The Twins Have Ground to Make Up in Baseball Analytics

[Cody Christie]

Image courtesy of © Jeffrey Becker-Imagn Images

The Twins have plenty of areas to address this offseason. After reducing payroll and moving on from several key figures in baseball operations, the organization needs to find ways to improve its roster without spending like baseball's biggest-market teams. One potential area for improvement might not involve signing a single player.

Analytics departments have become an increasingly important part of modern baseball operations. Teams use their staffs to evaluate players, develop pitching strategies, improve player performance, and help make decisions throughout the organization. The best departments combine traditional baseball knowledge with data analysis, engineering, research and development, and quantitative sports science.

A recent look at MLB analytics staffing shows a notable trend among the teams remaining in the postseason. Several clubs have invested heavily in these departments, while Minnesota sits below the league average. The Twins cannot expect to solve every problem by hiring more analysts, but this is an area where additional investment could help the organization make up ground.

The Postseason Teams Invest in Analytics

The Milwaukee Brewers have built one of baseball's largest analytics departments, with 46 employees. That total ranks second in MLB, trailing only the Philadelphia Phillies, who lead the league with 51. The Tampa Bay Rays have 39 employees, while the Cleveland Guardians have 30. All four organizations sit above the league average of 28.5 analytics employees.

These departments include more than employees whose job titles contain the word analyst. Baseball analytics and research-and-development personnel work alongside engineers, department leaders, embedded analysts, and quantitative sports scientists. Each role can contribute to a team's ability to evaluate information and translate it into practical decisions on the field.

The staffing numbers do not prove that a team will win more games simply because it employs more analysts. For instance, the Blue Jays, Tigers, and Mets all rank among MLB’s top-10 in analytics staff, but that trio all missed the playoffs. A larger department can still make mistakes, and a smaller department can be effective when its personnel are talented and its processes are sound. Still, the numbers show that several successful organizations have made analytics a significant part of their baseball operations infrastructure.

Minnesota currently has 27 employees in its analytics department, ranking 17th in baseball. That puts the Twins below the league average of 28.5. The final three teams remaining in the postseason average 38.3 analytics employees, a difference of more than 11 employees per organization.

That gap is worth examining. Minnesota does not necessarily need to match the Phillies' 51 employees, but the Twins should consider whether their current staffing level gives them the resources needed to compete with organizations that have made analytics a major priority.

Minnesota Has Cut Back in Other Areas

The analytics discussion comes at a time when the Twins have made difficult decisions about spending across baseball operations. Minnesota has operated with a reduced payroll compared with recent seasons, and its approach to roster construction has increasingly emphasized finding value rather than paying for established talent.

Those financial decisions affect more than the players on the field. Baseball operations departments need the resources to evaluate trade targets, identify undervalued free agents, develop prospects, improve player performance, and make decisions about the roster's long-term direction. When an organization reduces spending, it needs to be careful not to weaken the infrastructure that helps it spend wisely.

The Twins have experienced significant changes in their baseball operations leadership, including the departure of Derek Falvey and a transition to a new decision-making structure. When he was hired, Falvey was tasked with building Minnesota’s analytics department. Leadership changes can create opportunities to rethink how the organization operates, but they also make it important to maintain the people and processes that help turn information into better decisions.

Analytics cannot replace good scouting, strong player development, or experienced baseball leadership. It should complement those areas. A larger analytics department could give Minnesota more capacity to investigate questions that currently compete for limited staff time, work more closely with coaches and players, and build better systems for evaluating talent.

That last point matters for a team operating with financial constraints. The Twins need to find players who outperform their contracts, identify weaknesses before they become expensive problems, and develop internal options rather than relying on the free-agent market to fill every roster hole.

An effective analytics department can help with all three tasks. It cannot guarantee that every acquisition works or every prospect develops, but it can give the organization more information and better tools when making decisions.

A More Affordable Way to Close the Gap

One of the most compelling arguments for investing in analytics is the relative cost. Adding several analytics employees would cost money, but it would not necessarily require the same financial commitment as improving the major-league roster through free agency.

Consider the cost of adding a middle reliever. Even a modest free-agent contract can cost a team several million dollars for one season. That player might provide valuable innings, but there is no guarantee he will perform as expected. A few additional analytics employees could cost less than that single roster addition, depending on their roles and experience, while contributing to decisions that affect multiple players and potentially several seasons.

The value is not simply about finding the next inexpensive reliever. An expanded department could help the Twins evaluate bullpen options, identify pitchers whose underlying numbers suggest untapped potential, and develop more individualized approaches to pitch selection and workload management. Those same resources could help the organization evaluate hitters, improve defensive positioning, and support player development throughout the minor leagues.

