What’s the toughest division in baseball?

16 04 2010

I’ve been playing around with the Ease Rankings feature on Baseball Monster, trying to figure out which divisions are toughest to pitch in.  I’m focused on starting pitching, so I customized league settings to look only at wins, strikeouts, ERA and WHIP.  Baseball teams play divisional opponents more than anyone else, so I averaged the Ease Rankings by division:

  • AL West: 0.48 (most favorable to pitchers)
  • NL Central: 0.42
  • AL East: 0.10
  • AL Central: -0.23
  • NL West: -0.37
  • NL East: -0.39 (least favorable to pitchers)

Going a step further, I created pitcher ease ranking for each team by excluding the team they pitch for from the average.  The analysis shows that the easiest teams to pitch for are Oakland, Texas, and St. Louis.  The toughest teams to pitch for are San Diego, Atlanta, and Cleveland.

It’s early, and these rankings are likely to change, but they’re pretty interesting and have interesting implications both for fantasy and real baseball.  For one, don’t blame Javier Vazquez’s early struggles on his league change; thus far, the Yankees’ divisional rivals haven’t been hitting the ball nearly as well as those of Vazquez’s former team, the Braves.





Loss Aversion in Fantasy Baseball (continued)

8 04 2010

I was already planning to follow up yesterday’s post with some reasons why loss aversion might exist in fantasy sports, when reader Joe makes the following comment:

The goals of fantasy sports isn’t just winning; there are two: winning and maximizing bragging rights.

Picking up some new dudes and saying, “I KNEW that Whosthat McRandom was going to be awesome” is much more awesome than bragging, “I KNEW that Oldnewsy von Fartington still had another year in him.”

This is a decent summary of a casual attitude towards fantasy sports. “I probably won’t win anyway, so I might as well have some fun along the way.” It’s not my attitude, but I’m not a casual player–I’m an extremely competitive one. In my view, there’s no point in bragging if you’re losing. If you want to brag, play a strategy most likely to win, then brag when you win. Find creative ways to brag if need be. Back in 2003-2004, I KNEW that Kerry Kittles still had another year in him when he helped me win a 20 team fantasy basketball league.*

*I didn’t actually know this, so much as strongly suspect. The following season, Kittles played 11 games off the bench, then retired.

However, there actually is a case to made for picking cagey veterans over hotshot sleepers, from a bragging perspective, which is that no one else is doing it. Over at Baseball Analysts, Sky Andrecheck argues that experts should make recommendations based on how their opinions set them apart from other experts. It’s not hard to find an expert who’s big on Jason Heyward or Gordon Beckham; it is hard to find an expert who likes Johnny Damon and Chipper Jones over those two.

Throughout the season, I’ll check in on the veterans I praised and prospects I questioned in yesterday’s post and compare their stats. If my picks pan out, no doubt I’ll brag relentlessly.

Finally, I’d like to generalize the point I’m trying to make about young and old, and, just for fun, I’ll do it in the form of a delta-epsilon definition:

In fantasy baseball or basketball, for every set of players without proven track records ε, there exists a set of players δ who play the same positions, are older, and are deemed worse by fantasy experts, such that the expected value of δ exceeds the expected value of ε.





Loss Aversion in Fantasy Baseball

7 04 2010

In behavioral economics, loss aversion refers to a bias where people prefer a chance of gain over the combination of locked-in gain and chance of loss, even though they have the exact same results. For example, consider the following cases:

Case 1: Choose between receiving $100, or having a 50% chance of receiving $200 dollars.
Case 2: You receive $200. Then, you choose between losing $100, or having a 50% chance of losing $200 dollars.

Mathematically, the two cases are identical. Yet experimentally, when presented with offers as written, people tend to prefer the second option in case 1, and the first option in case two. Basically, people like the feeling of upside risk, knowing they stand to gain extra, but don’t like the feeling of downside risk, or knowing they might lose extra.

In fantasy sports, this bias pops up in the strong preference for younger players over older players. For instance, consider these two options:

Option 1: A young outfielder, with little major league experience, has a 50% chance of becoming a very good player this year, but otherwise will have little or no value.
Option 2: An old outfielder, who has been very good for many years, has a 50% chance of providing little or no value this year, but otherwise will remain a very good player.

