117 years ago, in response to an epidemic of infielders intentionally dropping popups to attempt double plays instead, the National League adopted the infield fly rule, and with some minor adjustments, the rule has survived to the present. Like many remedies from the 1800s, the intent- protecting the offense from chicanery- was good, but the implementation- calling their batter automatically out- was fraught with problems.

First, and most obviously in light of recent events, even when the defense can’t make the play, the rule intended to protect the offense punishes them by giving the defense the out anyway. Second, any time a fly ball can be intentionally dropped for a good shot at a double play, the offense should be protected from that, but because the play requires calling the batter automatically out, the rule as written can’t be invoked liberally. Third, and related to the second, the umpires have to make a judgment call based on the trajectory of the ball, the position of the fielder, environmental factors, and anything else they consider relevant to determining “ordinary effort”. That leads to late calls and inconsistent application.

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Searching for and appreciating the “Cinderella” team is a pervasive feature of American sports. Our love of the Cinderella might come from some uniquely American fascination with heroes rising from nothing, or from a basic human desire to recognize and value unexpected outcomes. Whatever the cause, we pay special attention to moments (the Miracle on Ice; the 1966 Texas Western basketball squad; the 1955 Dodgers or 1969 Miracle Mets or 2004 Boston Red Sox) where teams seemingly overachieved or overcame great adversity to come out champions.

Generally, there are three ways of thinking about Cinderellas:
1. A team winning after a long period of failure.
2. An objectively untalented team winning despite their flaws.
3. A team succeeding despite having the odds stacked against them, such as a talented team overcoming objectively more talented opponents.

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It’s been nine months since the trade that brought Ryan Theriot to St. Louis, and the shortstop picture for the Cardinals is no clearer today than it was then. With their playoff hopes all but officially extinct, the prospect of another offseason spent looking for up-the-middle help looms large.

The trio of players who have garnered playing time at short for the Cards this season have been unimpressive, producing a combined 0.4 WAR in approximately a season’s worth of plate appearances. Theriot is an obvious non-tender candidate, while newly acquired Rafael Furcal will almost certainly have his $12 million option declined and become a free agent at the end of the season. This leaves the Cards with only Tyler Greene as an internal option, and the free agent market for shortstops is about as thin (the obvious exception being Jose Reyes, who the Cardinals have almost no hope of signing if they expect to keep Chris Carpenter and/or Albert Pujols). While the Cardinals will likely either give Greene a shot to hold down the job, or pick up another bargain during the free agency period, I’d like to propose that the Cardinals consider a radical alternative that could provide the team with a definitive edge: Albert Pujols.

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This article was originally published on WahooBlues.com.

No one likes to travel. Vacations are great and changes of scenery can be nice, but that doesn’t make the cramped bus trip or the bumpy plane ride any more pleasant. The destination may be worth it, but when was the last time you stood up after an hours-long voyage with your good mood still fully intact?

This sentiment is shared even by multimillionaires who make their livings playing a children game and are cheered by thousands of adoring fans every time they go to the office. In baseball, “getaway day” is dreaded, and while jet lag alone wouldn’t make the Indians fall to the White Sox (who’d’ve thought that would be a good example this year?), a team that just got in after a long flight is seen as being at a real, if relatively small, disadvantage at the start of a series.

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This article was originally published on WahooBlues.com.

Everyone knows that money matters in baseball. I’m a Cleveland fan, so you don’t need to convince me that my small-market Indians are at an unfair disadvantage when competing against teams like the Yankees and the Bank of Steinbrenner (in the immortal words of Ken Tremendous, “It’s like Scrooge McDuck’s gold coin-filled pool”). There’s no question that franchises with the financial flexibility to retain their stars, import new ones, and remain contenders even when their well-paid players bust have a leg-up from the get-go.

But we all know that money isn’t everything. Omar Minaya and the New York Mets gave us a years-long crash course in what happens large payrolls are spent poorly. Meanwhile, plenty of underfunded teams have had success, including last year’s Rangers and the Rays of both 2008 and 2010. Check my facts on this, but I’m pretty sure one or two low-budget Oakland A’s teams have had some mild success in the past too.

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All major league sports division winners gain entry into the playoffs–the difference is HOW those division victors are determined. For example, the NFL places a greater weight on division record, so much so that a 8-8 division winner (like the 2010 Seahawks) is seeded higher than a wild card with a better record (like the 2010 New Orleans Saints). The NBA gives the top three seeds in each conference to the division winners, with winning the division based on overall instead of division record.

