Tuesday, November 20, 2012

Big Ten and the East Coast

Just a link for today, as Nate Silver has echoed my concerns over the Big 10 inviting Maryland and Rutgers to the conference.  From the standpoint of the two schools, this makes a lot of sense, money wise (leaving aside the huge ACC penalty).  However, I just don't get it from the Big 10 perspective.

Being from the MD-VA-WV-DC area, I can say that MD football isn't a big deal.  Most of the people I know are Penn State, WVU or Va Tech fans.  Even more are transplants to the DC area that are fans of other schools around the country.  The conference already has enough teams to have a championship game, so why do this?

I guess we will have to wait and see.  But it seems that the current Big 10 teams could be reducing the share they get from their media deal(s), and not really expanding to any market on the east that is worth much.  But of course, both Nate and I could be wrong.

Wednesday, October 31, 2012

Good Short Article on Economic Impact of the Super Bowl

Just a link today to a nice article about the prospective economic impact of hosting a Super Bowl

In general, I would say that if a region can get a Super Bowl, that's probably not a bad thing.  Just as long as they're not paying to bring it there.  The issue economists usually have with hosting large events isn't that the events are bad--there is much good that can come from them--but that cities generally try to outbid each other for these things.  In terms of the economic impact they have, the bids are always much, much more.

Of course, some events can crowd out economic activity (imagine trying to travel into Chicago for dinner at Ditkas if the Olympics were in town).  Ultimately, this could create a net negative result, too.

The final quote in the article is rather entertaining as well.

Hat Tip: The Sports Economist

Monday, October 29, 2012

Barry Bonds and Structural Breaks

A new issue of JQAS just came out, with this fun little piece.  It uses structural break models to analyze exogenous shocks in Barry Bonds's (Bonds'?...I have the same issue when using my own name: what's the grammatically correct choice here?).

Now, let's begin by saying that the answer to whether there was a structural break here is pretty obvious.  But since my entire dissertation was about structural breaks (an example plot here 3rd one down) in the 4 North American Leagues (and one of the authors of this paper designed the main statistical test I used for stationarity in the presence of breaks), it's always fun to see the method in action.***

I have not read through the entire paper; however, I can offer up a few notes about the method itself.

First, it can be very sensitive.  While they do not use exactly the same method to model the breaks that I did, I can say that very small changes in the data have impacted my analyses rather unexpectedly (see the downward shift earlier in Bonds's career that seems to be a product of one huge outlier).

Secondly, defining an "exogenous" shock is not as straight forward as you would think.  In the context of statistical modeling like this, an exogenous shock can be anything not included in the model.  So, if you model attendance of the Miami Heat without a dummy variable for their NBA Championships, you'll probably find an "exogenous" shock in your model around there.  But we all know where this came from.

With that said, these models can be very useful when we want to look at stationary segments and avoid issues with unit roots due to one time changes.  They can also be useful when we don't have an easy explanation for what happened.  And they're always fun in a descriptive sense (as shown in this paper).

***Add in that the first game I ever saw in the Big House was the Appy State game, and Strazicich does his work there, makes for fun coincidence as well.

Wednesday, October 24, 2012

How Much are College Players Worth?

Roger Noll has some estimates.  I had the chance to meet Dr. Noll a couple years ago, and he is really an entertaining guy.  Of course, he is also extremely thoughtful (as one would expect from an emeritus Stanford professor).

I haven't looked at the full released report yet, but hope to do so in the future.

Hat Tip: Stacey Brook at Team Sports Analysis

Friday, August 31, 2012

Another Day, Another Economic Impact Report

A former Michigan office mate (and avid runner) sent me a link to an article about economic impact of the Chicago Marathon.  I think it was mostly to convince me that other sports matter besides baseball, but let's be serious ;-).  The link is here.

Anyway, I always enjoy taking a look at these articles and the multipliers they use.  This one was pretty out of whack (I'll get to that later).  There's plenty of literature out there that speaks about the importance of accounting for all the effects and leakage of these events, but these reports keep on coming.  Luckily, Allen Sanderson provides us with some common sense.

Now, there are certainly great things about hosting a marathon.  There's the possibility that it sparks interest in physical activity (though, this phenomenon is not well understood).  It certainly brings some people into the city.  People definitely spend money.  People seem to have fun--for whatever reason--running or watching others run 26.2 miles.  But when we talk about economic impact, we don't really care about the total amount of money spent in the 3 days or so.  We care about the additional money spent in those 3 days or so.

A large majority of the spectators of the marathon are likely from Chicago.  They would be spending this money in the city anyway.  So we need to account for this fact, which reduces the initial impact estimate (pre-multiplier) by a huge amount.  We need to know how much non-Chicago native money comes in (a point also made by Sanderson above).

Streets generally get closed for these sorts of events.  That could be a net negative on both business and the residents in the city, or those that commute to the city and have to take a longer alternative route.  If the marathon wasn't going on, there would also still be plenty of entertainment in Chicago to take its place.  So maybe people that would have come for that alternative entertainment don't come during the marathon.

Does it create jobs?  Maybe, but it is doubtful that there is any real job creation.  Most of the people working these sorts of events tend to be volunteers.  And even if there are some new jobs, they'll be very temporary.  Marathons may seem to last forever for the runners, but they're really just a weekend event (or less).

What about hotels and restaurants?  Well, they're probably liking the event.  Most likely, they have some increases in rooms and room rates during this short period, but as the second linked article above notes (and does the math), it is nowhere near the estimation from the first linked article.