Again, these two options are mathematically identical, but there’s a significant preference for Option 1 among fantasy players. Spotting these opportunities is a key way to gain edge in fantasy sports, and a key reason why my teams tend to include players at the tail-end of their career.

For instance, this year I have one team with an outfield of Bobby Abreu (36 years young), Raul Ibanez (38) and Johnny Damon (37), with Chipper Jones (38) and a banged-up Lance Berkman (34) slated to share my utility spot. Some of those guys won’t pan out. But I’m just as confident in this group as I would be in an outfield of Jason Heyward (20), Hunter Pence (27), and Chris Coghlan (25), with Gordan Beckham and Billy Butler (both 24) at utility. And my team came much more cheaply, allowing me to slot more reliable players elsewhere.

I’ll check back on this question throughout the season, but right now I feel pretty good.





New York Times, Meet Economics 101

6 04 2010

This is a nitpick, but this NYT op-ed by Jay Soled and Richard Schmalbeck, on tax deductions granted business for attending sports and other entertainment, has a minor economics error in it, and I feel great need to point it out.  While I generally agree with the analysis and policy recommendation, the following section does not scan:

These deductions have led to higher ticket prices in two ways. On the demand side, they have fueled competition for scarce seats, with business taxpayers bidding in part with dollars they save through the deductions.

On the supply side, the large number of businesses bidding for expensive seats has driven the expansion of luxury skyboxes and a reduction in overall seats in new ballparks.

The authors argue that there are two effects–one each on the supply and demand sides–but there’s actually just one effect, on the demand side. In response to the policy-induced demand increase, quantity supplied has increased, but quantity supplied is not the same things as supply, and supply is not affected by the policy.

If government were to subsidize construction of stadiums with luxury skyboxes (which, of course, they do, but this is not the point the authors are making), then indeed there would be a supply side effect.  Instead the authors are trying to present a demand side effect as both a supply effect and a demand effect, a most nefarious* attempt to strengthen their case.

*: Not actually that nefarious

Anyway, this whole post is a roundabout way of saying this:  It’s time to start blogging again.





Fantasy Jose Canseco League

18 06 2009

Jose Canseco simply cannot stay out of the news.  Anyone interested in a pool to bet on the next time Jose Canseco makes himself newsworthy?





What’s Next?

4 06 2009

It’s become increasingly likely that, barring an injury or meltdown, Hurricane and I will win both our fantasy baseball leagues, currently leading them by 8 and 5.5 points.  With fantasy hoops and hockey finished for the year, and football season three months away, I’m not quite sure what to do with myself.

Anyone interested in starting a fantasy wedding league?





Kawasaki Konjecture, June 1

1 06 2009

Every two weeks, I post the top ten ranked pitchers over the two-week period, in order to test the theory that in fantasy baseball, drafted starting pitchers have little added value over starters added off the waiver wire.

This week’s top ten pitchers, from Baseball Monster, looking at Wins, Strikeouts, ERA and WHIP:

  • Early draft picks: Jake Peavy, Tim Lincecum, C.C. Sabathia, (Matt Cain)
  • Late draft picks: Chris Carpenter, Justin Verlander
  • Undrafted: Jason Marquis, Clayton Richard, Edwin Jackson, Phil Hughes

Matt Cain is bracketed because he was an early-middle pick.  Compiling the results from the first four two-week periods of baseball season, I find that of the forty pitchers to appear in the top ten, fourteen are early draft picks, fourteen are late draft picks, twelve went undrafted and two are relief pitchers.

In both our leagues, Hurricane and I spent very few resources on starting pitching–no keeper spots, nothing earlier than a tenth round pick.  In both our leagues, we’re a little ahead of average in the four categories where starters compete, currently holding 24 of 40 and 32 of 56 total possible points.

I’m not sure how much support/opposition either of these analyses give to the Kawasaki Konjecture.  I’ll try to post a few more tests over the next few days.