he could regress to his Pirates levels (perhaps he was temporarily replaced by a shape-shifting alien with super strength in 2010), but let’s look at a realistic low-end and high-end estimate based on the assumption that his change in ability was real:

Low end: (using a 45% FB%, 15% HR/FB%, 11% BB%, 25% K%)
640 PA, 560 AB, 135 H, 32 2B, 3 3B, 28 HR, 70 BB, 140 K, 10 HBP, .242/.337/.462 (.795 OPS)

High end (using a 48% FB%, 18% LD%, 19% HR/FB%, 15% BB%, 20% K%)
640 PA, 534 AB, 152 H, 34 2B, 3 3B, 39 HR, 96 BB, 107 K, 10 HBP, .284/.402/.577 (.979 OPS)

Note that these estimates don’t consider outlier seasons – he could get lucky or unlucky and end up with a .320 or .220 BABIP, for example, which would raise or lower these. What’s interesting about Bautista’s career year last year is that despite how much better it was than his established performance, it was not a case of everything breaking well. While he could certainly regress to roughly his career levels, there’s actually a non-trivial chance that he has as good a year as last year, even after we regress his power to more normal levels. If we assume his FB% will decrease, some of the flies could easily become LD rather than GB, raising his expected BABIP. Given the distance of his HR, he could certainly end up in the 19% range for true power. Given his terrific season, pitchers could pitch him more cautiously, leading to an increase in BB%. As surprising a season as last year was, this is not a player with nowhere to go but down. He is likely to regress in power, perhaps substantially, but he’s also likely to see gains in other areas. More likely than not, his overall level will regress in the balancing act, but it might not be as clear a drop as most people anticipate.

After looking more closely at his numbers, Jose Bautista’s new contract looks like a wise gambit on the part of Alex Anthopolous.

Hitting and Pitching

While the WAR scale is the same for pitchers and hitters, I will be treating the two separately for this particular exercise.  The main reason for this is the playing time adjustment.  For a hitter who plays almost every day, it’s relatively easy to adjust performance over different lengths of schedules and to treated missed time in a consistent way across eras, but for pitchers we’re also looking at changing usage patterns.  A pitcher in 1910 making 41 starts in 154 games is different from a pitcher in 2010 making 32 starts in 162 games.  Even more extreme of a difference is the enormous seasonal value accrued by 19th century pitchers who pitched upward of 600+ innings.  The usage pattern in the early days was so radically different that they tend to dominate any list that focuses on peak-value.  Their value increases even more so when you consider they played in a shorter season, thus making each win worth more toward a potential championship.

One common approach is to simply ignore players prior to 1900, since the game was so different, but I want to avoid that.  Another problem is that based purely on value metrics, the top position players of the early baseball era tend to be worth significantly less than their pitching counterparts.  This makes intuitive sense, since the starting pitchers usually have the most impact on any given game – if someone starts the majority of his team’s games, his impact can be profound.  The key will be finding a method to give these players credit for pitching a lot of quality innings, but to reduce the emphasis on volume of innings that come as a result of usage patterns.

The last thing to look at is hitting by pitchers.  There’s two different types of cases to consider here: the player who had a meaningful career as both a pitcher and a position player (e.g. Babe Ruth, Monte Ward) and the hitting ability of a pitcher.  One method would be to simply use the pitcher’s total WAR per season, including both his offensive and pitching contributions.  The issue I have with that is that most pitchers aren’t professional-caliber hitters.  It impacts the player’s value, certainly, but when discussing excellence, is it really important to emphasize that Koufax was a terrible hitter, while other pitchers who still wouldn’t have made AAA with their hitting skill at any other position get no penalty?  Similarly, should Randy Johnson be penalized for his offense during his NL years for being required to stand in the batter’s box, while receiving no adjustment for his AL years?

On the other hand, there are some pitchers who do make meaningful contributions with the bat.  Wes Ferrell, Red Ruffing, Bob Lemon, Mike Hampton – these guys created some real value with their ability to contribute on offense, and that should be counted when evaluating their careers.  That said, there’s still a problem with simply combining the pitching and hitting WAR.  If a pitcher hits well in a small sample of 100 AB, that might add a win or two to his value, but in a peak-focused system, that value will often be either muted or exaggerated based on the strength of his pitching that season.  If we’re looking at excellence, we want to know how good of a pitcher a player was and how good of a hitter, not how well his best small hitting samples align with his best pitching seasons.

My solution is to essentially treat pitchers as two separate entities: a pitcher, and a hitter playing the position of pitcher.  In most cases the latter will be negligible, but occasionally a pitcher will get extra credit for a bat.  This also creates a natural system for looking at combined pitcher/position players like Ruth.

Defining Excellence

One of the common debates in the Hall of Fame is the distinction between peak performance as compared to cumulative performance.  Put another way, we’re looking at a distinction between a player who was excellent versus one who accrued similar value by simply playing more.

