Tag Archives: baseball

MLB Playoff Review

Even though the World Series entrants haven’t been determined yet, two things have become clear:

1. You must root for the AL team, which is going to be the Kansas City Royals.

2. I’ve gotten everything wrong. Seriously, every pick I made in my playoff prediction has been the opposite of true. In fact, I didn’t pick a single League Championship Series team correctly. – none of the final four. That’s actually just as difficult to do as getting everything right, so I’ll take some solace in that, and the fact that I didn’t bet on any of this.

MLB Playoff Preview & Predictions

Still very busy, so this is going to be quick. Just want to get it on the record.

AL Wild Card Game
A’s over Royals. The regular season struggles of the A’s won’t matter tonight.

NL Wild Card Game
Pirates over Giants. Pirates have an edge of offense that should settle this in the middle innings.

Tigers over Orioles. Had the Orioles not lost most of their infield…
Angels over A’s. Regular season replays itself.

Dodgers over Cardinals. I’m stupidly betting against the Cards in the postseason.
Nationals over Pirates. Wouldn’t be stunned if Pirates pulled this out, but pitching makes the difference.

Angels over Tigers. Tigers’ bullpen issues will haunt them here.

Dodgers over Nationals. Nationals have no bullpen issues, but they will because it’s the postseason and that’s what they do.

World Series
Dodgers over Angels. In the “Los Angeles” series, the slightly richer team wins.


Slow posting these last couple of days as a result of plentiful World Cup games to watch, a flurry of important Supreme Court decisions to wade through, and that full-time job I have. I’ll have a review of the WC group stage tomorrow and new knockout stage predictions on Saturday, but in the meantime, a few thoughts on miscellaneous topics from the past few days:

  • It’s been extremely pleasant to watch soccer culture grow stronger in the US by the day, even if a certain shrieking witch thinks otherwise. (I do not link to trolls.) I’m more reserved than the average American about US potential in the short term, but there’s something pleasant about universal joy and pain in a relatively harmless endeavor. I’ve written in this space before that there are plenty of reasons to dislike organized sports, and FIFA is a major reason why, but if I had to choose, I’d prefer the US be united by Fabian Johnson than by bombing campaigns abroad.
  • Relatedly, “guy famous for biting opponents bites an opponent” was a real story this week, so that’s something we all have to live with now.
  • I haven’t commented on the ongoing IRS email scandal (in short, a top IRS official claims her email relevant to the IRS’s targeting of conservative groups was lost in a computer crash days after an investigation into that began) because it’s still early, and because it’s unlikely we can ever definitively know many things I’d need to know before making judgments. Obviously it’s possible that this is an innocent mistake, made possible by the government’s awful IT policies, and it’s also possible that it was staged to avoid some embarrassing emails from emerging. What you believe probably has more to do with whom you voted for in 2012 than the evidence, so I won’t get into it. I do like that the country seems to be noticing the hypocrisy involved – the IRS wouldn’t let anyone get away with a story like that – and perhaps the abuse of the office for political purposes will make more people realize that we shouldn’t entrust a whole lot of power to these agencies.
  • There was a massive downward revision to the first-quarter US GDP estimate, and everyone is revising what it all means. All you need to know is that everyone was right initially and everyone is right now.
  • Can’t forget to congratulate my Vanderbilt Commodores for winning the NCAA baseball championship (which I refuse to call the World Series). Great accomplishment for a great school.

Neyer On Pitcher Injuries

Rob Neyer writes:

Another thing: We know elbow ligaments seem to be shearing off like never before. But as I (and others) have mentioned, we’€™re seeing fewer serious shoulder injuries (or at least we seem to be). Would we see more shoulder injuries with higher pitch limits? Maybe. We might also see more shoulder injuries with old-school strength-and-conditioning methods, which falls (granted, loosely) under the heading of sabermetrics (the search for objective knowledge about baseball, including knowledge about strengthening shoulders with exercise).

The article goes on to, basically, state my theory posted yesterday: pitch count limits and rest protect shoulders, but encourage velocity which shreds elbow ligaments. I have no other point here except that my ego is now slightly bigger.

Have a nice day.