What about multipliers?  There are reasonable defenses for using a multiplier.  After all, when you buy a bagel and coffee at your local store, at least some of that money is likely redistributed and used again within the city (the local employee gets a salary, the owner takes his or her cut, maybe they use the sales to buy coffee grounds from a local coffee grower...not likely in Chicago).  If you buy coffee at a place like Starbucks or McDonalds, it is likely that less of this money stays within the city limits to be spent again than a locally owned shop.  But in any case, some of that money stays within the city and gets spent again, so we use multipliers.

A huge problem with almost any impact study is that these multipliers are way out of whack.  The one above uses a multiplier of 2.29.  Or, for every dollar spent, it supposedly results in a total of $2.29 of economic activity within the city limits of Chicago.  Conveniently, Mark Rosentraub and I have a forthcoming paper looking at more reasonable multipliers due to leakage using some VERY simple hypothetical examples.  Now, keep in mind that our examples could be overly simplistic.  But the point is that the multipliers really depend on the size of the region, the types of industry located within the region, and the commute sheds of the region.  What do we get as more reasonable levels of a multiplier?  About 1.28 or less.  Or, for each dollar spent within the city--above and beyond what would have been spent anyway (this is important)--creates an additional 28 cents in economic activity beyond that dollar.  That's a far cry from an extra $1.29 in activity.

So if we say that only 25% is NEW spending, then use our multiplier, we get something closer to $25-$30 million in impact.  That might be great for the city.  But it of course depends on what the costs were to have security there, close the streets, and so on.  There could be other negatives (that are not as easily measureable) like residents hating the crowded streets, having to take on more travel costs getting around the city, taking a day off work or leaving early to avoid incoming marathoners on Friday (possibly lost pay for the worker and lost production for the company). 

To be sure, these estimates are difficult to make with pinpoint precision.  But using more reasonable guidelines at least gets us closer to what is really going on.  How about we start doing that...

Monday, July 23, 2012

Thoughts on Penn State

I figure that after the huge announcement about Penn State football (and growing up a mild Penn State fan in Northwest-Central Maryland, mostly stemming from our high school QB taking over the helm at PSU in 2001) I should write something here.

As someone who in the past found Joe Paterno to be one of the most interesting and respectable coaches in sports, this whole event is a huge shame.  I can to some extent understand a relatively passive reaction to the idea that a good friend is doing terrible acts.  That is a very tough situation, but still one that seems clear what should be done.  I cannot, however, understand actively ensuring that others don't find out about this when I know the truth.  If this is really what happened, I have no sympathy for anyone involved.  Period.

However, I don't find the NCAA sanctions particularly comforting or useful.  There are a few reasons why.  I'll list them below, then talk about what I mean one by one.  I'll first preface this with: there is no penalty that can make up for the awful things that took place in the PSU locker room.

So here are my issues:

1) Nearly all of those people responsible for these events and its cover up are either dead, in jail, or have been fired.  In a situation like NCAA penalties, the idea is to ensure there is a strong incentive not to participate in certain behaviors.  If there is no punishment, then one could argue that they are encouraging this to happen.  So there should be punishment, but it should be punishing those responsible, not someone else.  I'll expand on this in Point #4.

2) Some feel that punishment is solely punitive, but I don't find this particularly relevant from the standpoint of the NCAA.  We should leave these decisions up to the criminal justice system in a situation such as this.  The NCAA's interests lie in incentivizing certain behaviors for their organization as a whole.  They have a right to fine, sanction, punish, etc. in the name of these goals.  But the acts here are not a case relevant to NCAA operations as an organization (leaving aside the moral obligations of people working with children--which here is a PSU oversight issue).  I'll expand on this in Point #3.

3) I am not convinced that there is a realistic moral hazard issue here in a specific sense.  I do believe there is a moral hazard issue of not punishing PSU in a general sense.

In this case, the idea is that allowing PSU to go unpunished for their lack of oversight will show that there are not consequences to covering up child molesting in the future.  That may be true, but I don't know that this, specifically, is a realistic concern (others may disagree).  The large majority of people, including coaches, find these acts abhorrent, disgusting, immoral, and so on.  I would like to believe that most would report, or at the very least not actively cover up, these issues if they are occurring.  I fail to see an upcoming epidemic of covering up rampant child molestation in college football locker rooms in the case where significant punishment does not take place...

This, of course, does not preclude issuing consequences for lack of oversight in a general sense.  There are many other issues which a coach or athletic department could decide to cover up that have less certain moral implications than something like child abuse.  If the NCAA wants to remove incentives for covering these things up, it should come down hard on PSU as an institution.

Which leads me to my most important concern...

4) The NCAA--if looking to punish Penn State and those responsible for "oversight"--did not choose some of its punishments particularly well.  This is the case with respect to their own (the NCAA) interest as well as the interest of the innocent football players at Penn State (and as a whole in NCAA).

In order to minimize collateral damage, the NCAA should have chosen to institute a larger lump sum fine (or "morality tax" if you will) in place of bowl and scholarship penalties.  Why you ask?

**Note: I am fine with vacating all of the wins while the cover-up was going on.  This is part of a lump sum fine/tax and can go along with monetary fines.**

Well, first and foremost, the players currently on the team had nothing to do with the events that took place in the 1990s.  By instituting football-specific penalties in the future, they are punishing these players who have already borne a large cost from being tied up in this whole mess thanks to a deceitful Paterno ("Come to Penn State...because I ensure moral character and academics and blah blah blah").  By instituting bowl and scholarship penalties, these players pay an even larger cost.  Yes, that cost is somewhat reduced by allowing them to transfer without penalty.  But this is really a red herring: the rule is essentially a way for the NCAA and its coaches to reduce the competitive labor market for playing football in the first place.  Gee thanks, guys.

