Astroball by Ben Reiter Book Summary


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A sport is formed by passion and instinct. The success in the game depends on courage, determination, and raw talent and this particular message can be reflected by people who are fans in the stadium, dedicated players or grizzled old-school coaches pacing the sidelines, and who live and breathe sports.

However, this is changing today. Something we do not associate with sports is increasingly embraced by top clubs: Math.

Let’s consider Houston Astros, a baseball outfit who has a sudden increase from mid-table mediocrity to World Series champion was directed by a managerial revolution. There were two forward-thinking innovators in its heart; The Californian data analyst Sig Mejdal and scout Jeff Luhnow who realized that baseball can be understood statistically as in the other games.

Mejdal and Lunhow began following the data by considering ‘’gut instinct’’ which means opposition from skeptics and proponents of good old and the results were fascinating. Soon enough, the Astros were playing in the market and signing talents who were overlooked but had unique skills to set laid the foundations for the club’s title-winning season in 2017.

As for games, the data is better than your gut.


A California student and future NASA engineer, Sig Mejdal, paid for college expenses by working night shifts at a casino in the late 1980s. When he realized the idea that gamers usually trust their gut over reasons, it was at the blackjack tables.

Blackjack is a probability game where the aim of the player is to defeat the dealer’s hand without own hand exceeding 21. There is always a statistically preferable option when choosing another card despite the players’ superstitions.



Suppose a player has a hand equal to 16. In most cases, s/he will be cautious about how to draw another card. As a result, the chance getting more than 21 is pretty high, right? Yes, but there is more. Actually, another card should be taken for the best move is told us by the reason. The dealer has a 74-percent chance of winning at least 17. However, when drawing another card, the chance of the player to lose is reduced to 67.5 percent!

This provided Mejdal to think that what would happen if the same logic is applied to other games. He began to take a closer look at baseball and his hypothesis appeared: Since baseball is a game just like any other, math might be more reliable than gut instinct.

Particularly, there was an understanding of dividend payment in one area: Player recruitment. It was proved by Mejdal in 2005 when he was an advisor to Jeff Lunhow, the scouting director at the Missouri-based St. Louis Cardinals. The best college player in the US was Stanford Cardinals’ Jed Lowrie according to Mejdal’s player performance metrics. The Scouts had literally missed Lowrie because of his lightness. He was too small and thin to be a big league player in the view of their instincts.

Lunhow trusted the advice of Mejdal and recruit Lowrie to the Cardinals team. And the result was that Lowrie was a highly capable all-star and defensive player in the shortstop position with a relatively dependable batting average of .262 in 2018.

A data-driven technological revolution continued to assess the players in 2012.


Scout Jeff Luhnow and his analyst Sig Mejdal started to work for Houston Astros in 2012. The duo was close to shaking up the events. It is now easy to compile more detailed performance metrics which allowed them to make more logical recruiting decisions.

In 2006, the video camera system PITCHf/x began to be used in all major league baseball games. It provides triangulation between three fixed cameras which provides calculation from the speed at which the ball is rotated to the point at which it was thrown, the strength of its rotation and the point at which it crosses the batting plate.



Collin McHugh, pitcher in the Colorado Rockies in 2013, was recruited by the Astros thanks to these data. Although his overall performance metrics were pretty average, there was an advantage to use that showed by PITCHf/x. He threw extraordinary curveballs with more than 2,000 revolutions per minute, way more than the average of 1,500 from time to time. The Astros took a risk and McHugh was put on the team by trusting that he could be a consistent player. As a result, he became of the best pitchers.

Meanwhile, Sig Mejdal worked on complex algorithms to support player-selection.  The scouts of the Astros collected information related to potential recruit’s health history, performance, playing style, and personality to help the team of analysts to create a database of player metrics.

There was a doubt in Mejdal’s mind which is about the reliability of the scout’s evaluations. To solve that there was a great way including a comparison between their ratings and the actual performances of players. In this way, decisions would be free from prejudice or bias. Mejdal showed that by doing this, you will be able to create a more objective recruitment policy to find players that perform high performance.

As you guess, a conflict between the new approach and traditional scouts who used their instinct to pick players and was appeared. However, it worked despite the doubts of naysayers. The key to the Astros’ 2017 World Series was Mejdal’s system. Thanks to his recommendations, a team set up and it had 101 wins with only 61 losses in 2017.

There are still two important factors in the scouting process: The ages and salaries of the baseball players.


In the middle of 2012, the Astros’ public relations office prepared biographies of high school players whom the team considered as potential recruits. When the elections were done, there were a few surprises. The reason for this was the unique approach of Jeff Luhnow and Sig Mejdal.

Let’s consider the age question. Most baseball followers expected to be chosen Byron Buxton because of his name and talent. However, Luhnow did not have any of it and he plumps for Carlos Correa who has a low-key profile.

Correa, a defense expert like Buxton, had promised, but his performance statistics were solid instead of outstanding. If Sig Mejdal hadn’t seen what others couldn’t see, there would be plenty of scouts turned off because of that. However, thanks to his algorithms, Correa has won with its powerful defense performances.