Pitcher Injuries And Baseball’s Peltzman Effect

Miami Marlins young ace Jose Fernandez will have to undergo season-ending elbow surgery soon, tanking both the Marlins’ season as well as one of my fantasy teams. He’s hardly the only one:

Jose Fernandez will be the 19th major leaguer to undergo Tommy John surgery (and it appears as if the Rangers’ Martin Perez may become the 20th). Only one season — 2012, when 35 pitchers had the surgery — has seen more surgeries and we’re still in May. The average age of the pitchers is 27. Seven of the pitchers had their second TJ operation.

The reaction seemed to center on two theories for the rash of injuries: Guys are throwing harder than ever and all the games and innings pitched in youth leagues and travel ball are helping to lead to these breakdowns.

Neil Paine at FiveThirtyEight summarizes the history of attempts to protect pitchers, addressing the two theories above (velocity and year-round pitching) and many others that have been floated over the years. His conclusion is, basically, that we still don’t know enough to protect pitchers, although limiting pitch counts, mandating rest, and capping total innings seem to help. Meanwhile, Blog-favorite Rob Neyer finds that it’s in everyone’s interest for young pitchers to throw as hard as possible even if it leads to a lost season following elbow surgery. Prospects want to get drafted and paid, so they throw hard; teams want hard-throwing pitchers, even at the cost of losing them for a year.

Major league pitcher Brandon McCarthy complicates matters a bit, pointing out that shoulder injuries seem to be down:

BMC Tweets

I don’t have the numbers handy to check if McCarthy’s impression of decreasing shoulder injuries is true, although as a fan of the sport I’m inclined to agree. This leads me to propose the following set of ideas, each supported by some evidence. I don’t have the time to gather the data to confirm any of them, so I leave that to an enterprising fan who wants to get a job with an MLB team.

  1. While total pitcher injuries may or may not be on the rise, catastrophic elbow injuries are up and catastrophic shoulder injuries are down.
  2. Teams have tried protecting pitchers by limit the number of pitches thrown per outing, providing enough rest, and capping innings.
  3. Shoulder injuries are caused (in part) by pitching while fatigued, especially throwing too many pitches in an outing and pitching on short rest.
  4. Elbow injuries, particularly ligament tears requiring Tommy John surgery, are caused (in part) by pitching at higher velocities, since human ligaments can only endure so much.
  5. By limiting the number of pitchers per outing, providing rest between outings, and capping innings, teams incentivize pitchers to throw harder when they’re pitching.

This could be baseball’s version of the Peltzman effect: protecting pitchers gives them an incentive to throw harder, much like building safer cars encourages people to drive more recklessly. If this hypothesis is true and plays some part in the rise of catastrophic elbow injuries, I’m not sure there’s much anyone can do to fix it. As Rob Neyer said, the current system seems to work out for everyone involved. If the rise of elbow injuries is caused by throwing harder and protecting pitchers from shoulder injuries, perhaps this is the long-run equilibrium that works out best for everyone.

Except for the 2014 edition of Villars Of The Earth.

Messing With Taxes – Baseball Contracts And Local Taxes – Updated

UPDATE, 2013-12-23, 3:02 pm: Accountant Robert Raiola, expert in athlete and entertainment  accounting matters, said on Twitter that Choo’s cash flow would be $700K lower in NYC than Texas. I followed up with him, and he explained that Choo would not pay NYC income taxes unless he were an NYC resident. Presumably Choo won’t be, to minimize his tax incidence. Thus, I need to add another assumption, which is that Choo would become an NYC resident. Raiola also adjusted for jock taxes, which I did not, as mentioned below. I’m sure I also missed several deductions and tax sheltering strategies that might apply in NYC, so read with appropriate skepticism.

Former Cleveland Indian Shin-Soo Choo agreed to a 7-year, $130 million deal with the Texas Rangers this week, after allegedly rejecting a 7-year, $140 million contract offer from the New York Yankees. This prompted blog-favorite Indians blogger Kevin Dean to tweet:
KIBI TweetI was among several people to point out to him that after taxes, Choo likely gets more cash in Texas than in NYC, and he acknowledged that he wasn’t thinking about that aspect. Curious fella that I am, I went ahead and ran the numbers for the life of Choo’s contract to see how big the difference is. I’m hardly the first to mention taxes in relation to sports – it was a big deal during LeBron James’s free agency, and there is some evidence that lower state-level taxes correlate with team success in salary-capped leagues. Obviously salary cap is not an issue in baseball, so I’ll just stick with Choo to see what would have happened had he signed in NYC instead.