Additionally, assuming that the cost of picking up and moving colleges is minimal is a real fallacy.  We're talking about very young people who have put roots in social (and future career) networks in State College.  Losing these is a high cost, not to mention the uncertainty clouding their future in football (what's to say they'll play somewhere else?).

The further impact is to football players in general.  While a small change, reducing Penn State's scholarship offers DOES reduce the opportunities for lower income athletes to have their college paid for at the margin.  Players that are good enough to play at Penn State can play at institutions equal and lower than PSU in a football sense, but of course that pushes out spots for guys that would have played at those places, and so on.

Another view comes from the NCAA: other than PR, they don't have much incentive to have Penn State become completely irrelevant.  As we've seen over the past year, they have a rabid (and yes, sometimes irrational and misguided) fan base.  No, I'm not saying the NCAA should choose $$ over child molesters.  But the NCAA will lose out on significant total revenue by reducing their competitiveness over the next 5, 10, maybe 20 years.  There are ways to lay down a hammer on PSU without these ancillary value reductions.  In other words...

A larger lump sum fine in place of these penalties could improve things for everyone.  First, the value of the scholarships to Penn State's athletic department (and the whole school) could be estimated.  We can include that in our fine.  The same goes for the bowl appearances.  By doing this, Penn State still pays the full cost of the sanctions.

Doing this reduces the cost passed on to the players that had nothing to do with the tragic events.  This is different than when coaches and players agree to compensation or other violations.  In these cases, there are explicit agreements that include players to break the rules (yes, players have lots of incentives to do so and I am not condoning players working for free for the NCAA).

Could PSU just pass on the cost to the players?  Yeah, it could.  But it's much less likely for a number of reasons.

First, the marginal cost of scholarships is near $0 for a large university.  We're talking about 10 extra students in a population of 40,000.  That's, say, one extra kid in a class of 30 to 500 that is being taught anyway.  The professors' time is already being taken up by the class, so there isn't much additional cost to having 31 (or 501) students instead of 30 (or 500).  The opportunity cost is somewhere near $0 as well.  Without a scholarship, it's not likely that the university would have collected tuition dollars from that student anyway (they would have gone elsewhere).  These guys aren't really 'taking a seat' of another student.  The admission process is almost completely separate.

If Penn State's athletic department is looking to maximize revenues (profits?...we'll leave aside moral arguments about college athletic departments for now), given whatever constraints they have, then they'll issue these scholarships to deserving football players up to the marginal value of these players (or the limit of scholarships, which likely comes first) despite being hit with such a huge lump sum fine.

So why also allow them to participate in bowls?  Well, by reducing their potential revenue, you reduce their incentive to invest in the program.  This is what happens with revenue sharing in some cases in Major League Baseball (or so, much of the literature goes).  If you can't get the $6 million bonus, then you won't be investing as heavily in your product.  This cost is borne by players through facilities that aren't up to par, or other perks when they arrive as a football player at PSU.

Once the lump sum is paid, it is seen as a sunk cost.  It does not enter into their decisions for future revenues and costs (but not being allowed in bowl games certainly does).  This is Economics 101.  They'll pay for facilities up to the point that the marginal value it attracts (players) equals the marginal cost (scholarship and facility upgrades).  They'll probably be cash strapped depending on where the money comes from, but it won't reduce their future earning potential and their football revenues can continue to help fund other sports within the department.  In this way, it doesn't distort decision making in a way that punishes those not responsible.  PSU can just snatch this out of their endowment (and I am told that their donations from alumni are at an all time high at PSU as a whole since this all started last year).

(Note: Stacey Brook has an explanation of a lump sum tax vs. one described by Nick Saban here.  I tend to agree with Dr. Brook on this as well.)

Maybe for some of you, a $100 or $200 million penalty (or more) just isn't enough.  But the truth of the matter is that nothing will be enough as retribution for ruining childrens' lives.  There seems little reason to increase the costs to people that have nothing to do with this tragedy.  Really, the loss of scholarships and bowls amount to a loss of revenue for Penn State.  A loss of stature due to these results in a loss of revenue.  Fire those involved.  Put them in prison.  Let them pass away in disgrace.  Calculate what you think they should pay, and have them pay it.  Don't push it on to innocent parties.

Tuesday, July 10, 2012

Yet Another Hall of Fame Paper

Browsing around some journals this morning, and came across another paper looking to predict Hall of Fame election (using vote counts).  This analysis is a little more sophisticated than some previous ones I have seen in the economic literature.  I haven't gone through it too carefully, but I know there would be some interest from those who visit here every once in a while.

As I have mentioned before, my colleague, Steve Salaga, and I have a similar type of paper in JQAS.  However, we don't look at vote counts, so there are limited conclusions to be made from that.  Our paper really is only interested in whether certain players were snubbed based specifically on the BBWAA's previous standards.  This is very different from who is "deserving" from a pure performance and value sense.  Just something to always remind people when reading these papers from the academic standpoint.