Then, the age question was there. Buxton was nine months older than Correa who is just 18 when the Astros took him. According to Mejdal’s data, each month’s age difference between players – and their teams – was important for their long-term purposes. The idea that the signing of talented young people can change everything was another insight for dividends. Correa got better and better while Buxton’s performance with the Minnesota Twins increased between 2013 and 2014 before decreasing in 2015.

Choosing young talents before their best years is more logical move financially because it is clear that they earn a lot less than experienced players. That is a boon in baseball because it definitely organizes spending for new signatures and keeps a certain amount for every ten new players.

Correa was young and inexperienced so this new system couldn’t be applied to him. If we consider this system, it means that the first new signing of the team -in this case, Correa- limits how much can be spent for other players and typically he gets the biggest pie. As a result, the Astros has given the new fielder something far below the expected $7.2 million which was $4.8 million.

As a result, The Astros has filled a key position and had enough change to get the best players in other positions!

Get rid of prejudice and discover new talents by relying on data.


Baseball is an emotional job like many games. For instance, Jeff Luhnow, the Astros’ scouting director, took letters and emails related to the favorite players’ recruitment by young fans of the team. Just ask him! Of course, sports can include emotions; however, the reason for playing and watching games is love. But recruitment policy needs a more logical approach.

This depends on the simple reason. Relying on data provides better results instead of sentiment or instinct.

In 2006, the Astros didn’t have Sig Mejdal’s algorithms yet, but they already used the data and struck gold. So it was something the team knew. Jose Altuve, a Venezuelan defensive fielder known as ‘’the midget’’ by his teammates was found due to his small size. Altuve was a talented player on all accounts but his figure made a problem although some major teams tried out him and he was sent home by saying that five-foot-five player never takes part in the major league.

This was the case until the Astros but everything changed when tryout for the Astros. Altuve’s speed impressed the team’s scout. Although he was absolutely small, he could cover a lot of ground, 60 yards in just 6.31 seconds to be precise. At the same time, he was a talented batter, hitting every ball in his path despite the general prejudice that smaller players have difficulty doing that.



The team believed in the numbers and Altuve had a chance to play in one of the Astros’ minor league teams with a small bonus of $15,000. And he didn’t disappoint. He was asked to join the Astros for the major league after his impressive batting average of .327 in 2011. This became another proof for data-driven scouting. Altuve was aggressive and shook 55 percent of all pitches, but better yet, he hit 88 percent of them, more than the best sluggers such as Hall of Famer Vladimir Guerrero.

If traditional methods applied, this talented, pint-sized baseball player could be missed. However, it wasn’t just Astros that benefited from it. The performance of Altuve was so impressive and $ 12.5 million was offered him to stay and play in the team for the next four seasons.

Health problems require difficult decisions and insightful management.


Good athletes often earn more money in a week than many people have won all year, and they are also worthy of attention when they are successful. However, the trade of athletic is open to harm because of injuries. So, it is not just about laughing all the way to the bank.

Pre-existing health problems can sometimes cause careers to end before it really begins. Look at the young player Brady Aiken by the Astros. Aiken was on the verge of fame and fortune when he came to Houston for his medical examination.  His dream had come to naught after the tests.

A weak ulnar collateral ligament that placed under high stress in a baseball was discovered in his arm by the researchers. Aiken was sent home because of the risk of its explosion. It was a  difficult decision. Although the Astros’ scouts loved the way Aiken played, it needed to be done.

However, Aiken couldn’t be turned away easily because to break the agreement with him without losing a ton of money needed plenty of savvy. This is because; Aiken had to compensate for his loss if this happened. This signature could get 40 percent of the bonus value. And for Aiken, that bonus was $ 7.9 million, which means Aiken received $ 3.1 million.



After all, what Aiken wanted wasn’t just money; he wanted to play baseball. Relying on this, the Astros gambled that he would reject this compensation offer.  As long as he refused to accept the compensation, another team could hire him. When that occurred, the Astros would receive a transfer fee and the team could use resources for different players.

In 2015, Astros saw that was the right decision. Aiken’s ulnar collateral ligament exploded in a game for the Florida-based IMG Baseball Academy, as predicted by Astros’ medics. Aiken was later taken part in Cleveland Indians until his injury reappeared again. Meanwhile, Astros chose Alex Bregman instead of Aiken and he became a new player to be a fundamental part of the team.

Athletes need to adjust when they plateau.


What makes the best athletes? Including baseball, all athletes develop with age, takes on natural abilities and completes their growing experience in the game. Each player hopes continuous growth and development. However, not all of the careers appear in this way. Sometimes plateau affects the players.



Let’s consider a batter JD Martinez from Florida, shining after knocking the door of the small leagues and selected by the Astros on the twentieth of the 2009 draft. In two years, he was chosen for the major league team. He was one of the best players in a struggling and the most consistent scoring player in the team of Astros in 2012.