I was curious how baseball playoffs would be affected if a team’s division record determined the division winner, and I expected to see a handful of changes. I was VERY surprised with what I saw. Read the rest of this entry »

After reading an extremely interesting piece by Jeff Passan on the legendary sabermetrics whiz Voros McCracken I have to admit it had me a bit down in the dumps, and depressed.  How could the man who basically redefined the sabermetric movement not be involved in baseball in some form or fashion?  It doesn’t seem right, or fair, that the man who basically founded and created ‘defence independent pitching’ (or DIPS) statistics wasn’t good enough for the game anymore.

Maybe it affected me more on a personal level and it was gut check time, if ‘Voros’ wasn’t accepted and embraced by the baseball world, what chance in hell did I ever have?  Now is the time for you to snicker, or snidely remark ‘fat chance in the first place’ and, to be honest, I would be saying the exact same things.  But I have a confession, and on some level every fellow ‘baseball nerd’ who writes about the game we love was affected in the same manner – we lost a bit of hope.

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For the first time ever in the divisional era, 1 division has managed to run the table against the other two. Barring the Royals taking 3 of 4 from Tampa over the weekend, there won’t be a single team in the American League who will have put together a winning record against the AL East.

Since 2007, only 8 teams in the American league have been able to put together a winning record against the AL East, (LAA 3 times, OAK twice, TEX, DET and SEA once). This season, as things currently stand, the Central and West divisions have combined to go 149 – 198 (.429%) winning percentage against the AL East, a record comparable to the Cleveland Indians or the Washington Nationals.

What’s worse, is that the AL East will end again with the team that has either the worst, or second worst record in the American League (assuming Buck Showalter doesn’t phone it in this weekend), but looking deeper into their divisional performance, how bad exactly is the AL East’s punching bag?

(Record, Winning Percentage, % Diff from total)
2010 Orioles: Non-AL East Record (39-47*, .453, +.054), 4 games at home v. Detroit left
2009 Orioles: Non-AL East Record (40-50, .444, +.049)
2008 Orioles: Non-AL East Record (46-43, .516, +.095)

AVERAGE % Diff = +.066, or 10.7 Wins

And the 4th place Jays?

2010 Blue Jays: Non-AL East Record (43-43*, .500, -.019), 4 games in Minnesota left
2009 Blue Jays: Non-AL East Record (49-41, .544, +.081)
2008 Blue Jays: Non-AL East Record (49-41, .544, +.013)

AVERAGE % Diff = +.025, or 4 Wins

This means, on average, even the worst that the AL East has to offer, averages almost 5% points higher against non-divisional foes, or roughly 7 wins better across a 162 game season. How much are those 7 wins worth? If you’re Tampa, obviously zero since the only way to fill the ballpark there is to give away 20,000 tickets, but to a team like Seattle or Toronto (as highlighted above), the 2009 Jays managed 75 wins at 23,162 fans a game, whereas the 2008 version of 86 wins averaged 29,626. Obviously its a very rudimentary look at attendance and I’m ignoring plenty of factors, but the fact is and has always been that outside of Tampa Bay, people will inevitably jump on the bandwagons and go to see winning teams win ballgames. The point I’d like to be making here is the financial impact of regional divisional slotting, and if you take the leap with me, obviously the analysis will have a more profound impact.

For comparison purposes, lets look at the AL CENTRAL 4th and 5th place finishers

2010 Kansas City: Non-AL Central Record (36-50*, .418, +.007), 4 games at home v. Tampa left
2009 Kansas City: Non-AL Central Record (33-57, .367, -.034)
2008 Detroit: Non-AL Central Record (47-43*, .522, +.065), 13-5 in interleague games

2010 Cleveland: Non-AL Central Record (33-55, .389, -.039)
2009 Cleveland: Non-AL Central Record (33-55, .389, -.012)
2008 Kansas City: Non-AL Central Record (44-46*, .489, +.025). 13-5 in interleague games

AVERAGE % Diff = .002, or +.4 Wins

The 2008 figures are both skewed in the positive directions due to AL Central success during interleague play, getting to play the even weaker NL West in the majority of their IL games, and zero games against that division’s winner (84-78 Dodgers), so discounting those games, the result is:

AVERAGE % Diff = -.015 or -2.7 Wins

Does the AL East really cost a team 7-10 Wins a season like it has the Orioles? Probably not, there are plenty of other factors that go into a teams eventual W-L, but traditional Strength of Schedule metrics that value the winning % of your opponents, or Runs Scored/Runs Allowed Differentials often don’t capture the simple facts that your record and team stats will be positively influenced by facing the Royals 18 times a season. Who knows, maybe the 2010 Blue Jays, who lead the majors in slugging and home runs, could’ve competed this season in another division where its young pitching staff wasn’t exposed to the three highest scoring teams in the league (NY Boston Tampa) for 54 games? Under this current alignment, we can never be too sure.