Tuesday, June 26, 2012

Fantasy League Idea as an Academic Paper

Early on when I started this blog, I wrote a lot about a proportional prize payout model for a fantasy baseball keeper league.  I argued that this sort of payout would not only keep people interested throughout the season, but also attenuate some dumping that often goes on in keeper leagues.  Well, it turns out that some smart people have done some research on proportional prize tournaments and, not surprisingly, they find them to be superior in incentivizing effort throughout the game.  A quote from the paper:

"Recent theoretical and experimental studies have identified several limitations of winner-take-all tournaments that might lead contest sponsors to seek different designs ( [Lazear, 1999] and [Lazear, 2000]). Relative to piece rate wages, winner-take-all incentives may lead to greater variance in effort by players ( [Bull et al., 1987] and [Nalbantian & Schotter, 2006]Eriksson et al., 2009) or sabotage among them (M√ľnster, 2007; [Chen, 2003] and [Harbring & Irlenbusch, 2008]), and the outcomes are also affected by heterogeneity among players ( [Schotter & Weigelt, 1992] and [Harbring et al., 2007]) as well as risk-sharing incentives (Krishna and Morgan, 1998). These considerations may discourage players from entry and distort performance, and thus reduce the total effort elicited in winner-take-all tournaments. Winner-take-all tournaments can also lead to a more unequal distribution of income (Frank and Cook, 1996). Moldovanu and Sela (2001) show that an alternative tournament design with multiple prizes elicits higher aggregate performance when the cost of effort is convex. One of their predictions is tested in a maze-solving contest by Freeman and Gelber (2010), who find that the multiple-prize structure does result in higher aggregate performance than the winner-take-all payment.4

This paper studies a new type of tournament: a proportional-prize contest, in which the prize is divided among participants in proportion to their achievement.5 This type of contest imitates some forms of competition among firms, for example, whose effort may be rewarded through a share of industry profit. Shared prizes can also be awarded in lobbying contests, such as the allocation of import quota licenses among competing importers (Krueger, 1974). Proportional contests may also be used within firms to reward workers, or as a type of procurement contract to elicit effort among suppliers. For example, poultry meat processors in the United States use proportional-payment competitions among their suppliers to spur cost reductions; Zheng and Vukina (2007) study the case of one firm that switched to such contracts in 1984, and estimate the resulting increase in performance compared to the rank-order contests used previously."

 I'd really like to get my league started up with some serious competitors, especially after seeing this.

Thursday, May 17, 2012

Upcoming NASSM Presentation

Just a quick announcement that next week I will be in Seattle, Washington for the North American Society for Sport Management (NASSM) Conference.  It is my first time to Seattle, so any suggestions on things to do and places to go would be appreciated.  I am definitely going to at least one Mariners game, so no need to suggest that!

This conference is probably of significantly less interest to readers here than that of the Western Economic Association meetings or any sports statistics conference.  However, there are some interesting economics-based research projects being presented (specifically on the first day, Thursday, May 24).  The full program schedule can be found here.

My office-mate, Mike Cantor, and I will be presenting some preliminary looks at thinking about demand analysis in the Sports Economics literature and operationalizing variables to better assess market conditions and stadium success.  The link to the abstract can be found below:

Defining Available Wealth and Its Impact on Demand for Attendance in Major League Baseball: Home Values, Local Population Density and Stadium Placement
by Michael Cantor, Brian Mills and Mark Rosentraub

If you happen to be in Seattle, come and stop by if you'd like (or suggest a beer-drinking place to meet).


Other works of interest from Michiganders and friends below:

Revenue Sharing with Heterogeneous Investments in Sports Leagues
by Steve Salaga, Alan Ostfield and Jason Winfree

The MLB draft: Training and employment outcomes
by Steve Salaga

A portfolio of partners for good?: Examining how perceptions of sport organizations' CSR partners affects willingness to donate to CSR initiatives
by Seung Pil Lee, Kathryn Heinze, and T. Bettina Cornwell

Measurement-based leverage of cause-oriented sports sponsorship
by Seung Pil Lee, T. Bettina Cornwell, and Kathy Babiak

Examining general managers in the North American professional sport context: Upper echelons as drivers of performance
by Matthew Juravich and Kathy Babiak

The effect of game uncertainty on demand for postseason games
by Scott Tainsky, Jie Xu, and Yilun Zhou

Heuristic cues and perceived product value: Effects of priming, team-brand cue and product category
by Dae Hee Kwak, Choonghoon Lim, and Youngbum Kwon

From human cockfighting to legitimate sport: Politicians weigh in on MMA
by Carla Santos, Scott Tainsky, K. Alexander Schmidt, and Chang Sup Sum

Tuesday, March 27, 2012

A Wolverine Grows Some Scales

So, as I mentioned in a recent post, I've been pretty busy over the past 6 months. Between getting married, applying for jobs (both academic and non-academic--for those interested in hearing about McKinsey & Co. interviews I am happy to give some insight there in what sort of atmosphere to expect, but take them with a grain of salt, as I was ultimately not offered a position), finishing up my dissertation, and having a slew of research papers coming together all at once, it hasn't left much time for blogging. But, luckily, all of this has led to an exciting announcement (for me at least).

So out with it. I have officially signed an offer with the University of Florida. Assuming a successful defense of my dissertation in May (of course, not a given), I will begin my new appointment as Assistant Professor with the Department of Tourism, Recreation and Sport Management in the College of Health and Human Performance this August. Obviously, I will then have to change the subtitle of this blog to "Naive Assistant Professor".

I will say that I will be very sad to leave Ann Arbor. Not only is this a great place to live, but the opportunities that Michigan has provided for me have been unbelievable. I was rather lucky to be in a situation where the department was in a monumental shift--especially for a Sport Management program--and it has been nothing but good. I was able to get here right as my adviser, Dr. Rod Fort, arrived and work with him as an MA student in the program. This ultimately led to me rolling into the PhD program and having a chance to do dual MA degrees in Statistics and Applied Economics--not a something that happens without some things falling right into place.

