Category: sports

The Gongaga T-Shirt

I have this great Gonzaga Bulldogs t-shirt that Kelly got for me a while back. It is a soft, comfortable t-shirt and I wear it fairly frequently because I like it a lot.


The thing about the t-shirt is that is a natural magnet for questions, the first of which always seems to be “Did you go to Gonzaga?” No, I didn’t.

The next question, naturally, is “Are you a fan?” Yes, I am. The thing is, I could not name a single player on Gonzaga or tell you how they are ranked or what their record is. In fact, I don’t think I’ve ever seen a single game.

I am a fan of Gonzaga because it is the alma mater of Bing Crosby, of whom I am also a very big fan. I’m a baseball fan and I don’t follow the NBA, let alone college basketball, but when the subject comes up, I always offer that I am a Gonzaga fan to avoid killing the conversation. I sometimes have to explain why I am a fan, and now I have a post to which I can point people.

Play Ball!

Baseball is back and so I know it must be spring, despite the fact that it is unusually cold here (I don’t think it supposed to break 45 F today). Two days into the regular season and I haven’t watched a game yet, but I’m keeping my eye on things:

  1. The Yankees lost their opener to the Red Sox, which delighted many, if not most of my friends and family. The Yankees are playing with a lot of injuries–as one might expect from an older team. I think its way too early in the season to draw any conclusions1.
  2. Houston is now in the American League, and every division now has 5 teams, meaning that we get interleague play throughout the season. The Angels play the Reds today, for instance. So that’s a bit different.
  3. The Texas Rangers were one out away from a perfect game yesterday. That’s pretty remarkable.
  4. And Robinson Cano fired Scott Boras and hired Jay-Z.

I thought I might catch the Yankees game tonight, but it looks like I might actually make it to a writers group meeting instead, but I’ll get around to watching a game soon enough. And besides…

This Sunday, the Little Man has his first t-ball practice and that should be a lot of fun. More on that next week.

  1. And yes, I’d be saying the same thing if the Yankees had won that game.

Superbowl Sunday

I am not a football fan. I’m a baseball guy and that’s pretty much it. When I lived in Los Angeles, I’d spend my Superbowl Sunday’s at Disneyland because the park wasn’t particularly crowded on that day. These days, Superbowl Sunday is, for me, no different than any other Sunday. I’m taking the Little Man to his swimming lesson this morning, making sure he gets a nap in this afternoon. I’m going to try to get in some work on a new story. And I’ve got a ton of reading that has piled up.

We have no plans to attend Superbowl parties or other game-related festivities. If the Giants were in the Superbowl, I might check the score every now and then, but I don’t plan on doing that this evening. I’ll find out who won when I get into the office tomorrow, I’m sure. Especially if the Ravens win. And I’ll say for the record that while I am not a fan of the game, if I had to pick a team that I wanted to win, it would be the Baltimore Ravens, and not just because they are named after an Edgar Allen Poe poem. It’s just that I simply can’t stand the San Francisco 49ers. (I can’t stand the San Francisco Giant in baseball, either.)

The best part of Superbowl Sunday for me is that it means that after today, football will be over and we’ll find ourselves only a few weeks away from the beginnings of spring training. Players will start to report, the weather will gradually start to warm up, and before you know it, opening day will be just around the corner.

A Sad Day for Baseball

Yesterday, baseball lost two of its stars. Early yesterday, it was reported that Earl Weaver, former long-time manager of the Baltimore Orioles had passed away at 82. And then as I was heading off to bed last night, I learned that Cardinal’s great, Stan Musial, had passed away at 92. It’s a sad day for baseball, losing two great members of the baseball family. On the other hand, both men lived long lives, doing what they loved. I like what Musial said to Sports Illustrated back in 1963:

Maybe one reason I’m so cheerful is that for more than 20 years I’ve had an unbeatable combination going for me — getting paid, often a lot, to do the thing I love the most.

A 20-Step Plan for My Baseball Century Experiment

Back in August, I wrote a post about my Baseball Century Experiment. I haven’t had much of a chance to do actual work on it, but in the months since, I’ve done a lot of reading, particularly on the science of sabermetrics, and I now have a plan, at least, for moving forward with this little experiment. I explained some of my reasons for doing this in my original post, and a few people pointed out that there was already software out there that does this, so why reinvent the wheel? I have a couple of thoughts on this:

The first, and most important reason, for me, is to learn. Sure, there is software out there that can do this, but it exposes only the results. I’m interested in the internal mechanics of how such a piece of software might work. This helps me in 3 different ways:

  1. It allows me to make a deeper exploration of baseball by implementing it as a simulation myself.
  2. It allows me to dive deeper into a development package–in this case, Mathematica–that I want to know better.
  3. It allows me to tinker in ways that I could not do with off-the-shelf software.