 

The first thing to look at is a seasonal breakdown of WAR.

Let’s take a look at an example of two fictional 60 WAR players:

1. Player 1:    0, 1, 2, 2, 5, 8, 10, 10, 12, 10
2. Player 2:    2, 3, 3, 4, 4, 4, 5, 5, 4, 4, 3, 3, 3, 3, 3, 2, 2, 2, 1

The two players are equal in terms of value, but the shapes of their careers are different.  The first player is the Koufax model: a superior prime, but a short career with minimal value outside his great years.  The second is closer to the Ted Lyons model: a long career with a lot of solid years and a few very good ones, but nothing that comes close to the first player’s prime years.

 

Next, let’s look at two similarly valued seasons by a couple of contemporary first basemen:

1. Mark McGwire, 2000:  89 G,  .305/.483/.746,   32 HR,   4.5 WAR
2. Rafael Palmeiro, 2001:  160 G,  .273/.381/.563,   47 HR,   4.2 WAR

Palmeiro had the higher totals because he was healthier, but McGwire managed almost the same WAR because his performance on a per-game level was considerably higher.  On a value level it’s similar, but the shapes of the seasons were different.

 

Finally, let’s look at the offensive/defensive breakdown of some seasons:

1. Ozzie Smith, 1989:   3.2 oWAR,  3.1 dWAR
2. Dick Allen, 1967:  7.4 oWAR,  -1.5 dWAR
3. Mark Belanger, 1975:  0.2 oWAR, 3.3 dWAR
4. Joe Torre, 1971:  9.4 oWAR, -2.6 dWAR

When we break a player’s value into offense and defense, we accomplish two things.  The first is that we have a way of separating isolated excellence from total value.  It gives us a better understanding of a player’s strengths and weaknesses, rather than clumping everything together into one number.  The other thing it accomplishes, however, is that it’s a way to address the variance in defensive metrics.  Sometimes a player’s peak WAR seasons will appear higher or lower than expected because his best or worst defensive seasons will align unusually well or poorly with his best offensive years.

I want to leave a little bit of leeway in terms of how to define excellence, so I’ll be presenting three different approaches:

1. Compare a player’s seasonal WAR with the average player, and credit the player with gradually increasing value per point above the average
2. As above, but prorate the intervals of increasing value base on the playing time
3. Separate oWAR and dWAR, and credit the player with gradually increasing value in each as he separates himself from the average

The core element to all of these is that we’re looking only at performance that’s above the league average, and we’re favoring big seasons disproportionately.  With this method, there’s no difference between a player staying on as a fringe starter, hanging around as the worst player in the league, or choosing to retire.  The goal here is to evaluate the years in which a player made an impact, not to color his totals with years that are more representative of a choice in when to retire.

Developing a Method

How do you measure greatness?  The Baseball Hall of Fame is an institution built to try answering that question as it pertains to the game of baseball.  There have been lots of attempts at coming of with objective methods for comparing the top players, by such analysts as Bill James, Jay Jaffe, and many others.  One of the challenges for an objective measure for something like Hall of Fame worthiness, however, is that there’s by nature a subjective element to it.  Unlike a straight value metric, where the goal is to strip as much subjectivity out of the results as possible, an evaluation of a Hall of Fame case requires personal judgments on things like career value versus peak performance, how to treat career interruptions, how to weigh career highlights and postseason performance, and so on.  My goal in this series is to develop a framework to help weigh these factors.

The first step in this process will be to look at some of the issues that need to be addressed in developing this system.  How much weight should be put on brief excellence versus sustained effectiveness?  How should durability be factored in as compared to dominance?  Should offense and defense be addressed as two separate parts, or should the focus be on the total package?  There’s subjectivity involved in answering those questions, and one of my goals is to be able to show a range of outputs using the same data, in order to demonstrate how the core methodology can be tweaked to answer these questions from different angles.

One final note here is that this is not an attempt at building a superior value metric.  It’s not a value metric at all, but rather it’s an attempt at interpreting existing metrics for different purposes.  I will be using the WAR metrics on Baseball-Reference as a foundation, for three main reasons:

1. The data is easily accessible
2. Historical players are treated the same as modern players
3. The offensive and defensive breakdown of WAR is presented neatly

With that in mind, any flaws or limitations present in the baseline WAR will show up in my numbers as well.  With some tweaking to adjust for different scales or baselines, the framework I’m building can be applied just as easily to Win Shares, WARP, other variants of WAR, or any other value metric.  I’ll try to keep my discussions neutral of any metric, in the interest of modularity.  There’ll be some light number crunching here, but I’m more concerned with the theory than the specifics at the moment.

 

 

The Beacon

Welcome to the Baseball Beacon.  It’s a place where I’ll discuss my thoughts on the Blue Jays, the Hall of Fame, and whatever else I want to write about on the topic of baseball.