There is no doubt in my mind that this is the prime place for quantitative and economic analysis of sports (and this includes comparing it to economics departments). I have been able to bump elbows and work with some of the top names in the field, and would like to thank them for their guidance throughout the process: Professors Rodney Fort--who played a pivotal role, taking a chance on a guy with a Psychology degree to do quantitative work--Mark Rosentraub, Jason Winfree, Kathy Babiak, Stefan Szymanski, Dae Hee Kwak, Kate Heinze, Ketra Armstrong, Bruce Watkins, and Richard Wolfe (now at University of Victoria). I'd also like to thank my fellow graduate students here for all of our discussions and collaborations: Steve Salaga, Matt Juravich, Mike Cantor, Scott Tainsky (our first PhD graduate, and an Assistant Professor at University of Illinois), Kelly Xu, Thomas Peeters (visiting from Antwerp), Seung Pil Lee, and Joon Sung Lee. And, last but certainly not least, I would like to thank our Graduate Coordinator, Charlene Ruloff, for all of her help with administration of graduate student stuff. We would be completely lost without her.

Of course, I have had the chance to take advantage of the top tier Statistics and Economics graduate programs here at Michigan as well. The opportunity to take classes with the likes of Charlie Brown, Jeff Smith, Joel Slemrod, Scott Masten, and Naomi Feldman has been a real thrill. I will certainly be sad without Charlie around to pitch in softball. Hopefully, he will continue to share his thoughts on outrageous internet links.

Through my studies, I have had the chance to personally speak with Joel Maxcy, Michael Leeds, Stefan Kesenne, Roger Noll, Dan Mason, Stephen Ross, and J.C. Bradbury, as well as email discussions with Cy Morong and Young Hoon Lee. Each of these discussions had added to my knowledge of the field and expanded my mind with respect to possible research topics in the future.

As an MA student, I had the opportunity to take a class with Alan Ostfield, which was really a lot of fun. Additionally, Mark Rosentraub has been pivotal in providing students with access to prominent business figures in sports. Through Dr. Rosentraub, I have had the chance to meet, hear talks from, and/or have lunch with the likes of Rob Dupuy, Ron Shapiro, Jim Irsay, Steven Soboroff, John Moores, Paul Dolan, and Dan Gilbert. While I am sure they won't have much to remember about me, I will certainly always remember what they had to say while they were here.

This blog has gotten more attention that I would have ever expected. It really started out of frustration as a grad student having lots of ideas, and little direct outlet for them. The chance to speak with some prominent names in the front offices of MLB, talks with Josh Orenstein at Trackman Technologies, and an invitation to speak at an R Users Meetup following Metamarkets CEO Mike Driscoll--not an easy act to follow at a data science meeting!!--all stemming from work on this blog have been a real unexpected honor.

Of course, those commenting here--and at other online forums--have forever contributed to my thinking about analytics and sports. I thank you for the enlightening discussions over the past couple of years, even if we still disagree. Mike Fast, especially, has been extremely helpful in discussions regarding Pitch F/X data. I don't have any plans to stop updating my blog, but the type and regularity of updates will depend on the time I have over the next 6 months or so as I finish up my required work and prepare for the move.

So, here we go. Looking down the home stretch--and with some luck--I have sun, palm trees and Spanish moss in sight. I am excited to become a Gator.

Tuesday, March 20, 2012

"Sporty Business"

Just highlighting that I added a new blog to the sidebar, "Sporty Business". It is a Forbes blog by Stefan Szymanski, of Soccernomics fame, who happens to be next door to me here in my office. I actually had a chance to discuss his most recent post--about Basque soccer--at lunch the other day. Always exciting to have such high level sports research going on around you. Hopefully, Stef and I will start working on a project together soon. Go check it out, especially if you're a soccer (football, futbol) fan!

Wednesday, March 7, 2012

Strike Zone Changes?

It's been a while since I have posted here. I have been swamped with some papers I am trying to get out, finishing up the dissertation, and interviews (faculty ones in addition to others). I should have some big news in the next couple of weeks regarding this last activity. But something spurred me to take a break from this process and post today.

The Book Blog recently provided a link to Baseball Analytics claiming a huge increase in strike calling by umpires over the past 4 years. However, this is a somewhat questionable finding. Before reading on, go there and check out the discussion already taking place. Then come back.

I also ran into this "huge discovery" earlier last year when trying to come up with a topic for my Baseball ProGUESTus post. I spoke about the finding with Mike Fast, and we quickly realized (more Mike than I) that, rather than the umpires becoming more accurate within the strike zone, it was the stringers creating the "sz_top" and "sz_bot" measurements who were actually getting better over time. I talked briefly about this problem HERE, and temporarily took down my original umpire strike zone calculations because of that. As an example of the bias, below I have the strike rate of pitches within the rulebook zone using a fixed zone and the stringer-provided top and bottom of the zone numbers:

Fixed Zone:
2008: 86.08%
2009: 85.90%
2010: 86.78%

Stringer-Provided Top & Bottom:
2008: 79.99%
2009: 82.20%
2010: 85.55%


From the above fixed zone, we'd expect about a 0.034 to 0.060 increase in run scoring per game (or 0.017 to 0.030 per team per game) when accounting for the number of pitches that we expect to change from a ball to a strike here (between 550 and 970 per year total). Keep in mind this is a very rough estimate, and does not account for changing behavior of pitchers or batters. But that's about a factor of 10 smaller than the estimate found with the stringer data (and the one that Baseball Analytics reports). So we should be wary about these numbers.

So, we can see here that one really needs to use a consistent top and bottom of the strike zone to ensure we don't see weird changes like this due to something other than changes in umpire behavior. That's not to say that there hasn't been any change (and I suspect that younger umpires are better than their older counterparts partly due to the extensive technological monitoring and performance training they must go through) but the 5 percentage point increase in strikes within the zone is well above what that change really is.