Second, I’ve looked at the software that is out there. The top-of-the-line appears to be Out of the Park Baseball. Not only did I look at this, but I bought a copy for my Mac and played around with it a bit. It gets to some of what I am looking to do, but not all of it. I’m not (at the moment) interested in human management in the game. I’m currently more interested in simulating human management through some basic game AI. That is part of the fun for me.

Third, I’m not interested in developing the kind of elaborate interface that OOTP has. My simulation will be entirely text-based. My ideal output and presentation layer would be something akin to WolframAlpha, for baseball, where you could type in some natural language queries and get a boatload of results, charts, graphs, numbers, etc. But at the simplest level, I’m satisfied with producing text-based box scores, play-by-plays, rosters, lineups, standings, etc.

Fourth, I’m not interested in using real players. Part of the point is to think of this as almost an alternate history to baseball. Fictional players, randomly generated, moving through careers based on statistically valid simulations.

The ultimate goal of my initial1 experiment is to be able to simulate 100 continuous seasons of baseball, and then look at the resulting number and see who are the leaders? Did anyone every hit .400 in a season? Did anyone break a 56-game hitting streak? Who is the home run kings and what is the record? Did any pitcher throw a perfect game?

My approach to all of this is starting very simple and layering on more and more complexity. Over the last several weeks, I have drawn up a plan for how I will approach this. It looks something like this:

1. Develop a simple player generator

Since I’m not using real players, I need a way of bootstrapping players. One of the tools I will need to create, therefore, is a player generator. As with all the tools I’ll need to develop, my plan is to start simple and layer on complexity over time. The simple version of the tool will generate names, positions, and some basic stats for the players. My present approach for generating the stats will be to assume a standard bell curve for a statistic and randomize the stats based on a normal distribution. This probabilities of such a distribution would allow for an appropriate relative generation of “average” players to “superstars” and to players who don’t perform so well. Put another way, there would be a lot of values (say, batting averages) that have small deviations from the mean average. There would be very few that are far better or far worse.

Not a perfect solution but it allows me to bootstrap some basic statistics in a fair way without the need to borrow from real player numbers.

2. Develop a simple team generator

The team generator in this instance is a way of picking out the players needed to create a roster of n people, with all of the necessary slots fills (so many pitchers, so many fielding positions, etc.) from the pool of available people. In a more complicated version, the team generator would be a kind of AI scout or GM, looking at what is available and getting the best that it could. But that is way down the line. Right now, I’m simply looking to be able to create teams out of the players generated in #1.

3. Develop a lineup generator

Again, we are talking simple here. In a more complex version, the lineup generator would be part of the manager AI function. For now, I’m looking to produce the best possible lineup with the data available. In its most simple terms, this is likely a fairly simple two-part problem:

  1. Identify a team player for every position.
  2. For each position, sort the players by OBP (on-base percentage) and then choose the best OBP for the given position.

At this point, the pitcher almost doesn’t matter

In future versions, I’ll probably also look at some more advanced sabermetrics statistics, but this is good enough for now.

4. Simulate a match-up using simple BLOOP methodology

BLOOP is a method of simulation that sabermetricians have used quite a bit. It’s fairly simple. It involves calculating the probability of various outcomes based on the hitters stats. A more sophisticated version normalizes these calculations based on the pitcher they are facing and across the league, but for now, I’m keeping things simple.

Read more

  1. And I expect that over time, there will be more than one experiment.

This Year’s Baseball Hall of Fame Ballot

Later today, the Baseball Writers Association of America will come out with their Hall of Fame ballot for 2013. I have a feeling that for only the third time since 1965, there may be no one on the list. Included among the eligible candidates this year are Roger Clemens, Barry Bonds, and Sammy Sosa. While all three have Hall of Fame numbers, all three of their characters are called into question by the issue of steroids. In order to get into the Hall of Fame, a player must appear on 75% of the ballots cast.

I suspect that this year, these three names at the very least will not appear on the list. And it’s possible that no one will. And I am okay with that.

I agree with what Tom Verducci has written:

Voting for a known steroid user is endorsing steroid use. Having spent too much of the past two decades or so covering baseball on the subject of steroids — what they do, how the game was subverted by them, and how those who stayed away from them were disadvantaged — I cannot endorse it.

As a baseball fan, I remember watching with absolute excitement on the day that Mark McGwire hit the homerun that broke Roger Maris’ single-season homerun record. I just happened to get home from work early that day and turn on the ballgame. I couldn’t even sit down. It was thrilling. And it made it that much more disappointing when questions arose of his steroid use. I felt cheated, betrayed even. It wasn’t even disappointment that the record would now have a black mark. It was the damage done to the entire game. It has been a long road since then–fifteen years–and the damage still isn’t entirely healed.

It may be that Clemens and Bonds eventually get into the Hall of Fame. But, given their numbers, not getting in on their first year of eligibility sends a message that Cooperstown is about more than just the numbers1. And maybe, it will help finally bring to a close a disappointing era in the national pastime.