Analytics staff members also do not need to produce an immediate return in the form of wins. Their work can influence decisions across the organization, from amateur scouting and international acquisitions to major-league roster construction. That creates the potential for a broader return than spending a similar amount on one player.

Of course, hiring additional employees does not automatically make an organization smarter. Minnesota would need to identify the areas where its current department lacks capacity, recruit people with the right expertise, and make sure its analysts work closely with scouts, coaches, and players. Adding staff without a clear plan would simply increase expenses.

The Twins should also avoid treating analytics headcount as a competition in which the team with the most employees automatically wins. The quality of the staff, the information available to it, and the organization's willingness to act on its findings matter more than the raw total.

Still, a department with 27 employees operating below the league average may have opportunities to expand its capabilities. Minnesota does not need to double its staff overnight. Targeted additions in research and development, engineering, or quantitative sports science could address specific needs without creating an enormous new expense.

Like payroll, analytics staffing is one input in a much larger equation. Coaching, scouting, player development, front-office leadership, and the players themselves still matter more collectively than any single department's headcount. A well-funded analytics operation cannot overcome poor decisions across the rest of the organization.

But the opposite is also true. A team with a limited payroll needs every advantage it can find. If Minnesota intends to compete with organizations that consistently identify undervalued players and maximize their existing talent, it should make sure its own baseball operations staff has the resources to do that work.

The Brewers, Rays, and Guardians offer useful examples of organizations that have invested in analytics while operating under different financial circumstances than baseball's wealthiest clubs. Their staffing numbers do not explain their entire success, but they reinforce the idea that teams can invest in their infrastructure even when they cannot spend without limits on the major-league roster.

The Twins have ground to make up. Their 27 analytics employees put them below the league average, while the final three postseason teams average 38.3. Closing that gap would not guarantee Minnesota a postseason run, but it could improve the organization's ability to make better decisions with the resources it has.

If the Twins are serious about building a sustainable contender, expanding their analytics department deserves a place in the offseason conversation. Spending millions on one more reliever might help solve a single roster problem. Investing in the right people behind the scenes could help the organization solve problems across the entire roster.

For a team looking to maximize every dollar, that is an opportunity worth exploring.

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Should the Twins invest more in their analytics department? Leave a comment and start the discussion. 

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[DJL44]

It isn’t about people, it is about what the analysts are doing and whether that analysis adds value.

[Linus]

I would also add that all the data is important and certainly more data and more accurate data is better. However, at some point someone in a leadership position takes that data and makes a decision. The quality of the decision making is key in my view. 

[thelanges5]

Quality over quantity. 

[Andy MacPhail]

"Analytics cannot replace good scouting, strong player development, or experienced baseball leadership. It should complement those areas. A larger analytics department could give Minnesota more capacity to investigate questions that currently compete for limited staff time, work more closely with coaches and players, and build better systems for evaluating talent."

I'm all for analytics, but IMO. what makes the most difference is philosophy. If the philosophy is off, it doesn't make any difference in how much analytics you have, it'd be a waste of money. What makes a difference for MIL, TB & CLE is their philosophy. Once that is taken care of, then yeah, analytics is good.

[mikelink45]

Give me good players - players with speed, bat to ball contact and good gloves - an out is an out no matter what analytics says. 

[Maybe Next Year]

Enough with the analytics. How about an actual baseball organization that focuses on player development and fundamentals. I will take common baseball sense over analytics every day of the week. Money is not the answer- look at the top Mets, Dodgers, Yankees, BlueJays etc… it’s all about player development and common sense application of fundamentals and game strategy. 

[Hrbowski]

7 minutes ago, Maybe Next Year said:

Enough with the analytics. How about an actual baseball organization that focuses on player development and fundamentals. I will take common baseball sense over analytics every day of the week. Money is not the answer- look at the top Mets, Dodgers, Yankees, BlueJays etc… it’s all about player development and common sense application of fundamentals and game strategy. 

Name one team that has eschewed analytics that has won the world series in the last 15 years. I'll wait...

[DJL44]

1 hour ago, mikelink45 said:

Give me good players - players with speed, bat to ball contact and good gloves - an out is an out no matter what analytics says. 

The whole point of analytics is to find those players and maximize their development.

[Vanimal46]

32 minutes ago, Maybe Next Year said:

Enough with the analytics. How about an actual baseball organization that focuses on player development and fundamentals. I will take common baseball sense over analytics every day of the week. Money is not the answer- look at the top Mets, Dodgers, Yankees, BlueJays etc… it’s all about player development and common sense application of fundamentals and game strategy. 

Replace the word analytics with statistics. Which is the foundation of analytics. Then read your post again. And realize how silly it is to push back on statistics. 

