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1-Page Summary of Astroball
Overview
Ben Reiter’s book Astroball: The New Way to Win It All (2018) tells the story of how the Houston Astros went from being one of the worst teams in baseball to winning a World Series. He first predicted this on Sports Illustrated, and after three years they won it all. His book details their unlikely turnaround with an inside look at what made them so successful. They used analytics and data-driven management techniques to beat opponents while also having players who were dedicated and willing to change their playstyle for success.
Baseball is a sport where stats matter, but it’s also built on tradition. The Astros team and their managers were able to overcome this by using analytics to inform all of their decisions. They used data even when there was criticism or doubt about the outcome. For example, they signed star pitcher Justin Verlander before the playoffs because he was expensive and not guaranteed to work out—but ended up being a key contributor in winning games.
The Houston Astros use data analytics to make better decisions. They have a team of analysts who are passionate about baseball and they have recruited players who were overlooked or underestimated in the past. Their process helps them decide things like when to promote certain players and what trades to make, while also allowing room for collaboration and human intuition. The results of their system revolutionized baseball, so it can be applied elsewhere as well. Michael Lewis’s book Moneyball (2003) made data manipulation essential for sports teams, but Reiter’s story updates that formula for a new era where humans collaborate intensely with data to achieve higher levels of success.
Key Point 1: People often make decisions based on intuition, which is a powerful blend of emotion and bias. But intuitive decisions are not always beneficial for their long-term self-interest.
Jeff Luhnow got his start in baseball with the St. Louis Cardinals, where he headed up their scouting department and focused on drafting top talent. One thing that stuck out to him was a draft choice between two players: one who was more athletic but not as skilled, and another who had less athleticism but more potential skill. He chose the player with less athleticism, which ended up being a bad decision because this player did not end up succeeding at all compared to the other player’s success. This taught him something about how he should run his team when he became general manager of another team—the Houston Astros—which is that data can be very important in making decisions about what players to choose for your team based on their performance statistics or metrics rather than just relying on traditional scouting methods like looking at a player’s physical appearance or judging them by watching them play for only a short period of time.
In decision-making, intuition can be powerful. However, it’s hard to define exactly what it is and how people use it. A 2017 study from the Journal of Developing Ideas found that people exercise intuition when they analyze “specific bits of data combined with past experience.” This usually happens unconsciously. People rely on their experiences in order to make choices based on those experiences. For example, if someone has a negative experience at one car dealership, he or she will probably choose not to go back there for another purchase even if he or she chooses a different dealership the next time around.
The author provides advice on how to overcome biases in decision-making. She says that one of the most important steps is to understand where these biases come from, and she offers tips for doing so. This includes asking questions about why a person or situation triggers an uncomfortable feeling, as well as looking closely at cognitive biases such as anchoring bias, which means giving more weight to the first idea presented even when additional information has been provided. By understanding where these feelings and thoughts originate, we can make better decisions by viewing all options objectively and choosing what’s best overall.
