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Technology Didn’t Save the Angels’ 2022 Season. Sacrificing People for Data Analytics Won’t Save Your Company, Either.

As I was reading an article in Sports Illustrated (SI) the other day, I noticed multiple leadership failures associated with the Angels’ horrendous 2022 season, which I believe all business leaders can learn from. Despite having a fantastic start to the season, one of their best in years, their manager Joe Maddon was unceremoniously discarded.

Joe Maddon’s relationship with the Angels goes back a long way, including serving as bench coach for the 2002 World Series championship team. (I was lucky enough to be at game 7 of the 2002 World Series when they clinched the series.) Maddon then managed the Rays and led them to their first-ever World Series appearance. If that wasn’t enough to cement his legacy, he took the Cubs to a World Series championship in 2016, their first in over 100 years, breaking the “Curse of the Billy Goat.” In addition, Maddon was known as a well-liked player’s coach and was respected among other baseball managers and executives. He earned the prestigious Manager of the Year title an impressive three times. So what led to this revered baseball manager firing at the beginning of the 2022 season? 

Leadership Problems Take the Shine off the Angels’ Halo

Situations like these are often complex, with lots of moving parts. Although I don’t have insider knowledge, I’ve lived through similar situations in corporate America. My personal opinion is that it can be boiled down to a leadership failure of the Angels’ front office – mainly the team’s general manager, Perry Minasian, and owner, Arte Moreno. 

Angels use of data analytics in baseball

The Angels have recently had a couple of major scandals involving the front office. In 2019, a promising pitcher died of an overdose of opiates provided to him by an Angels front office employee. More recently, a shady deal where Moreno attempted to purchase Angels stadium and the surrounding land took down Anaheim’s mayor and a few other local politicians in an FBI corruption probe. After this hit headlines, Moreno announced he was exploring the team’s sale. My guess is that Moreno is being forced to sell the team due to the allegations of corruption.

Although the scandals I referenced aren’t directly tied to Joe Maddon’s firing, I mention them to give a glimpse of the front office corporate culture. As we know, nothing happens in a vacuum. 

Data vs. Humans – the Moneyball Effect

The SI article attempts to explain the Angels cutting Maddon loose as a philosophical disagreement over how data is used in baseball – old school vs. new school. It certainly seems to be part of the issue. However, I think it’s a bit more nuanced than that. 

Being a business leader means prioritizing humans over AI

Baseball data analytics, made famous by Moneyball, brought an evolution to the game. Moneyball wasn’t just a baseball book; it made the rounds in business circles. I know I read it and thought it was a fascinating read.


Moneyball, published in 2004, is a book about how the 2002 Oakland A’s, a small market team, used data analytics to compete against large market teams with much larger payrolls. That year, the A’s set an American League record by winning 20 games in a row to earn a playoff spot. The book was later adapted into a movie starring Brad Pitt. Ironically, 2002 is the year the Angels beat the A’s in the playoffs before winning the World Series.

Data Isn’t Accountable to Anyone

From how the SI article described things, Minasian appears to value data over people, believing that following whatever the Angels’ proprietary algorithms spit out would win games for them. Minasian even dictated strategy to Maddon gleaned from data analysis, including during games. In baseball, there is a dividing line between the front office and the on-field manager and coaches. However, this line has been less transparent since Moneyball. To me, this shows a top leadership in the front office that micromanages and lacks trust in the on-field staff.

Data analytics

If micromanagement isn’t bad enough by itself, Maddon was fired for implementing a failing strategy dictated to him by the higher-ups in the front office. This is commonly known as scapegoating. I’ve had personal experiences with this in the business world, it’s happened to me and I’ve seen it happen to others.

Someone had to take the blame for the Angels’ poor performance during a 12-game timeframe preceding Maddon’s firing. Data isn’t accountable to anyone, so it can’t be the data’s fault. The algorithms that analyzed the data were developed by front-office staff and seen as the Angels’ “secret sauce,” so it couldn’t be the algorithm’s fault. Clearly, Minasian didn’t want to be accountable for the Angels’ failures. It had to be someone’s fault, so Maddon was forced to fall on his sword. 

The Problem With Prioritizing Data and Technology Over People

What does this tell us aside from the front-office refusal to take responsibility? I believe that in this situation, technology, especially data analysis, is being prioritized above people. Data is often seen as being godlike – infallible. Partly because the average person doesn’t really know what an algorithm is and how data analysis is done. I think this will become even more pervasive with the rise of AI technologies. 

Data is only as good as how clean the data is and how it’s interpreted. I’ve had many experiences where I’ve looked at the same data set as my colleagues and come away with different interpretations of what the data meant than my colleagues did.

There are plenty of ways data analysis can go sideways. Data can be collected improperly; for example, a survey may be biased. An algorithm can be flawed by analyzing the data incorrectly, resulting in skewed insights. There are also things that computer systems aren’t good at analyzing, especially when it comes to human beings. We are complex creatures that have infinite variabilities. 

Just like baseball teams, companies are comprised of people. Employees and customers make or break a company. You can have a human resources AI system that analyzes how to increase the performance of your employees or a marketing algorithm that outputs the best target market for a product. However, these systems aren’t good at understanding the human condition.

Algorithms are only as good as the people who program them and use them.

The Angels’ proprietary algorithm can infer how much rest each relief pitcher needs. But an algorithm can not motivate a relief pitcher to pitch at or above his ability. Data won’t be able to tell you that a player had a fight with his spouse the night before or how to help that player deal with a personal situation and perform at his best.

A player will not give extra hustle and make a spectacular play in the outfield because of an algorithm. Data analysis can be great at analyzing past data points, and AI can be especially good at making predictions based on data. But an algorithm can’t factor in every human variable.

Technology Won’t Make up for Poor Leadership

Technology is not a substitute for an experienced manager who knows how to use emotional intelligence (EQ) to understand and motivate a team. As leaders, we must prioritize people over technology. Ideally, we should pair great managers with great technology, with humans leading the machines, not the other way around.

Technology didn’t save the Angels’ season. Instead, they ended up with a losing record, finishing 33 games out of first place in the AL West. 

Angels 2022 Record Under Maddon: 27 wins – 29 losses
Angels 2022 Record After Maddon Was Fired: 46 wins – 60 losses

Sacrificing people for data analytics won’t save your company, either. 

If, as a business leader, you aren’t able to be empathetic, you’ll keep losing and blaming others for it. 

If you have a boss who isn’t empathetic and won’t take personal responsibility, it’s time to find another job before you become the next scapegoat