[Vanimal46]

4 hours ago, Andy MacPhail said:

"Analytics cannot replace good scouting, strong player development, or experienced baseball leadership. It should complement those areas. A larger analytics department could give Minnesota more capacity to investigate questions that currently compete for limited staff time, work more closely with coaches and players, and build better systems for evaluating talent."

I'm all for analytics, but IMO. what makes the most difference is philosophy. If the philosophy is off, it doesn't make any difference in how much analytics you have, it'd be a waste of money. What makes a difference for MIL, TB & CLE is their philosophy. Once that is taken care of, then yeah, analytics is good.

And what do you know? Those organizations emphasize good pitching, defense, and athleticism. 3 traits that have aged well in baseball for 100+ years. 

[DJL44]

I saw Baseball America ranked the Twins minor league pitching as among the worst in Stuff+, so maybe they could use more help in the analytics department. Why can’t they draft any decent pitching?

[Vanimal46]

15 minutes ago, DJL44 said:

Why can’t they draft any decent pitching?

Perhaps a one size fits all development strategy making everyone a 2-4 inning pitcher isn't a great idea. 

[mikelink45]

1 hour ago, DJL44 said:

The whole point of analytics is to find those players and maximize their development.

I guess eyes must be analyctic

 

[DJL44]

14 minutes ago, mikelink45 said:

I guess eyes must be analyctic

 

So they can’t develop pitching because they haven’t looked at their pitchers hard enough?

[MeleMouth]

As someone who was reading Bill James more than 40 years ago, I'm confident he would say that decision-making is much more important than analytics, which is just utilizing data as a tool to gain insights for decisions. In that vein, all the analytics in the world wouldn't help the Twins be better than Milwaukee, if, for example, Milwaukee makes better decisions about which pitchers to trade and when, and which pitchers to acquire, or if Milwaukee makes the hard decisions about which prospects and rookies to sign to long-term contracts and gets it right when they do.

Nor would more analytics help the Twins be better than Tampa, if, for example, Tampa makes better decisions about when they are not competitive and trades veterans for prospects, and acquires better prospects when they do, and acquires higher-end talent when they are competitive. You could probably find other areas where Milwaukee and Tampa, as well as Cleveland, Los Angeles, and even the White Sox and other teams, generally make better decisions than the Twins.

This year, an analytics staff of only one person would have been all that was needed to tell the Twins that their offensive results in the first half were likely to regress, they had a small chance of making the wild card, and a miniscule chance of going much further. A team of just average smartness would have said it was time to fold 'em, but not the "go big or go home" Twins who, instead of trading for next year, went out and made a lot of drama about tinkering around the edges and then crashed into a 77-win year with the dubious consolation of probably drafting 10th instead of higher.

That's bad decision-making, not bad analytics.

[TheLeviathan]

I think this was a really interesting article.

How did some of you arrive at such silly responses as "quality over quantity" and "an out is an out".

Like....the two teams in the World Series, who have been consistent winners for the better part of a decade now, are clearly investing in something the Twins are not.  Why are we not open to taking notes on that?

Is it really a surprise that they keep mining aces out of the 2nd round, turning Trevor Megills into lights out closers, get Yandy Diaz for scraps, or snag Junior Camerino for a reliever?

Part of how they keep making so much out of so little is what was discussed in this article.  Put down the cloud yelling for a second and consider the world might be different.

[TNtwins85]

9 hours ago, MeleMouth said:

As someone who was reading Bill James more than 40 years ago, I'm confident he would say that decision-making is much more important than analytics, which is just utilizing data as a tool to gain insights for decisions. In that vein, all the analytics in the world wouldn't help the Twins be better than Milwaukee, if, for example, Milwaukee makes better decisions about which pitchers to trade and when, and which pitchers to acquire, or if Milwaukee makes the hard decisions about which prospects and rookies to sign to long-term contracts and gets it right when they do.

Nor would more analytics help the Twins be better than Tampa, if, for example, Tampa makes better decisions about when they are not competitive and trades veterans for prospects, and acquires better prospects when they do, and acquires higher-end talent when they are competitive. You could probably find other areas where Milwaukee and Tampa, as well as Cleveland, Los Angeles, and even the White Sox and other teams, generally make better decisions than the Twins.

This year, an analytics staff of only one person would have been all that was needed to tell the Twins that their offensive results in the first half were likely to regress, they had a small chance of making the wild card, and a miniscule chance of going much further. A team of just average smartness would have said it was time to fold 'em, but not the "go big or go home" Twins who, instead of trading for next year, went out and made a lot of drama about tinkering around the edges and then crashed into a 77-win year with the dubious consolation of probably drafting 10th instead of higher.

