As you read this, you probably have heard that Buck Showalter will not return next season to managing the Orioles. This is something that many Orioles fans and commentators have been expecting, although there were some who thought that Showalter would move to a front office role. However, this is not the case and Dan Duquette—currently*—remains to reshape the organization going into a complete teardown.
Two hours after this article was posted, the news came out that the Orioles intend to let Dan Duquette go as General Manager.
I don’t want to concentrate on the manager search that will now consume much of the next few weeks. The team will eventually make a hire, and this could shape the franchise’s future for the good or ill going forward. Where I want to focus the next few words is on the intersection between the team’s managerial hunt and a promise that Dan Duquette made back in July: an increased focus on analytics.
There was a time when the Orioles seemed to be on the analytical upswing, as recently as 2015. The analytics department was led by Sarah Gelles, who had been with the team for many years. She entered the front office in 2011, and became the Director of Analytics the following year. The team had hired Kevin Tenenbaum, a graduate of Tufts University who had just presented at the SABR Analytcs Conference in 2013 and 2014. Mike Snyder—Director of Pacific Rim Operations and Baseball Development—was an Economics major and was studying to get his Masters in Statistics from John Hopkins. The team was working to hiring a systems developer—crucial to a well-working analytics department—and it seemed like the department was well on its way.
Since 2016, that growth has seemingly stagnated. Gelles and Snyder are still with the team, and Gelles has also added Major League Contracts to her purview. Di Zou became that Systems Developer, and he also still remains a member of the front office. Tenenbaum left for Cleveland, where he joined one of baseball’s most talented analytics departments. To this point, it does not appear that he has been replaced. If you look at the front office page on the Orioles’ website, you do not see a single person with the title “Analyst” in the Baseball Operations department.
Now, this is admittedly a difficult thing to quantify. Team’s do not necessarily list their full analytics departments on their web pages. The Tampa Bay Rays, for example, list their analysts right there for the world to see. Tampa is one of the noted analytical teams, a leader in the sabermetric movement. The New York Yankees are also on of the most analytical teams—they employ an estimated 20 analysts in their front office—but you would not in any way know this from their website. That said, it still seems like the Orioles have not necessarily grown or even replaced the members of their analytics department.
Replacing these losses seems like a fairly easy solution; Johns Hopkins—just 5 miles from Oriole Park—hosts one of the top five graduate programs in Statistics in the country. Three more top-10 programs—Harvard, Carnegie Mellon, and University of North Carolina—are within 500 miles of Baltimore. Surely there are Masters degree or Ph.D. students—yes, graduate education is nearly a must today to enter the professional sabermetric world—who have an interest in baseball and would be willing to help build up the team’s analytics from its current state.
Now, the next portion of what I have to discuss deals with how analytics interacts with the rest of the front office. Many of the things I mention are things that I am sure are obvious and are in fact things that the Orioles likely know and already do. That said, these ideas do deserve restating.
The problem is, investing and building an analytics department goes beyond hiring analysts. It has to be a front office-wide commitment to understanding the goals, methods, and language of analytics. The goals of analytics are the goals of any department within Baseball Operations; to help the major league club win games. Analytics accomplishes this by working with available data and uncovering new data sources. Professional scouting, amateur scouting, player development need to understand—as I am sure most members of these departments do—that analytics is not here to replace them but to complement them. It’s this co-complementary role that all departments need to play, with equal standing and mutual trust.
The language of analytics and communication of analytics is key here. Implementing any solution that analytics devises, or analytics investigating any question player development has can only be accomplished when everyone understands each other. This goes beyond just understanding the equivalent of batting .300 for each advanced statistic. Scouts need to understand the outputs of analytical models, the reasons for those models, why analysts want them to focus especially on certain traits in players. Analysts need to understand what a scout means when they say a college catcher has the potential to be a good receiver, and why they think this is the case. Analysts need to be able to communicate why certain defensive positioning is important to managers, coaches, and players. Communication is key throughout all the interactions between every department.
All of this starts at the top. Whoever is hired to be the General Manager must do more than pay lip service to analytics. He needs to do more than just hire analysts. He needs to ensure that this front office-wide commitment to collaboration within departments not only occurs, but becomes second nature.
The manager is key here as well. They need to be numbers-literate, or at least willing to entertain new analytical ideas. Josh Bard—a former major catcher and current bench coach for the Yankees—is an intriguing candidate here. David Laurila did an excellent interview with Bard, as he talks about the integration of data and information in the clubhouse and game in general. Bard would know, as he has not only spent time with the Yankees but two years as the bullpen coach of the Dodgers, another data-rich team. While it doesn’t have to be Brad, but someone with a similar line of thinking is necessary to truly invest in analytics.
The quote from Duquette’s July interview is very telling about the state of the Orioles organization, and is worth repeating here.
You have to do a number of things well to compete in professional sports, but we had identified the areas that we needed to improve in — technology, international scouting facilities, the draft, strengthening our analytics, investing in our international scouting, investing in more front office staff to be more in line with our competitors…
On top of this, the organization needs to hire a manager. If they treat each of these decisions as separate decisions—putting manager, analytics, technology, etc. each in their own little kingdom—little will have been done to truly improve the teams investment in analytics. Analytics pervades all aspects of the game, and the Orioles’ commitment to truly integrating them into the decision making process will go a longer way to determining the team’s future success than mere individual hirings.
Orioles Analyst
Dr. Stephen Loftus received his Ph.D. in Statistics from Virginia Tech in 2015 and is an Assistant Professor of Mathematical Sciences at Randolph-Macon College. Prior to that, he worked as an Analyst in Baseball Research and Development for the Tampa Bay Rays, focusing on the Amateur Draft. He formerly wrote at FanGraphs and Beyond the Box Score. As a lifelong fan of the Orioles, he fondly remembers the playoff teams of 1996-97 and prefers to forget constantly impending doom of Jorge Julio, Albert Belle’s contract, and most years between 1998 and 2011.