On the positive, at least the divisions regionally make sense in their current form, unlike football. I’m sorry, putting Miami in the AFC EAST, Baltimore in the AFC NORTH, and Indianapolis is in the AFC SOUTH makes about as much sense as the BCS national championship formula.

A few weeks ago, Sportvision hosted the 3rd Annual Pitchf/x Summit.  Sportvision is the company behind the Pitchf/x system and has initiated Fieldf/x, which I’ll get into in a minute.  The goal of the summit was to share some of the research being done in baseball analysis, while also serving to explain the possibilities that exist with the new system.  Without further ado, here were the presentations:

Using Velocity Components to Evaluate Pitch Effectiveness (Matt Lentzner/Mike Fast): The purpose of this study was to change the reference point by which Pitchf/x data are measured.  Often, fastballs show more movement than breaking balls, but without the proper frame of reference, it means nothing.  Mike and Matt were able to demonstrate how to determine the horizontal and vertical velocities with respect to the batter’s eye and make the Pitchf/x data more meaningful.

Pitchf/x Application in Player Development and Evaluation (Dr. Glenn “Butch” Schoenhals): Dr. Schoenhals has a Pitchf/x system set up at his instructional school, which allows pupils (including some major leaguers) to see the their pitches broken down immediately and make adjustments.  In conjunction with three cameras set up around the pitcher, the Pitchf/x data provide benefit to both pitchers and instructors in learning/teaching how to pitch.

Okajima’s Mystery Pitch (Matt Lentzner): Hideki Okajima throws a pitch roughly 20% of the time that had previously been classified as a curveball, more specifically a “rainbow curveball.”  Actually, it didn’t really fit any of the known pitch types.  Using his research on pitch types and arm slots (“The Pitching Peanut”), we see that this pitch has almost no break, is faster than a curveball but slower than a slider, and falls at the exact center of the peanut.  His explanation: Okajima is the Boston pitcher who is actually throwing the gyroball, not his more famous teammate Daisuke Matsuzaka.

Leaving the No-Spin Zone (Alan Nathan): Dr. Nathan showed his experiments that relate the spin of the baseball just before and just after it is hit. The result? The two are almost totally independent of each other! I couldn’t believe that, but Dr. Nathan made a lot of sense.  This was a high-grade physics lesson, crashed into about 20 minutes.  He explained why balls tend to curve toward the foul lines; he showed that the bat actually “grips” the ball for a few nanoseconds or so before the ball explodes off the bat, which contrasts the earlier model of the ball “rolling” off the bat.  Really, really cool.

Fieldf/x System Overview (Vidya Elangovan): And the main event began.  Fieldf/x is a new tracking system that utilizes cameras attached to the light standards in baseball stadiums (for now, just AT&T Park) to track the movement of every person on the field 15 TIMES A SECOND.  As soon as I heard that, my mind started going crazy and I don’t think I paid attention for about 5 minutes.  The only issue at the time is that the system does not include the ball (but it will).  All ball events currently have to be added by someone watching the video.  The following presentations showed some of the things you can actually do with the data, and it’s fairly obvious that these data, particularly when connected to batted ball data through the Hitf/x database, are about to revolutionize how baseball players are evaluated.

Infield Defense with Fieldf/x (John Walsh): Actually the first presentation, thanks to being in Italy, (tough life), but it really would have been more helpful after the overview.  Either way, a lot of cool stuff.  First thing he said was that in tracking the different players, he noticed that an average centerfielder runs 8 miles per game, which stunned me and kept my attention.  Thanks to these new data, we can also see the effects of shifts and also what players away from the ball are doing while teammates are attempting to make plays.  Other questions John poses: can we see infielders cheating in a certain direction as the pitchers throws the ball? Do infielders lean in a certain direction before the pitch? Based on his initial investigations, he saw that third basemen step toward the line as the pitch is delivered and shortstops step directly at home plate.  Weird, but potentially important, and just a peak into what can be obtained.