But one year later, with the fall of Martinez’s statistics, things began to change. The batting average of him declined to .251 and he hit 24 home runs throughout the season. While people thought about what was going on, the hitting coach of the team John Mallee explained that Martinez was stagnating. If he really wanted to be a great player, he needed to change. Mallee warned him if he continued in the same way so he would be separated from US baseball.

Mallee’s advice worked and Martinez decided to improve his game. After a few weeks, he broke his wrist and he benefited from it by following some of the world’s best sluggers’ games in the stands. There were few better players than Ryan Braun at Milwaukee Brewers. While Martinez was watching Braun’s shoot the ball out of the park, he realized that Braun waved his bat downward and had a tendency to swing upwards make the batter’s final position higher like other top talents. So, his swinging style was incompatible with Braun’s.

Martinez went to California for a few months to be trained with expert batting coaches after his wrist was healed.  And, he re-emerged in the field in 2014 with the batting average of .312. Unfortunately, the Astros was not believed and dismissed him, but that would be their mistake. When he transferred the Detroit Tigers, Martinez became the player of the month in June 2014 by raising his average to .444.

Team spirit can get strong with the help of inclusion.


There are two separated groups of major league baseball players that mother tongue is English and Spanish. In most of the locker rooms, the distinction between them may not even appear, but it is still the same in there.

However, there is no need to be in that way. Also, the clubs’ spirit gets much stronger when they overcome the linguistic division.

For instance, Carlos Beltran was a Puerto Rican player and when he joined the American baseball leagues in 1998, he couldn’t speak English. I wish the only problem was language. There was also a racial prejudice which caused prevention of bonds between Caucasian and Hispanic players.

Beltran had a lasting impression because of that experience. When he was a 40-year-old player in the Astros between 2016 and 2017, he was determined to create the inclusive atmosphere that he had never found before in his career. Of course, it wasn’t as easy to tell. But Beltrán found Alex Bregman, a Caucasian player who has been in the Astros since 2015.



Bregman claimed that he can speak Spanish perfectly. Although this was a white lie, he really wanted to get to know the Hispanic players of the team, including stars like Altuve and Correa. In a short time, other players tried to improve their English and Spanish skills thanks to his desire and as the boundaries of the language disappeared, a new team spirit began to appear.

Yuli Gurriel was a talented Cuban first baseman and he transferred to Houston in 2016 although he didn’t speak English. Eventually, many of Houston’s top performers were similar to Gurriel and the performance of the team was great. Bregman was in the management again and he provided the new signee’s social adaption by chatting with Gurriel in Spanish.

A sense of inclusion was shaped among them thanks to Beltran and Bergman and it provided a successful performance to the team. As a result, the most successful season of the club was in 2017 with a total of 101 wins.

There are also some limitations to predict the value and future performance of a player despite the advantages of the data.


The Astros became one of the best baseball teams in the American Major League thanks to the data and sophisticated algorithms. However, only technology can’t provide the success. Of course, what the data can do is too much, but that does not mean that it can do everything.

There is an area that the data is insufficient is player valuations. For instance, the Astros had a chance to take Justin Verlander who is one of the best pitchers in the country in 2017. This sounds like great news. However, he would cost $ 40 million for two seasons. According to Sig Mejdal’s algorithm, the deal would not be worth it, but he could not predict that the economic climate was changing in the major league. Prices had risen fastly everywhere. Star players such as David Price and Zack Greinke earned $ 30 million a year on four-year contracts.



From a different point of view, Verlander could actually be a good deal because the Astros would take Verlander at a lower cost than most other pitchers. This step would be one of the most important steps of all time. The club’s sports director, Jeff Luhnow, made a lot of decisions by considering Mejdal’s data, but this time he ignored the algorithm and started calling Verlander and it didn’t end badly. Today, he is a seven-time the Major League Baseball All-Star player!

Another thing the algorithm missed was that Verlander could continue to develop, even though he seemed as at the top of his game. This is not interesting. It is difficult to predict accurately because future performance is generally based on past performance.

Top players can adapt and change their styles of playing so setting price is difficult for them. As an example, how can an algorithm predict the fact that Verlander’s signature sliding pitch is undermined by new, higher speedballs or that he answer this change by raising his game once more and preparing a new technique?

Statistics, data, and mathematics will continue to play a major role in major league baseball in the foreseeable future. Thanks to teams such as the Astros, what you can achieve when you trust the data, not instincts is proved.  However, there is still enough space for a more human touch.

Astroball: The New Way to Win It All by Ben Reiter Book Review


While choosing players for a baseball team, prejudice often appears because of too much reliance on gut instinct. On the other hand, the data help taking more logical decisions. However, there are still exceptional situations which need to be ignored data and followed instincts by the scouting directors.


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Savaş Ateş

I'm a software engineer. I like reading books and writing summaries. I like to play soccer too :) Good Reads Profile: https://www.goodreads.com/user/show/106467014-sava-ate

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