Another criticism of this is only calculating changes in strike calling on pitches within the zone. If umpires also decrease the number of strikes called on pitches outside the zone, then the net change in run scoring could be zero. Rather than calling more strikes, umpires could simply be getting better at their jobs. If anything, the latter is the most likely choice, given the data I have. So let's take a look at the fixed zone strike percentage on pitches that are outside of the rulebook zone:

Fixed Zone:
2008: 11.84%
2009: 11.51%
2010: 11.39%

Aha! So any increase we see on in-zone strikes tends to be cancelled out by a decrease in out of zone strikes. This change amounts to about 0.076 runs per game total (or about 0.038 per team per game) since there are more than twice as many pitches outside the zone than within that are called by the umpire.

That's interesting. But this doesn't explain everything. There could be a decrease in the quality of pitches outside the zone over time. And if pitchers now that they'll get more strikes well outside the zone, they may try to nibble way out there more often. We'll see that this might be going on a bit later. But note that using a discrete measurement also may be an issue. Not every pitch within the rulebook strike zone is created equal, nor is every pitch outside of it. There are varying degrees of strike likelihood depending on how close the pitch is to the edge of the zone.

To be clear, I think there is still something going on. I don't believe it is anywhere near the effect size reported at Baseball Analytics. But there is certainly plenty of good reason to think monitoring and training using these advanced technologies is improving umpire performance. In fact, I believe we see this training taking hold for those younger umpires coming up through the ranks. This is, of course, a VERY interesting effect. But it almost certainly does not account for any huge change in run scoring.

So I figured I would go a little deeper. Below I have mapped out and measured the size of the strike zone across 2008, 2009 and 2010. These are maps I have used before, employing cross-validated smoothing parameters in order not to overfit. The contours tell you the boundary at which--within that contour--pitches are called strikes at least 50% of the time. In the tables, I map out the area of each contour, as well as the area within each contour. This will provide some evidence as to WHERE the umpires are changing their strike calling behavior, if they are at all.


As you can see, there are some slight changes. Right handed batters do seem to be getting more low strikes called against them. However, the net change is nearly zero once we account for the fewer strikes being called on the outside of the plate. We see a smaller change for lefties low and outside; however, it seems that the inside strike is being called less often against lefties.

But above I only plot the 50% contour, and the size is rather ambiguous. Luckily, we can actually measure the size of this zone in R (HOORAY R!). You have seen Josh Weinstock do this in the past, so the measurement is nothing new. We can do this at all the different contours to see if the umpire is changing on pitches down the middle, just those on the edges, or perhaps those on the well-outside edge of the previous zone. Below I have the 30% through 90% contour zone sizes from 2008 to 2010, and the change in each from year to year.

RHB RHB RHB RHB RHB RHB RHB RHB RHB RHB
Zone Size (sq. in.)
10%

20%

30%

40%

50%

60%

70%

80%

90%
2008 672.77 586.56 530.90 485.95 445.19 404.87 361.54 309.86 235.65
2009 670.73 582.44 525.40 479.47 438.05 397.45 354.37 303.80 232.76
2010 681.09 594.13 535.39 487.17 443.46 400.94 356.69 306.37 238.80

Changes

10%

20%

30%

40%

50%

60%

70%

80%

90%
2008 to 2009 -2.04 -4.12 -5.50 -6.48 -7.14 -7.42 -7.17 -6.06 -2.89
2009 to 2010 10.36 11.69 9.99 7.70 5.41 3.49 2.32 2.57 6.04
2008 to 2010 8.32 7.57 4.49 1.22 -1.73 -3.93 -4.85 -3.49 3.15

Percent Changes

10%

20%

30%

40%

50%

60%

70%

80%

90%
2008 to 2009 -0.30% -0.70% -1.04% -1.33% -1.60% -1.83% -1.98% -1.96% -1.23%
2009 to 2010 1.54% 2.01% 1.90% 1.61% 1.24% 0.88% 0.65% 0.85% 2.59%
2008 to 2010 1.24% 1.29% 0.85% 0.25% -0.39% -0.97% -1.34% -1.13% 1.34%












LHB LHB LHB LHB LHB LHB LHB LHB LHB LHB










Zone Size (sq. in.) 10% 20% 30% 40% 50% 60% 70% 80% 90%
2008 658.93 575.93 521.70 477.83 437.93 398.50 356.20 306.04 235.00
2009 657.55 575.06 521.14 477.31 437.35 397.69 355.00 304.15 232.16
2010 675.05 587.10 527.48 478.58 434.54 392.08 348.32 299.01 233.88

Changes

10%

20%

30%

40%

50%

60%

70%

80%

90%
2008 to 2009 -1.38 -0.87 -0.56 -0.52 -0.58 -0.81 -1.20 -1.89 -2.84
2009 to 2010 17.50 12.04 6.34 1.27 -2.81 -5.61 -6.68 -5.14 1.72
2008 to 2010 16.12 11.17 5.78 0.75 -3.39 -6.42 -7.88 -7.03 -1.12

Percent Changes

10%

20%

30%

40%

50%

60%

70%

80%

90%
2008 to 2009 -0.21% -0.15% -0.11% -0.11% -0.13% -0.20% -0.34% -0.62% -1.21%
2009 to 2010 2.66% 2.09% 1.22% 0.27% -0.64% -1.41% -1.88% -1.69% 0.74%
2008 to 2010 2.45% 1.94% 1.11% 0.16% -0.77% -1.61% -2.21% -2.30% -0.48%


You can see that, overall, the zone size isn't changing at the huge rate suggested at Baseball Analytics. In fact, within the defined zone the strike rate is somewhat decreasing. What is very interesting, though, is that umpires DO tend to be calling more pitches well outside the strike zone, with an increase of about 1% to 1.5% in the size of the outer edges of the zone. This is not a trivial change, and the majority of it DOES seem to be coming from the low strike, as you can see below. The strange thing is that this seems to contradict the in-and-out-of-zone numbers cited early on in this post. That likely means there's something going on in between these contours.