0. The NYC contract would be for 7 years, $140,000,000. The Texas contract is for 7 years, $130,000,000. In each case the salary is divided equally over the seven years.
1. We’re ignoring inflation or discount rates. A fair assumption, probably, since inflation is likely to be similar nationally, and whatever discount rate we use will be the same in both markets.
2. Choo pays for his housing in cash from previous earnings, so we don’t have to discuss the mortgage interest deduction. It’s unlikely to make much of a difference, considering assumption #3. In addition, housing prices in NYC are approximately 142% higher than in Dallas, but we’ll round that down to 100% to account for various uncertainties. Thus, Choo pays $1 million for housing in NYC, and $500K in Dallas. Low estimates, perhaps, but changing that number barely matters in the end.
3. To give NYC every benefit of the doubt, the house price in NYC is assumed not to change through the value of the contract (to keep property taxes low) while the Dallas market will continue to appreciate at the rate of 16.5%, as it has over the past seven years. We won’t, however, give Choo the benefit of this appreciation at the end of the contract, so he can’t resell at the higher price.
4. Similarly, Choo’s Dallas property tax rate will be the highest (3.01) in the Dallas area, regardless of whether someone like Choo is likely to live there.
5. NYC property taxes have gone up 3 percentage points over the last seven years, but I’ll assume they stay frozen over the life of the contract.
6. All other tax rates are also held constant for the duration of the contract.
7. Choo’s expenses subject to sales tax are $1 million in NYC, and approximately $750K in Dallas, based on the price level differences in grocery, restaurants, and consumer prices between the two. (This actually favors Dallas despite its higher sales tax rate, but the difference is very small so I’ll leave it in for accuracy.)
8. Choo is presumed to be a married taxpayer, filing jointly, with deductions of $1 million for the purposes of federal taxes and maxing out his tax-advantaged retirement contributions at $16,500. This was calculated here.
9. For simplicity, we’re ignoring “jock” taxes for games played on the road, although given the team schedules, this would likely further benefit Texas.
10. To preempt certain people: I understand that New York is different from Dallas, and in your mind New York is more expensive because it’s so much better and everyone should want to live there, and if they don’t it’s because they’re too weak to handle it. I’m sure you’re right, but I hereby stipulate that Choo doesn’t care and just want to max out his income.
11. The taxes used to calculate  state-level tax liabilities, gathered from various sources online, are listed here:

  NYC Dallas
State 8.82% 0.00%
City 3.876% 0.00%
Property 1.15% 3.01%
Sales 8.75% 8.25%


As predicted, even with a $10 million difference in total contract value, Choo comes out way ahead in the Texas deal, in terms of cash. The magnitude of the difference, however, is stunning. I’ve posted the whole Excel Worksheet I used to calculate here, but this is the executive summary:

NYC Dallas, TX
Contract Value $140,000,000.00 $130,000,000.00
Cash remaining $67,638,461.80 $79,578,932.51
Taxes paid $72,361,538.20 $50,421,067.49
Tax Share 51.69% 38.79%

Playing in New York, Choo ends up paying more than half his contract in taxes, so that the lower Texas contract actually nets him nearly $12 million (!) in disposable income. Said differently, had Choo signed the same 7/130 contract with the Yankees, he would have lost nearly $16 million. To have the same cash left over as he would in Texas, Choo would have to get nearly $154 million from the Yankees.

Taxes take Choo’s annual salary in New York from $20 million down to approximately $8.3 million, while Texas taxes drop it from $18.6 million to $11.4 million. I should note that Choo’s biggest annual tax liability are the $7.7/$7.1 million (NY/TX) in federal taxes, rather than any state-level levies. However, New York adds approximately $4 million on top of federal taxes, mostly in state income taxes, while Texas adds almost nothing except property taxes. Obviously a lot more goes into choosing a destination for free agents than money, but I bet you this is part of the Rangers’ and Astros’ pitch when they meet with players and their agents.

One final note: while taxes differ between New York and Texas, death is inevitable in both jurisdictions.

Causes Of And Solutions To Grade Inflation, Part 2

In my last post, I posited some explanations for grade inflation at elite colleges in recent years and decades, and mentioned that this poses an information problem for employers and graduate schools. There are other costs as well: it drives students to take easier classes rather than better classes, making students less productive than they otherwise would have been. It’s hard to calculate what these costs are, but it’s safe to say that this is a bad thing.