From Raw Data to Analytical Database (Peter Jensen): As a baseball nerd and a programming dork, this was really cool.  Peter Jensen took the 400,000 lines of code that results from each game and wrote a macro to display what actually happened in the game in an Excel worksheet.  The simulation relates the position of each player as well as an approximation of where the ball is throughout the play.  His solution with regards to the reorganization of the data was very impressive for a first run, and it is absolutely vital to make the data useful for analysis.

Using Fieldf/x to Assess Fielders’ Routes to Fly Balls (Dave Allen): These next three were absolutely incredible to me (and I’m sure the last three would have joined them had I had the time to stay).  By using the data to reconstruct fielders’ routes to the ball, Allen surmises that the Fieldf/x data can be used to determine the speed of an outfielder as they pursue a ball, the starting points of each fielder at the time of the pitch (and hit), and how efficient each player is in getting to the ball (measuring the distance traveled against the shortest distance to the ball).  To me, this is something that teams can use to help players they already have by addressing alignment issues or noticing what is happening during the different points of pursuit.  Are outfielders getting good reads/jumps on the ball?  Are they running in straight lines or weaving?  Simply put, the data can confirm for us (and also measure exactly and more efficiently) what our eyes (and scouts’ eyes) have seen.

Measuring Base Running with Fieldf/x (Mike Fast): Mike’s presentation examined the different portions of base running and what the data can be used for.  Mike was able to track each base runner’s path around the bases, even what they were doing on pitches that weren’t hit (during which we would typically say “nothing happened”).  Obviously, with all of these data, there’s a lot happening.  Also, by knowing the position of the player at each moment in time, we can track both his speed and acceleration as rounds the bases; very valuable information for measuring “baseball speed.”

Fieldf/x of Probabilities: Converting Time and Distance into Outs (Jeremy Greenhouse): The coolest of the presentations.  As soon as he said the words “probability model,” I was sold.  Jeremy first examined stolen base attempts (in the thirteen games of data released, he only found four) and tried to determine the different component times of the stolen base attempt.  Some things he brought up that were interesting: “Pop” times, or the time it takes a catcher to catch the ball and get it to second base, was between 2.0 and 2.2 seconds for all attempts, which suggests that a lot of stolen bases are taken off pitchers, not catchers.  The ability to get a good lead is now measurable, as well as the jump a runner gets on the pitcher.

Jeremy also developed a model to determine the probability that a player makes a play on a ball hit near him.  The model was based on where the player is, where the ball would come down, and how long it would take the ball to get there.  From there, the player’s probability can change based on his jump, route, speed, and what I called “catching ability,” or the ability to actually make a play on the ball when in the vicinity.  It was shocking to see some of the plays made where players started out with low (less than 10 percent) chances of catching the ball, but by getting a good jump and running (quickly) in a straight line toward the ball, their probability would increase each 1/15 of a second.  He then showed the video of these plays and we were able to see the spectacular catches made by really good outfielders.  This also applies to outfielders who start with a low probability to make the catch, but increase it as they, for example, chase a ball into the gap, close quickly on it, but don’t catch it.  The ability to increase the probability of a catch is very valuable and that knowledge would be immensely valuable to teams.  Lastly, he also showed how bad outfielders can turn outs into hits by reading the ball poorly, getting bad jumps, and being indecisive.  Super cool, and as soon as the presentations are made available online (which hopefully will be soon), I will link to some of them, but especially some of these graphs.

Unfortunately, I missed the following presentations, so I will just show the abstracts presented in the program.

Where Fielders Field: Spatial and Time Considerations (Matt Thomas): Continued application of close-range photogrammetry through high-resolution digital photography to baseball is revealing hitherto unseen patterns of fielding in the game. Matt examines these patterns and where data permit, factors time into this examination. After reviewing general trends he notes specific achievements and then speculates on whether any of this freshly quantified insight tells us what makes for good (and not so good) fielding.

Scoutf/x (Max Marchi): This presentation evaluates players’ tools with Pitchf/x, Hitf/x, and Fieldf/x.

True Defensive Range (TDR): Getting out of the Zone (Greg Rybarczyk): Greg intends to display detailed tracking of the 25 batted balls in the released data that were hit in the air to the outfield. Presented data will include the relative positions of the outfielders and the ball from the time the ball leaves the bat until the time it is retrieved by the fielder. Using the essential elements of this data (fielder starting position, ball hang time and landing point), he outlines the fundamentals of a new outfield defensive metric, called ‘True Defensive Range’ or TDR, which should provide more accurate player defensive ratings with a smaller required sample size than current metrics. Full realization of this metric will require establishment of baseline values using the full data set. TDR for infielders will employ a similar method, but it will not be covered during this presentation.