  1. And yes, players with character flaws have been voted into the Hall of Fame before. But that should not be a precedent we want to emulate.

Tigers Sweep Yankees in Four Games in the ALCS

Well, it would seem that nearly all of my predictions for the playoffs this season were wrong.

The final nail in the coffin was the Tigers easy sweep of the Yankees last night. I’m hard pressed to remember a time when I’ve seen the Yankee hitters slump this badly in a post season series. They just weren’t hitting. Period. The first three games were all close thanks to the Yankees pitching, which did a fine job. They simply got no offensive support. It was a dreadful disappointment. I was glad to see Joe Girardi benching players (like Alex Rodriguez) who were particularly opprobrious at the plate. But no one else seemed to be able to step it up. About the only two people hitting consistently on the team were Jeter and Ichiro, and of course, Jeter went out with a broken ankle.

At this point, it looks as if the World Series will be an entirely central division affair, Detroit vs. St. Louis. I’d rather see St. Louis than San Francisco, that’s for sure.

And let me give credit to the Detroit Tigers. They were the team with the fewest wins leading a division when they came into the playoffs and they managed to beat some tough teams. Or at least, a team that was tough only a few weeks before.

Next season will be interesting with Houston moving to the AL west and the increase in interleague play.

Is it April yet?

“God, I Love Baseball”

I got to go to the third league division series game between the St. Louis Cardinals and the Washington Nationals yesterday at Nationals park. I’ve been to countless major league baseball games, but this was the first time I’ve ever been to an MLB playoff game. As it turns out, it was a somewhat historic game, the first home playoff game for a Washington team since 1933.

I’ve been to Nationals Park six or seven times before, but this was the most crowded I’ve ever seen it. I was lucky–my friend who gave me the ticket had Diamond Club seats: great seats, with all kinds of perks, but even so, the park was packed to the gills. Red rally towels were handed out to everyone as they came into the ballpark and when I looked around the stadium, it seemed that all I could see was red:


The Nationals lost–were really blown away by the Cardinals yesterday. In the last 2 games I think the Cards outscored the Nats 20-4. Still I diligently kept score throughout the game, although I did so on paper because I didn’t want to bring my iPad to the stadium. Here are my scorecards for those interested.

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Cardinals Scorecard for Game 3 NLDS

And here’s the Nats’ scorecard:

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Nationals Scorecard for Game 3 NLDS

Despite the Nationals now being down 2-1 against the Cardinals, yesterday’s game was a lot of fun for me. I might be a die-hard Yankees fan (and way to go Raul Ibanez for keeping us ahead last night!) but I am a baseball fan above all else. I love the game, I love the history, and I love watching the teams play. And what better time to watch then in the post season when we get to see the best teams square off against one another. It is really so much fun.

My Scorecard for the NLDS Nats vs. Cardinals Game 1

I like keeping score when I watch baseball. It makes me feel more in tune with what is going on in the game. In the past, I’ve kept score on paper like just about everyone else who keeps score. But I am always looking for more ways to go paperless. So yesterday, for the first time ever, I kept score on my iPad using an app called iScore. It was pretty easy to do, I was able to keep up with the game, and my stats matched those of the game as it progressed. One of the cool features of iScore is the ability to produce scorecards from your score-keeping, so here are my visitor and home team scorecards for yesterday’s NLDS game between the Washington Nationals and the St. Louis Cardinals:

nlds nats 1.PNG
Nationals Scorecard


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Cardinals Scorecard

The scorecard is not perfect, because I am still learning how to use the app. This was my first time. I had planned to keep score of the Yankees/Orioles games as well, but the rain delay made that impossible. It was on too late for me to stay up and watch, let alone keep score.

I like the fact that I can do these without paper, because it means I can begin archiving my scorecards in Evernote like I do for just about everything else.

My Post-Season Predictions for October

The MLB post season starts tonight with the wildcard eliminations games. After tonight, the Yankees (and Nationals) will know who they are playing. For what it’s worth, my prediction for the post season outcome is below. This isn’t based on any rigorous assessment. It is a combination of gut feeling personal wishes. Of course, being a Yankees fan, I always believe the Yanks will go all the way. This year, I think they’ll do it against Washington.

Playoff Prediction.png

Scorecard From My Yankees Inside Experience (Tampa at New York)

I’d meant to post my scorecard from the Yankees game I attended a few weeks ago, and never got around to it. So I present you with my scorecard today. Note that after the 6th inning, I went to get some ice cream and the line was long so I didn’t get back to my seat in time to record a half-inning. At that point, I decided to give up. But most of the game is here, for those interested in seeing my slightly nonstandard method of scoring.

Here is Tampa’s scorecard:

Scorecard 1.PNG

And here is the Yankees scorecard:

Scorecard 2.PNG