Here, I propose a simple solution that addresses both the information problem and the selection problem. It’s based on several stats that are used in baseball analysis to compare players from different eras.

Within-School Inflation

I ‘ll use as an example a statistic called OPS+, though virtually any stat in baseball can be adjusted this way. OPS is a stat that combies two other stats, On-Base Percentage (OBP) and Slugging Percentage (SLG). (Yes, it adds unlike quantities. Deal with it.). This stat is designed to measure offensive production by batters. Because offense varies over time, comparing players from different eras can’t be done straight up. Steroid era stats don’t compare to dead ball era stats in any meaningful way: league-average OBP was .345 at the peak of the former and under .300 at the bottom of the latter. To compare two, eras, OPS+ compares a player’s percentages to the league averages and then creates an index that lets you compare players from different eras, with 100 indicating “league average” and higher numbers indicating better seasons. The formula is this:

OPS+ = 100 x (OBP/lgOBP+SLG/lgSLG-1)
(where lgOBP and lgSLG indicate league average for the statistic)

This translates well to calculating GPAs for people who took different classes (for now, let’s stay within the same college.) For a particular student who took classes 1 and 2, the formula would be:

GPA+ = 100 x [(GP1/clGPA1+GP2/clGPA2)/(number of classes)]
(where clGPA1 and clGPA2 indicate class average values in classes 1 and 2)(we also have to adjust for the fact that these aren’t rate stats, hence the difference)

Let’s say the student got a B in each class. His GPA would be 3.0. His GPA+, however, would depend on what grades other people in the same classes received. If the average grade in each class was a C, then:

GPA+ = 100 x [(3.0/2.0+3.0/2.0)/2] = 150

This tells us that the student did 50% better than the average students in two hard clases. Comparatively, if the average grade were a Harvard A-:

GPA+ = 100 x [(3.0/3.7+3.0/3.7)/2] = 81

In this case, the student did 19% worse than the average student in two gut classes. Now expand this to every student for every class, and list their GPA+ on their transcript. (Perhaps it’d be useful to provide the average grade for each class next to the grade the student attained.) Now anyone reading the transcript has a far better measure of whether the student did well in easy classes or challenged him/herself, with the appropriate hit to the GPA. This also removes the incentive to take easy classes only, since a hard class will reflect itself in an appropriately low denominator.)

School Quality

The above changes will permit comparisons of students at the same school that take different course loads. This is helpful to a degree, and it lets students take classes they need rather than classes they want, but it doesn’t solve the problem of comparing students from different schools. Of course, the current system doesn’t really do that either, and I don’t think it’s a huge problem for people to differentiate between graduates from Stanford and Idaho State (no disrespect to the Bengals).

That issue is solved in OPS+ by adjusting for park effects – certain parks are smaller, others have better backgrounds, still others have wind that blows out more frequently, so some parks are easier to hit in than others. Park effects are calculated by comparing runs a team scores at home and runs they score on the road, and using the ratio between the two to calculate the park effects. This is difficult to accomplish in colleges, since so few students take similar classes at more than one school, but an interested party could still get additional information. For example, a particular employer or graduate school could track how graduates of different schools with similar GPAs turn out as employees or doctoral candidates. If Stanford engineers are 20% more productive at your company than Idaho State engineers of the same GPA, then you should give Stanford applicants an implicit 20% boost in GPA relative to ISU applicants.

With enough data, you can generate these ratios for many schools, and even for particular fields. Park effects can be calculated separately for, say, home runs (which benefit from small parks) and triples (which benefit from large parks and unusual design), or even for left-handers and right-handers. One could imagine calculating separately the implicit differences between Stanford English majors, ISU English Majors, Stanford math majors, and ISU math majors applying to your program.

Of course, few organizations will get enough data to figure this out,* since much output can’t be measured well enough to compare graduates, and you need large sample sizes to make meaningful conclusions. This would be difficult to put together from existing data sets, too, so most likely industries would have to combine data for this to work. Considering the up-front costs, the uncertain benefits, and the collective action problems inherent in rivals working together, I’m not sure we’ll any such analysis any time soon. I wouldn’t definitely say no, though, as identifying market inefficiencies and recruiting talent are going to matter more and more.

*Except the NSA.