The Future of Sportvision’s Data Collection (Greg Moore): Greg will talk about several bits of baseball data that Sportvision might collect in the future, and he will discuss how the data can be used in conjunction with Pitchf/x, Hitf/x, and Fieldf/x. Greg will also conclude the 2010 Pitchf/x Summit with closing remarks.

Obviously, there was a lot of cool stuff presented.  As mentioned, only 13 games worth of data were released to the analysts and most of the presentations were about determining what could be done with the data.  But with enough work and research, it will not only change the way teams and analysts evaluate players, but also will give teams another tool with which to teach their players and improve the guys they already have on the roster.  We’ll also know exactly what skills are important in each aspect of the game (base running, fielding, etc.), and as we learn these things we’ll discover other things we want to know.  I’d love to know what you guys think of all this and I’ll try to answer any questions you have about what can and can’t be measured and how we’ll use it in the future.

UPDATE: After I wrote this mess, I discovered this, much cleaner, detailed, mess, written by Baseball Prospectus writer Ben Lindbergh.  I’ll link to it down here because I want you to read what I wrote instead of Ben’s running diary.  Sorry, Ben.

This article was originally published at Knuckleballs, written by Dan Hennessey.

Reading Joe Posnanski’s latest piece about the struggles of the Royals, in which he opines about the fact that they’re a bad offensive team despite leading the league in batting average and showing no desire to promote two of their more intriguing young players (Alex Gordon and Kila Ka’aihue), I kept being struck with two pervading thoughts: (a) it must be terrible to be a fan of the Royals and (b) why would anyone do it?

Posnanski, of course, has become something of a darling in the sabermetric world not only for his excellent and insightful writing but for his acceptance and use of some of the more involved stats that we use to measure ballplayers. As such, he’s able to look past the fact that his Royals are taking pride in leading the league in hitting and have no interest in advancing beyond using batting average to measure players. Walks to them are res non grata, Posnanski argues, and he does so in the sort of tone that suggests that he has come to believe that there is no hope for change on the horizon. Which, you know, as long as Dayton Moore’s in charge, that does seem to be the case. But in any event, that’s really what made me wonder why Posnanski – and the other fans of the (disproportionately well-represented on the internet) Royals – keep following a team that gives them nothing in return.

Now, I suppose that on the surface, it makes sense: you root for the team you root for, and if you don’t root for the team that you grew up near, then you’re destined to be labeled a fair-weather fan. Such is life. But, perhaps because I adopted the Braves as my favorite team when they were on TBS every day and the Cubs were terrible, I don’t understand why that has to the case. See, sports is entertainment; we watch them because we enjoy the athletic splendor and all, but mostly because we are entertained by our favorite players going out there and plying their trade – because it’s fun.

If I had my copy of FreeDarko’s Macrophenomenal Pro Basketball Almanac with me, I’d quote here from their bit about liberated fandom. As it is, though, there is this post (first two paragraphs being of especial relevance) that will have to suffice for the moment; essentially, it argues for the eschewing of The Home Team in favor of the players that we actually enjoy watching. Are you a Cubs fan, but can’t stand watching a team put runners on third base with fewer than two outs in the 9^th 10^th and 11^th innings and not score them even though come on just hit a freaking sacrifice fly or at the very least try a suicide squeeze*? Don’t concern yourself with it; soak in the good times to be had in watching Carl Crawford steal bases or Vladimir Guerrero defy age or…oh, boy…or Albert Pujols beat down the doors to Cooperstown.

*I petitioned for this to happen in each of the three aforementioned innings. People say the triple is the most exciting play in baseball. People are wrong. The brief burst of drama and immediacy that a squeeze provides is unlike anything else in baseball. And it’s not for only that reason that I don’t understand why we don’t see more suicide squeezes, but also because it seems a really easy way to get a run, no? As long as bat hits ball, your chances of scoring a run are far higher than if you’re just letting the guy at the plate hit.