One thing to remember is that these contours do have confidence intervals. And it could be that the CI's get larger as we get further out toward the 50%, 40%, 30%, 20% and 10% contours, since this is where the most variation comes in across umpires. Therefore, the differences we see should be attenuated somewhat to account for this uncertainty. I haven't plotted the CI's here because they'll just make things confusing to look at. But you must remember that these contour lines are not the end all of the conversation on how the zone is being called. I think my method gives the best estimate that we can really get from this type of data, but that doesn't mean it is anywhere near perfect.

Also, keep in mind I have not done this by count or pitch type, so everything is pooled together. So, if more of a certain type of pitch is being thrown, this could affect our results (and ultimately mean that umpires aren't changing their behavior, it is the pitchers who are throwing more of certain types of pitches that umpires are more likely to call strikes outside the zone). Or, if umpires are changing behavior differently in different counts, we won't pick this up and it means they are changing their behavior in some way that creates only a very small net effect when averaging across all of them. Certainly that would be the next step in the analysis, but I just don't have the time right now. And once we start cutting up the data into smaller sample sizes, there are issues in the reliability and comparability of zone measurements across these very different sample sizes.

But we can see if pitchers tend to throw more to this area by taking the percentage of pitches thrown between each contour (i.e. between the 10% and 20% contour, between the 20% and 30% contour, etc.). Doing this, we'll want to use the 2008 strike zone to predict the probability of our 2010 pitches. That way, the contours are comparable. Additionally, we want to apply this model to ALL pitches thrown, not just those called by the umpire. This is because there could be changes in contact and swing rates, and we're just interested in the pitchers' behavior.

But, if pitchers in 2010 are throwing more to the 2008 10% and 20% contours, then we may be able to say that pitchers are trending toward throwing to these areas where the umpire seems to be expanding the zone some bit. Below, I have the changes across time for the areas that pitchers are throwing to:

RHB RHB RHB RHB RHB RHB RHB RHB RHB RHB

Pitches Seen in Area
10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70-80% 80-90% > 90%
2008 18,674 13,458 11,880 11,408 12,179 13,972 18,092 28,819 115,688
2009 18,673 13,379 11,746 11,482 11,745 13,728 17,926 28,864 116,928
2010 19,473 13,800 12,139 11,841 12,677 14,326 18,689 30,137 120,643

Rate
Thrown To


10-20%


20-30%


30-40%


40-50%


50-60%


60-70%


70-80%


80-90%


> 90%
2008 7.65% 5.51% 4.87% 4.67% 4.99% 5.72% 7.41% 11.80% 47.38%
2009 7.64% 5.47% 4.80% 4.70% 4.80% 5.62% 7.33% 11.81% 47.83%
2010 7.67% 5.44% 4.78% 4.67% 5.00% 5.65% 7.37% 11.88% 47.55%

Change

10-20%

20-30%

30-40%

40-50%

50-60%

60-70%

70-80%

80-90%

> 90%
2008 to 2009 -0.0001 -0.0004 -0.0006 0.0002 -0.0018 -0.0011 -0.0008 0.0000 0.0045
2009 to 2010 0.0004 -0.0003 -0.0002 -0.0003 0.0019 0.0003 0.0003 0.0007 -0.0028
2008 to 2010 0.0003 -0.0007 -0.0008 -0.0001 0.0001 -0.0008 -0.0004 0.0007 0.0017

Percent Change

10-20%

20-30%

30-40%

40-50%

50-60%

60-70%

70-80%

80-90%

> 90%
2008 0.13% 0.71% 1.25% -0.52% 3.68% 1.87% 1.04% -0.03% -0.95%
2009 -0.48% 0.62% 0.42% 0.63% -4.00% -0.55% -0.45% -0.60% 0.59%
2010 -0.35% 1.32% 1.67% 0.11% -0.17% 1.33% 0.59% -0.64% -0.36%










LHB LHB LHB LHB LHB LHB LHB LHB LHB LHB

Pitches Seen in Area
10-20% 20-30% 30-40% 40-50% 50-60% 60-70% 70-80% 80-90% > 90%
2008 14,073 10,126 8,883 8,645 9,254 10,250 13,191 20,763 86,135
2009 14,909 10,700 9,459 9,348 9,645 11,092 14,090 21,974 91,871
2010 14,291 10,218 8,970 8,612 9,174 10,486 13,464 20,813 86,686

Rate Thrown To

10-20%

20-30%

30-40%

40-50%

50-60%

60-70%

70-80%

80-90%

> 90%
2008 7.76% 5.58% 4.90% 4.77% 5.10% 5.65% 7.27% 11.45% 47.50%
2009 7.72% 5.54% 4.90% 4.84% 5.00% 5.74% 7.30% 11.38% 47.58%
2010 7.82% 5.59% 4.91% 4.71% 5.02% 5.74% 7.37% 11.39% 47.44%

Change

10-20%

20-30%

30-40%

40-50%

50-60%

60-70%

70-80%

80-90%

> 90%
2008 to 2009 -0.0004 -0.0004 0.0000 0.0007 -0.0011 0.0009 0.0002 -0.0007 0.0008
2009 to 2010 0.0010 0.0005 0.0001 -0.0013 0.0003 -0.0001 0.0007 0.0001 -0.0014
2008 to 2010 0.0006 0.0001 0.0001 -0.0005 -0.0008 0.0009 0.0009 -0.0006 -0.0006