That's bad decision-making, not bad analytics.

The decision making is key. Like punting a roster spot to keep Alex Jackson. Magically realizing after a month that Brooks Lee is not a shortstop after watching him for 2 years. Waiting 2 months to come to the conclusion that Royce Lewis’ approach was garbage. Fielding Matt Wallner in right field because he has a good arm when the rest of his defensive game is terrible. Decision making.

[mikelink45]

11 hours ago, DJL44 said:

So they can’t develop pitching because they haven’t looked at their pitchers hard enough?

If they looked they didn't see - or our pitchers just aren't that good. 

[MeleMouth]

10 hours ago, TheLeviathan said:

I think this was a really interesting article.

How did some of you arrive at such silly responses as "quality over quantity" and "an out is an out".

Like....the two teams in the World Series, who have been consistent winners for the better part of a decade now, are clearly investing in something the Twins are not.  Why are we not open to taking notes on that?

Is it really a surprise that they keep mining aces out of the 2nd round, turning Trevor Megills into lights out closers, get Yandy Diaz for scraps, or snag Junior Camerino for a reliever?

Part of how they keep making so much out of so little is what was discussed in this article.  Put down the cloud yelling for a second and consider the world might be different.

Analytics are very important, but not the be-all, end-all. 

For example, the same analytics that caused the Twins to see something in Trever Megill in the first place are what caused Milwaukee to pick him up from the Twins for a PTBNL and cash. However, MLW was able to read their analytics to see what changes Megill needed to make, but which the Twins failed to do. Similar stories probably apply to other discarded relievers whom the Twins identified as talented, but who almost immediately reached a couple levels higher after they went to other teams, such as Pressly to the Astros, Cano to the Orioles, and even Henriquez to the Marlins.

Similarly, it is probable that decisions based on analytics caused many mistakes by the Twins over the years, such as continually pinch hitting Margot even after he set a record for futility, prioritizing hitters who hit homers but struck out a lot and fielded poorly, pinch hitting early in the game to maintain a hand advantage, and giving at-bats to Joey Gallo long past all evidence showed he was cooked.

Now, if you're arguing that advanced stats like exit velocity and launch angle are better predictors than traditional stats like RBIs for identifying future run production, I'm with you, as well as I am for many other advanced stats that are proprietary to the various teams, but all the analysts in the world will not overcome bad decision-making and strategy. 

[TheLeviathan]

37 minutes ago, MeleMouth said:

Analytics are very important, but not the be-all, end-all. 

For example, the same analytics that caused the Twins to see something in Trever Megill in the first place are what caused Milwaukee to pick him up from the Twins for a PTBNL and cash. However, MLW was able to read their analytics to see what changes Megill needed to make, but which the Twins failed to do. Similar stories probably apply to other discarded relievers whom the Twins identified as talented, but who almost immediately reached a couple levels higher after they went to other teams, such as Pressly to the Astros, Cano to the Orioles, and even Henriquez to the Marlins.

Similarly, it is probable that decisions based on analytics caused many mistakes by the Twins over the years, such as continually pinch hitting Margot even after he set a record for futility, prioritizing hitters who hit homers but struck out a lot and fielded poorly, pinch hitting early in the game to maintain a hand advantage, and giving at-bats to Joey Gallo long past all evidence showed he was cooked.

Now, if you're arguing that advanced stats like exit velocity and launch angle are better predictors than traditional stats like RBIs for identifying future run production, I'm with you, as well as I am for many other advanced stats that are proprietary to the various teams, but all the analysts in the world will not overcome bad decision-making and strategy. 

You're trying to put pieces together about information we simply don't have about process or what these departments are doing.

What can be said with certainty is that both of these teams (Rays and Brews) are putting more man-power to it than we are and their track records speak for themselves.

[MeleMouth]

6 minutes ago, TheLeviathan said:

You're trying to put pieces together about information we simply don't have about process or what these departments are doing.

What can be said with certainty is that both of these teams (Rays and Brews) are putting more man-power to it than we are and their track records speak for themselves.

Simply counting headcount is also putting pieces together about pieces we don't have. These teams are actually using analytics differently from other teams. Further, the world's largest and most technically brilliant analytics department won't overcome "go big or go home."

Finance is full of analysts. When you're picking someone to invest your money, do you pick the company with the biggest analyst department or the one with the best track record of decisions?

In fact, the answer to your request is within your response itself. Analytics is necessary, but before adding headcount, the Twins need to figure out the gaps between their processes and the processes of other teams. Critically, "processes" needs to include thought and decision processes, which are more important than algorithmic processes, which were one of Falvey's downfalls.