Dave Cameron, Baseball, And Basic Economics

Dave Cameron is one of my favorite baseball analysts, and he has an article up at ESPN (subscription required) that shows some sophisticated math as applied to baseball. Specifically, Cameron shows that, considering the falling offensive output, home runs are actually less valuable than they are in a high-scoring environment. I won’t get into it here, but the basic argument is that in a high-scoring environment, good offensive plays (hits) are more likely to be preceded or followed by another hit and thus have a higher impact. It’s pretty smart stuff.

Cameron, unfortunately, makes one error in the piece that is related to economics:

Let’s deal with the scarcity issue first. Yes, there is now a lower supply of home runs than there used to be, and when supply goes down, price usually goes up, assuming demand holds steady. However, a baseball game is not a very good model of economic theory, because the scoring system of baseball is not designed to reward scarcity. If events were valued based on how rare they were, the triple would be baseball’s ultimate hit, as there were 4,661 home runs but only 772 triples last season. Of course, no one thinks triples are more valuable than home runs just because there are fewer of them, because the currency of baseball is runs, not scarcity of events.

At the end of the day, the only thing that really matters is how many runs a team scored and allowed in a given game. Even over a full season, the standings usually track very consistently with total runs scored and runs allowed. How you score runs does not really matter so long as you do. Home runs certainly help in that regard, but they don’t become exponentially more valuable simply because they become more scarce.

Sadly, Dave is very wrong here (baseball IS a pretty good model of economic theory) and he even tells us why (demand doesn’t hold steady). He’s obviously right that the goal of baseball is wins, and they’re obtained with runs. Hits, including triples and home runs, are ways to get runs, but they’re obviously not equally effective at getting them. Home runs are much more efficient at getting runs, so they’re in much higher demand. Thus, the relative scarcity of triples doesn’t really matter: it’s their relative ability to generate runs that explains why home runs are so much more richly rewarded in free agency.

It’s true that “Home runs certainly … don’t become exponentially more valuable simply because they become more scarce,” but no one – certainly economic theory – would argue that this necessarily follows. (I’ll ignore the “exponentially” as an exaggeration.) Horse buggies and bank tellers are becoming relatively more scarce AND relatively less valuable at the same time because in a changing environment (cars and ATMs), their contribution to well-being is lower. In Cameron’s article, home runs are becoming more scarce and also less valuable. He’s right to point out the latter, because it’s not at all obvious, but he’s wrong to impugn economic theory in the process.

On Pressure and Chemistry (In Sports)

The Tampa Bay Rays defeated the Texas Rangers earlier tonight in what was confusingly referred to as a playoff game, even though it’s not part of the playoffs. The Rangers, trailing both my Indians and the Rays in the wild card race for much of the last week, were set to play either three or four (depending on other games on Saturday) consecutive games in which a loss would mean elimination. As they lost today, they didn’t get to four straight, but that didn’t stop the announcers and several people on Twitter from wondering how the Rangers were affected by that pressure.

It’s a reasonable question, and it arises often in sports contexts, but it seems to me that most people approach it the wrong way (as happened tonight). As a note, I’m not referring here to “clutch” situations I’ve addressed before. I’m talking about the cumulative effect of several days under stress. It seems to me that most people are placing the emphasis in the wrong place. Announcers will talk, after a miscue, whether the cumulative stress of consecutive important games is “getting to” a player. While I think fans and announcers overvalue the effect of pressure and stress on professional athletes, if there is an effect, I believe it’s complete by the times the team take the field. Athletes, for the most part, don’t think consciously while they’re performing – at that level, most actions are best described as quasi-instinctive. They’re not legitimate instincts, which are natural and inborn – there is no natural instinct to cover first base on a grounder to the right side – but after sufficient practice and repetition, the reactions are automatic. (My professor Danny Kahneman’s theory explains how.) As a result, it’s difficult for a player to be bothered by something that happened two days ago while he’s swinging at a pitch (or reading a coverage, or pick-and-rolling).

However, a player involved in stressful activity for an extended period might well enter a game more poorly prepared than he otherwise would be. Perhaps he didn’t get enough sleep following a difficult loss; perhaps he’s a bit dehydrated from celebratory champagne; perhaps his nutrition is suboptimal because of a disrupted late-season routine. As a result, a series of elimination games might actually make a player or team perform worse (or not), but any such effect happens before the game starts. After that, instinct, talent, and luck take over.

