America’s Pastime or America’s Snoozetime

First off, congrats to the Atlanta Braves on their World Series win a couple weeks back. A really fun team to watch once my hometown Red Sox got eliminated. At least the team with ties to Boston managed to come out on top in the end. We’ve had some really good debates in this class throughout the semester about how digital transformation, big data, and artificial analysis can bring out the best within an organization yet also at times cause some unintended consequences. Baseball I think happens to be a great real-world example of where we see both the good and the bad. You’ve got the Moneyball crowd on one hand and the Trouble with the Curve crowd on the other (both worth a watch by the way).

First the good. Billy Beane’s approach with the Oakland Athletics throughout his tenure as general manager deserves a lot of praise. For those who don’t follow baseball, there is no salary cap, which differs from the other three major sport leagues (NFL, NBA, and NHL) so small market teams are often at a disadvantage over the big market teams because they can’t afford the best players. Throughout the past two decades and particularly for a stretch throughout the early 2000s, the Oakland Athletics defied expectations and had some very successful teams despite having a payroll that was in the bottom third of MLB teams. Sadly they have yet to be able to get over the hump and make it beyond the first round of the playoffs. Beane and his team used Sabermetrics (SABRmetrics) to essentially help identify traits to capture players based on low valued stats vs high valued stats. Beane based this approach primarily on two main statistics: On-Base Percentage (OBP) which is the frequency for which a hitter gets on base and Slugging Percentage (SLG) which is the total number of bases recorded by at bat. Combining these two statistics you get On-Base plus Slugging (OPS) which is what the Athletics used to make a lot of decisions. Beane valued getting on base rather than other high valued qualities like speed and power and was able to turn this methodology into wins for his team.

Beane’s analytical prowess caught the attention of other organizations within the MLB (he actually turned down a lucrative offer for the Red Sox GM role). Other MLB organizations, building on to Beane’s approach, begin using similar methods to build their rosters. The Red Sox roster in their curse reversing 2004 season was largely a mix of stars and relatively unknown players. Johnny Damon famously referred to the team as a bunch of idiots. In the years since teams throughout the league have started to focus heavily on analytics with many teams having full departments dedicated to analytics to look at various aspects of the game in order to build rosters and even develop methods for game management.

Now for the bad. Has data analytics become too involved with the game? Take a look at the St Louis Cardinals. Manager Mike Shildt was let go as manager after the conclusion of their season. This was a playoff team that won 90 games during the season which included a win streak of 17 in a row, one of the longest streaks in the modern era. Rumor has it that a rift between Shildt and the analytics department ultimately led to his dismissal. Analytics has become a focal point within team offices and one can argue it has started to create issues within the game itself. If you look at attendance for MLB games, its been in a slow decline throughout the past decade.

Beyond attendance, baseball has seen a number of problems that could come down to decisions with analytics. The shift in the infield by plate appearance has become more common. Back in 2012 infields shifted 4.62% of total plate appearances. In 2019 that percent increased to 21.17% of all plate appearances. As a result, hitters responded with analytics and started to mess around with their “launch angle” while swinging which impacts whether the ball is hit in the air or on the ground. In 2015 average launch angle was 10.1 degrees. It has increased each year since with average launch angle measured at 12.7 degrees in 2020. How do you think pitchers responded? That’s right analytics. The Tampa Bay Ray’s pitching staff countered by throwing more fastballs up in the zone to deter the effects of high launch angle. The Rays finished that year with the most strikeouts, fewest walks, and fewest home runs allowed. This brings up the fact that more players are striking out in general. The percent of strikeouts in the MLB has increased every year now since 2008 with strikeouts accounting for 23% of all plate appearances in 2019.

Analytics isn’t to blame for all of baseball’s woes. Pace of play is certainly an issue that is driving fans away from the game. Let’s be serious, nets don’t extend all the way down the baselines due to stronger players only. They’re there sadly because people are glued to their phones during what is at times a boring game with too much downtime. Fans are at times seeing games with more pitchers than hits and these issues are adding problems on top of some of the analytical issues I discussed earlier. On the counter argument one could argue that analytics help a team achieve the best chance of winning. After all the objective of the game is to win. But beyond that it’s also a business kept alive by the fan base. If fans aren’t as excited about the game it doesn’t bode well for the future of baseball. I do hope baseball figures it out because I’d hate to see the sport I grew up loving become obsolete in my lifetime.

14 comments

  1. I confess I’m not into sports, BUT I thought your blog brought up a very interesting question: When does analytics provide too much information? I understand why teams would want to maximize the amount of information to play a better game. I also understand why consumers would want less. At the end of the day, consumers go to games for the experience. They want to watch the game in real-time and play “back seat coach”. With only so much attention span, constant stats can take away from the experience.

    Great blog!

  2. Rob great post! It makes me wonder how “entertaining” winning is? At the end of the day, the decision to use analytics comes down to providing an advantage, which will hopefully lead to your team winning. So with that said, would you do everything in your power to win?