Two things: (1) Outs are almost always the dominant outcome of any game. Teams simply don’t put 27 men on base very often; they will always make enough outs (sometimes as few as 12; far more often 27) to finish a game. (2) Don’t think of batting average relativistically. Viz., think of them as percentages, not in the context of your baseball experience. A .330 hitter sounds like he’s really good at hitting…but ultimately, it means that he’s been getting hits in one-third of his at-bats and making outs nearly 70% of the time. If you’ve a guy on the team hitting .501, then, sure, let him swing away. But hits simply do not happen all that frequently; bunting is a much easier way to put the ball in play.

That’s the kind of suggestion I can make nowadays, what with the availability of MLB.tv and the internet making it easy to follow any team. During the World Cup – and immediately after – people loved to talk about how this would be the World Cup that got people into soccer. Now, they say this after nearly every Cup where the USMNT doesn’t get totally embarrassed, but this one was Different because we have the Internet and can keep track of our Nation’s Heroes as they play for Club Teams over in Foreign Lands. Similarly, though infinitely more effectively, people can follow any baseball team, or any selection of players, that they choose. At the risk of sounding like a shill for MLB, MLB.tv has a feature where you can select any player in the league, and they’ll alert you when he comes up to bat or in to pitch. I myself follow guys like B.J. Upton, Jay Bruce, Ichiro, Matt Wieters, Colby Rasmus and Pablo Sandoval that I wouldn’t be able to see otherwise – guys whose careers I enjoy more than, say, Melky Cabrera’s*.

*This is perhaps the wrong time for me to be writing this article, because this Braves team is probably the most enjoyable one to watch since Andruw Jones and the Baby Braves ruled the roost. Cabrera and Eric Hinske were the only two guys I could think to speak of derisively and I don’t hold any particular grudge against them. I guess Derek Lowe isn’t all that fun, but it doesn’t seem fair to pick on pitchers.

So why shouldn’t I just declare myself a fan of baseball, rather than the Braves? Everyone knows that Seinfeld bit about how having a favorite sports team is like rooting for laundry; what makes the Braves’ laundry so compelling that I should forego the pleasure of watching Jose Reyes and Hanley Ramirez and Chase Utley and Stephen Strasburg? I imagine the answer to this question is ‘it just is,’ or some similarly vague and far-reaching statement. Perhaps the tribal nature of fandom is so engrained in sports fans’ minds that there’s no turning away from it; perhaps people think there is a greater reward to be gleaned from “suffering”* through a team’s ups-and-downs and winning a championship.

*Y’know, for all the good there is in sports, it sure is a bastion of hyperbole. People love to throw around how Cleveland fans have “suffered” because they haven’t had a team in their city win a title in so long, and don’t have any real prospects of doing so in the near future. With the culture of superlatives that dominate sports, is it any wonder that Dwyane Wade dropped his 9/11 line? I’m going to stop there because the only thing more grating than that hyperbole is the moralizing and holier-than-thou attitude inherent in telling people that they’re not feeling real pain, and turn on the news if you want to see tragedy.

I don’t like that view. Sports isn’t life; sports is a diversion from life – it’s a forum for unparalleled conflict resolution (winners, losers, champions, meticulous documentation and quantified performance) and enjoyment of things we don’t see in everyday life (e.g. 450-foot home runs and diving catches and walkoff celebrations*).

*Though I do think this could (and should!) be brought into offices and schools. Say you just gave a really great presentation; you could have the audience cheering throughout your conclusion and hitting a crescendo as you nail the last syllable of ‘thank you,’ and then they vault over their tables and mob you and everyone jumps around. You could even rig the projector to drop company-color confetti. If this were commonplace I’d almost be excited to graduate soon.

So why do we arbitrarily bring unpleasantness into the equation? Why do we self-identify as fans of a team of guys that we may not like? Why do stat-minded guys like Rany Jazayerli and Rob Neyer and Joe Posnanski put themselves through the drudgery of a Royals team that couldn’t be more antithetical to their baseballing values? It is an inherently jingoistic, paleolithic process, a throwback to the days when the United States was a name and not a realized concept. I do think that there is a place for fandom in sports; I would argue that the incredibly fluid player movement in the NFL leaves fans rooting for teams as the only constants in a league of flux, and that watching a game where you don’t care for (or actively dislike) both teams is painful. But, with all due credit to those exceptions, I do not think that we need to subvert our enjoyment of sports and call ourselves ‘fans’ of a team. We don’t need to slog through inning after inning of uninspired baseball that’s not played to our liking when there are so many options out there. We can cast off the shackles of supporting a last place team and enjoy watching whomever fits our fancy; we can, or indeed should, be a fan of the game without being a fan of a team.