This view is the flip side of my take on clubhouse chemistry. Some argue that good chemistry is necessary to winning; others say talent is the only thing that matters, and winning creates chemistry. While I won’t dispute that winning makes people get along better than they otherwise would, I do believe in a particular value of clubhouse chemistry. Specifically, it (along with proper coaching) can foster better preparation than a poisonous atmosphere would. Hardworking teammates who spend a lot of time lifting weights and watching film can induce others to do the same and be better prepared once the game begins. I don’t think it makes players more talented than nature permits; it just makes them come closer to their full potential.

A quick Google search shows that my view on chemistry is shared at least by Keith Woolner of the Indians:

Matt A (Raleigh): ARE you a believer in intangibles? Has your experience with a big league club changed your thoughts on this?

Keith Woolner: I’m not sure that “changed” is the right word. Rather, it’s help crystalize some things I thought to be true, but was fuzzy on the specifics. There are advantages to having good people on your team, whether you’re talking about the clubhouse or the front office. Good work ethics rub off on the people around you. Veterans setting a good example help a young player develop good habits. Good habits help a player maintain and improve his ksills. A team leader isn’t going to help a guy swing the bat when he’s at the plate, but the guy at the plate might be a better, more prepared version of himself because of the players around him.

Why Not To Like Sports

There has been a rash of columns this fall by fans quitting the NFL for a few common reasons: the emerging science of head injuries, the ubiquity of performance-enhancing drugs, and the associated corruption of college football (which is an abomination in itself).

I’m sympathetic to the arguments: the brain injuries in American football are too frequent and too harmful, and there’s something bestial about watching men fight one another and shortening each other’s lives in the process. (That’s part of the reason I never got into boxing or MMA, the modern gladiators.) While I’m certainly not an anti-PED loon, I do feel that achievements lose some value or at least authenticity when they’re accomplished with PEDs. It’s just a feeling, and I can’t really justify why eye surgery is okay but human growth hormone isn’t. Suffice it to say that my feeling seems to be shared by many, if not most fans.

As for corruption, it’s bound to pop up in any highly regulated industry that’s overflowing with money. Since sports leagues, by definition, restrict who can do what, and since their restrictions are largely arbitrary, they’re susceptible to such abuses. (Especially the evil empire that is the NCAA, but that’ll be the subject of a future post.)

So I understand why so many are quitting the sport right now (although some of it is just to be able to say just how moral and high-minded you are). In fact, I’ve entertained similar thoughts. My travel schedule last year made me miss most of the NFL season, and I’ve rarely been less excited about it as the concussion lawsuit continued. In fact, It’s made me wish that I cared less about sports. (Note: everything I say here about sports applies also to the various arts). Sports isn’t an endeavor that contributes to the enduring well-being of mankind in any real way. Yes, we may develop some medical advances (orthopedic surgery, nutrition, etc) that benefit the rest of humanity, but the price we pay is high: hundreds, thousands, millions, billions of man-hours spent on designing a blitz package, on watching scout film, on compiling and analyzing statistics of a game. Imagine the smartest players, coaches, and analysts dedicating this energy toward more useful scientific pursuits. The opportunity costs of sports are massive.

People enjoy sports, of course, and we can’t discount that as a benefit. But as my old professor Danny Kahneman has explained, people perceive a loss to be worse than they perceive an equivalent gain to be good. (Meaning, it hurts more to lose $10 than it feels good to find $10.) By this logic, contests with a winner and a loser can produce net losses: if the fan bases are roughly equivalent, the pain of losing will outweigh the joy of winning. Week after week, we could be increasing world misery every time a game doesn’t end in a tie (which, in some places, produces pain of its own). Not only that, I sometimes wonder if it’s fair to subject people around me to sports-induced feelings: why should my family have to schedule events around a particularly meaningful game, or my girlfriend have to deal with a bad mood following a particularly brutal loss? They don’t deserve to deal with the fallout of my obsession with what is basically “other men playing a game.” I bet this is true for many, even if it’s often exaggerated.

Sports, as long as it’s profitable, will continue to be plagued with bribery scandals, cheating (including drugs), corruption, and related problems. Add to that the reality that many sports result in health problems for the players (a problem worse at the amateur levels, where players don’t get paid), and it’s understandable that someone might not want to be a part of this. I get it. I enjoy sports way too much to quit it myself, but I suppose realizing I’m part of the problem is a first step, even if there isn’t a second one.