    Here’s a great article on The Braves choosing data over a possible World Series no hitter. I am not sure if they “right” choice.

    https://www.wsj.com/articles/atlanta-braves-houston-astros-world-series-no-hitter-11635595849

  3. This is a really fascinating topic, when do we say enough to the data analytics folks and go with our gut? If we look at the perspective of an owner, if a team does better, there are more playoff games, more seats and merchandise sold, more eyes on the team, and the fan base grows. However, the question is, will all that happen if your team is boring and calculated, will the fan base still grow? While not perfect analogies, the Patriots in the NFL and Spurs in the NBA are both considered boring, calculated teams with high success rates, yet they still have some of the biggest fanbases in their sports. Feels like DA is here to stay, so we better get used to baseball’s boring era.

  4. I love the narrative of your article and the way you came me engaged through it. Although I wasn’t exposed to baseball until I moved to the US, I learned to love the game, and I love going to the ballpark(my wife and I got engaged in Bleacher Bar right on Fenway). I don’t believe the nets affect the experience, and after watching the people that had to suffer permanent injuries from the accident. I don’t see the point of not having them, but I can see how the purest don’t love them. I will pitch clock being part of the game in the majors. Although analytics is a colossal part, it should be used as a tool, not a solution for all the problems!

  5. Really interesting post, Rob! Great job. Digital Transformation in sports is fascinating because there really is a limit. In just about any other industry, there’s at least a possibility for continued growth and the general acceptance that the work could be done by a robot. Sports, on the other hand, does not have such a possibility — there’s no way fans would go see a bunch of robots play baseball (I’d imagine there’d be no scoring?). Is the use of data in sports making players into constructive robots when, as you mention, they’re too calculated? Something I haven’t thought about before, but really quite fascinating.

  6. Interesting post. I did indeed watch Moneyball and found it particularly interesting as I had no clue how much analytics were used in Baseball. With this said, I think the game is relatively slow, and coming from Europe, I still struggle to understand the rules. However, I wonder, is it analytics driving fans away, or is it something else? I believe a combination of things such as an older fan base, increased competition from other sports, and a general indifference brought on by a long season have helped shrink the sport’s following.

  7. Such a controversial topic in the baseball realm right now! Let a pitcher pitch, or stick to a pitch count? I think that if a pitcher is dealing, let him deal, but it’s tough to not go with the data. I really liked your statistical analysis on how teams are pitching and what they’re letting their pitchers throw. I think this is a great example of a digital transformation! Great post!

  8. The amount of revenue that the sport brings in is not going away. I just see them failing to grow at the same rates as the other sports. I also wonder if the risk of alienating the hardcore traditionalists in worth the uphill battle of trying to make the game faster.

  9. Just an extremely well-written blog from beginning to end. The controversy of technology being integrated into sports and impacting viewership is a definite catch-22. I certainly feel that analytics are a much better path to go down for teams trying to win a championship, but I also feel that for certain players, stats don’t do them justice. Pujols has been great throughout most of his career, but awful in recent years. That doesn’t mean Pujols can’t hit a dinger out of the park in clutch moments. Heck, fans might be drawn to come to watch a childhood icon rather than the team itself. Baseball will figure out how to monetize different points of engagement, but a loyal fanbase and attendance will never become obsolete, at least for professional teams in the US.

  10. I’m a long term ATL fan, and I had to DVR through most of the game (which made it way more interesting). Face it, Baseball is really a game that you do while you’re doing something else. I’m not sure it can be made more exciting.

    In fact, there’s a classic Robin Williams bit about the need for players to do drugs because the game is so slow. https://www.youtube.com/watch?v=Vv0FNBdLTdI

  11. My friend in college would talk my ear off about how baseball (particularly MLB) was really challenging to keep people’s attention for giving the stop and start nature of the game and only people who really understood what was going on would benefit from the game analysis and enjoy the game (in his defense, he played through high school and then became a non-athletic regular person). If explained correctly and concisely, this may be an addition to helping understand the game, why certain things are exciting, and how games are a nail biter rather than just traditional rankings. Of course, all of this is said with a grain of salt since my favorite part is the hot dogs and the singing.

  12. Great post Rob! I definitely agree that baseball seems to be a sport more on the analytical side compared to other professional sports. I can personally say that unless its a crucial game or playoffs, I typically won’t bother putting baseball on the TV. So even though teams are are getting better, especially with pitching, it doesn’t feel as exciting as it used to. Hopefully there is some change up in the formula that can take the game in a more exciting way soon.

  13. Love this post & topic. A few other considerations when thinking of the digital aspects of baseball. First off is the ability to analyze opposing teams & players, such as what pitch is most likely in a given count, or the way defenses utilize shifts. Another factor is the introduction of a robotic umpire similar to what you see in games like tennis. This would dramatically reduce the number of incorrect balls & strikes and perhaps speed up the game.

  14. Baseball seems to always get in its own way. Interesting how analytics has shaped so much of how the game is played today. Such as shifts and teams much more heavily relying on the bullpen in important playoff games.

    I did a research project on baseball’s attendance and engagement issue in another class last year. One finding that I came across that was a major issue was MLB’s approach to social media. In the early 2010’s MLB refused to allow fans or any third-parties to post their videos on Twitter or any other social media feeds. They wanted to force all views to be on their main pages. This was a terrible decision as leagues like the NBA were allowing their content to be shared around the world.

    Hopefully baseball can learn from its past mistakes and become a treasured sport in this country once again.

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