By:  Holly Horning & Kurt Snyder

Analytics is a system to help evaluate personnel decisions. It uses computers, software, video and stats to give a bigger picture of individual performance. It is a combo of statistics but with a human element included. It can dissect a pitcher’s performance pitch by pitch as well as tell managers which righty-lefty combinations work.

Baseball teams need to evolve with the times. If teams are taking advantage of technological tools that can help them make more educated personnel decisions, than why not jump on the bandwagon? It appears the Tigers finally will.

Totally Tigers jumps into the fray on analytics, but we can’t just dip our toe in first to check the water; you have to dive in full-bore.

1. What’s your opinion about analytics?

Holly – I love stats but they have to be within reason. They must have a non-interpretive formula, make sense, and also pass the eye test. I’m against stats as the sole analytical tool. But I’m always in support of options and increasing ways to interpret performance.

I like anything that can assist in identifying patterns because they are the most reliable ways to anticipate likely performance. But what makes analytics especially appealing is its ability, through advanced computer software programs, to see habits that humans cannot. I love the video capability that can break down a pitcher’s form into milliseconds. Well beyond what scouts and coaches can see.

But with anything, too little or too much of something doesn’t work. Analytics is a not a replacement for the ability to include the human element, the gut feeling or to evaluate the intangibles seen in such players as JD Martinez.

Kurt – Well, analytics definitely has its place in baseball and it can be impactful. They give teams the ability to identify patterns in data.

It took me a while to warm up to the idea of using data to make decisions on players to acquire. There are so many patterns to study to determine whether a certain player can be successful in a given role.

I believe the teams with smaller budgets have to take more of this data into account because they don’t have the luxury of trying to acquire the best players money can buy to build a winner. The Oakland A’s have a long reputation now of building teams based on data patterns that give them advantages with players who had previously been under the radar.

So, analytics is definitely an instrument you want part of your tool box, but it can’t be the only tool you use. In the end, you have to still trust your instincts and evaluate talent base on your knowledge of the game and all the intangibles that make players the right fit for your team.

Are there analytics to evaluate the interest level of Bruce Rondon? Are there analytics to determine leadership skills?

2. What kind of impact do you think analytics will have on the Tigers?

Holly – I have no idea why the Tigers, given their vast resources, have always been the last to adopt what other teams have been using for years.

One just has to look at the analytic departments of other organizations and you will see, for the most part, those teams with established departments are consistently in the mix.

Kudos to Brad for pushing Old School Dave to hire the Tigers first part-time analyst. And Al Avila shows how different he is by hiring 4 full-timers. The Tigers have placed near the very bottom of all 30 teams in analytics year after year due to Dave and Jim Leyland but this recent move puts them in the top half of MLB.

What this means is that the Tigers have another resource to finding the right players. Hopefully guys who don’t need huge contracts and are trending upwards in performance. Players who may be paid for their promise, and not for their past track record with another team.

Would the Tigers have signed Joe Nathan if they had an analytics department? I think we all know the answer to that $21 million question.

Kurt – The Tigers are near the top of Major League Baseball in payroll. They are a team that is becoming quite cost-constrained based on some salaries that restrict what they may want to do to improve their team.

They don’t have the Yankee luxury of digging through the menu at the finest of restaurants. But, they can now turn to analytics to uncover players who they wouldn’t normally consider to come in and help.

They will need this relatively new tool (for them) to find players to round out that bullpen. Avila has talked of how he will search for guys who could be candidates for a closer role but haven’t necessarily been closers before. I am assuming analytics will come into play here.

All in all, I am open. It certainly can’t hurt to get with the times.


  1. Analytics can help management make decisions and explain them to stakeholders. The main risk is “analysis paralysis,” where you’ve got a big amount of data you’re not sure how to interpret. The people who work with the data must be action-oriented, not just stat geeks.


  2. Can you tell me, in laymen’s terms, how analytics would could have convinced us not to go after Nathan in free agency? As I understood it, his previous season was very, very good.



    • Hi, John – Without knowing what analytic capabilities the Tigers have, Nathan would have shown at least a couple red flags. First, his age before signing with Detroit: 39. His last year with the Rangers being an outlier year and not representative of his typical performance. Reports of a change in his pitch use as well as a significant drop in velocity towards the end of 2013. His pattern of “dead arm” becoming more frequent. Without analytics, the Tigers would have had fewer options but with it, they might have uncovered other younger closer options. Thanks for reading – and for the question! – Holly


  3. Perhaps the reason analytics were put on the back burner was because of stubbornness or unwillingness to learn a new way to evaluate talent on Dave’s part. Jim’s many decades in the dugout didn’t require these new methods-experience over analytics. Besides “with Ilitch’s money, who needs analytics and sabermetics?”


  4. Considering the current team was built using the old fashioned method (re: gut feeling), with little or no regard for analytics, I don’t think one can expect an immediate drastic change in results. Thinking going to have to change, and the roster is going to have to change along with. It should be interesting, but have patiience, cuz it might take awhile.


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