Percent Change

10-20%

20-30%

30-40%

40-50%

50-60%

60-70%

70-80%

80-90%

> 90%
2008 to 2009 0.52% 0.77% 0.01% -1.54% 2.13% -1.62% -0.31% 0.62% -0.16%
2009 to 2010 -1.30% -0.92% -0.21% 2.64% -0.52% 0.10% -0.98% -0.09% 0.29%
2008 to 2010 -0.77% -0.14% -0.21% 1.14% 1.62% -1.52% -1.29% 0.52% 0.13%


All in all, the table above seems rather ambiguous, but I'd be interested in hearing any patterns that others see here. RHB have been seeing more pitches at the 20% to 40% contours, while LHB have been seeing more at the 40% to 60% contours. Of course we would also have to understand if batters s are changing their behavior that affects run scoring in a more significant way than we would expect due to the lower strikes outside the zone or any of the changes in the table above. But given that we're talking about so few pitches in terms of overall ball-to-strike changes (or vice versa), I am going to be cautious about making any large statements about the effects of this on the run-scoring environment.

Lastly, what I think could also be going on is these younger umpires coming into the league. Umpires are being trained more and more using pitch f/x type technology and use it for learning missed calls, problems in their own strike zone, and so on. They get reports for their games from the umpire's association as they come up through the minor leagues. I think this should have a real effect on strike calling behavior, likely meaning that younger umps call strike closer to the rulebook zone. As a rough comparison, below I have Mike Estabrook (a younger umpire) and his zone compared to, say, Jerry Crawford. Now, this is only two umpires and a small sample, but there could be something to the idea that a younger umpire like Estabrook is willing to form his zone to the rulebook, as opposed to Crawford who essentially has tenure as an MLB umpire. Keep in mind that the below is only two umpires, and we'll probably need a few more years of data to detect any changes for younger umpires vs. older ones.





So that's all I have for today. I have spent way too much time on this, but please provide comments if you have thoughts, criticisms, or flat out think I'm an idiot. There is certainly more to say than what I have here.

NOTE: At the suggestion of Tango, I provided some additional information below regarding the size of the strike zones which I have used in a recent academic paper I have under review. In this case--rather than use square inches--I report the approximate number of baseballs that could fit side-by-side through the given area if it were, say, an actual square rather than strips of changes around the zone (a baseball is about 8.4-8.5 square inches, or a 2.9-by-2.9 inch area, the diameter of the ball). So, for example, 81 baseballs means a square 9 baseballs by 9 baseballs. Hopefully, this will help to visualize the size changes in the zone in a context relevant to the discussion, as I think Tango makes a very good point.

RHB RHB RHB RHB RHB RHB RHB RHB RHB RHB
Zone Size (in baseballs) 10% 20% 30% 40% 50% 60% 70% 80% 90%
2008 80.00 69.75 63.13 57.78 52.94 48.14 42.99 36.84 28.02
2009 79.75 69.26 62.47 57.01 52.09 47.26 42.14 36.12 27.68
2010 80.99 70.65 63.66 57.93 52.73 47.67 42.41 36.43 28.39

Changes (in baseballs)

10%

20%

30%

40%

50%

60%

70%

80%

90%
2008 to 2009 -0.24 -0.49 -0.65 -0.77 -0.85 -0.88 -0.85 -0.72 -0.34
2009 to 2010 1.23 1.39 1.19 0.92 0.64 0.41 0.28 0.31 0.72
2008 to 2010 0.99 0.90 0.53 0.15 -0.21 -0.47 -0.58 -0.41 0.37


LHB LHB LHB LHB LHB LHB LHB LHB LHB LHB
Zone Size (in baseballs) 10% 20% 30% 40% 50% 60% 70% 80% 90%
2008 78.35 68.48 62.03 56.82 52.07 47.38 42.35 36.39 27.94
2009 78.19 68.38 61.97 56.76 52.00 47.29 42.21 36.17 27.61
2010 80.27 69.81 62.72 56.91 51.67 46.62 41.42 35.55 27.81

Changes (in baseballs)

10%

20%

30%

40%

50%

60%

70%

80%

90%
2008 to 2009 -0.16 -0.10 -0.07 -0.06 -0.07 -0.10 -0.14 -0.22 -0.34
2009 to 2010 2.08 1.43 0.75 0.15 -0.33 -0.67 -0.79 -0.61 0.20
2008 to 2010 1.92 1.33 0.69 0.09 -0.40 -0.76 -0.94 -0.84 -0.13

Friday, February 10, 2012

Bill James on Dwight Evans

Bill James has an article up at Grantland lobbying for Dwight Evans being voted into the Hall of Fame. He's right, and not just from a sabermetric standpoint.

My paper at JQAS with Steve Salaga argues exactly the same point (actually for both Darrell and Dwight Evans, but Darrell isn't eligible any longer). However, we take a non-saber look at things and use the traditional statistics that we all know BBWAA voters love. Of course, we run a rather complex technique, but we still use these basic statistics. What do we find?

Well, even by the BBWAA's own criteria (based on their past voting behavior), Dwight Evans should be voted in. When we compare him to others in our analysis, he comes out ahead of Mark McGwire (sans-steroids, he's a sure thing), Barry Larkin (fielding is a weak point of our study), Joe Carter, and Dave Parker. And just behind Mike Piazza.

That means that--given how voters have behaved before--Evans should be in. If voters' own preferences toward traditional statistics say he should be in (without even accounting for Evans' great fielding!). And if Bill James's sabermetric thoughts think he should be in. Then why the hell isn't he in?

Hat Tip: Tango