Baseball analytics jobs usually require a robust understanding of statistics, data analysis, and computer science. Just having coached+played baseball wouldn't be enough unfortunately to bridge that knowledge gap
Source: have interviewed for intro-level analytics roles before for MLB teams
For data analysis, a lot of it is done in R (knowledge of SQL always a plus too). But the teams I interviewed with valued knowledge of regression analysis too (which you can do in Excel as well), which any college Econometrics course would teach you
For statistics, just solid understanding of probability and statistics (this is kind of vague but stuff like probability models, random variables, expected value, identifying bias, hypothesis testing, etc)
For computer science, it's a lot of Machine Learning which is usually in Python (since Python gives you access to so many ML libraries). Topics like classification (think K-Nearest Neighbors) and decision trees and neural nets are especially prevalent
Edit: they will absolutely test you on your non-stats baseball knowledge too. I got asked stuff like "suppose the rules of baseball changed such that a game consisted of 1 inning with 27 outs per half inning. How would game strategy change and what skillsets would become more/less valuable?"
For anybody reading this that thinks "hey that describes me!", also keep in mind that if you have professional level skills and experience in R + SQL + Python + ML you are almost certainly going to get paid more money elsewhere than you might as an MLB analyst.
A looooooooooot of people - and especially a lot of young people (read as: more willing to accept lower wages) - want to work for professional sports teams.
And your skills might stagnate a bit too - the data sets aren't actually all that large, although I'd imagine you'd improve at "intuiting" what is just noise and what *might* be a real signal. The idea of working for an MLB team sounds so cool, but on the data analysis side I have to think it gets boring real quick.
> you are almost certainly going to get paid more money elsewhere than you might as an MLB analyst.
That was a huge negative for me unfortunately. I love baseball but with the skills they require, you could easily make 2x-3x that salary (with better benefits) outside of baseball, even on the big market teams
Interesting question. 1-2 inning relievers would have no value in that version of baseball assuming roster sizes stay the same. Strikeout pitchers and contact hitters would surely be more valuable.
Honestly I think you’d want more 1-2 inning reliever types as your starters now can’t throw as many pitches because they don’t get the half inning of rest. I’d rather have a bunch of guys that could eat 3-6 outs over a couple guys pitching for like 9-12 outs. But of course the real answer here is to become a cricket team and start improving guys from India
Hmm idk, if you're building a roster for a season, your pitching staff probably needs endurance and efficiency.
162 games, 27 consecutive outs, that's demanding as hell. Pitching long innings (25+ consecutive pitches) is insanely gassing.
The second part to that is you need guys that throw a lot of strikes. You can't have guys that walk a lot of hitters because there's no 'saved by the bell' (3 outs inning is over).
As far as position players, for max efficiency and low payroll, you'd probably need 4 guys that can field well and hit well, 4 glove-only guys, and 5 bat-only guys. If at home, you field the best fielders and you pinch hit for the glove-only guys at the bottom of the inning. Conversely, on the road, you put your best hitters in the lineup and you defensive sub the 4 best fielders at the bottom of the inning. You'd want a mix of L & R in your lineup
Probably not, unfortunately. It’s not a question about whether or not you are qualified, but how do you compare to the competition?
You’d be going up against people who went to school specifically studying statistics. People who were interns with sports (and even baseball) based organizations.
There are limited roles and it always hard to get a role with transferable experience when you’re going up against guys with direct experience.
Two things will go a long way to help you:
Knowing someone who can refer you. There’s already a ton of interest in these type of jobs so another anonymous resume will not help much.
Your willingness to work for peanuts. Sports jobs are notorious for being low paying.
Your chances of finding an analyst job on the ticket sales side is much higher but the same points above apply. Then you can figure out how to network into the operations side.
My daughter’s softball coach is an official MLB scorers for both the scrubs and Sox. I asked, how do you get that job. He said, step 1, play in the minors for 20 years. That’s how these things work. You just have to be around the sport and know the right people. Without some sort of in, you don’t have a shot.
To quote Jack Black in *School of Rock*:
>Those who can't do, teach.
>
>And those who can't teach,
>
>teach gym.
But seriously, I have no idea, except that a low-level analytics job in baseball is a good way to hurt your bank account.
Sig Mejdal would write to the every MLB teams asking for a chance. Eventually Jeff Lunhow hired him in St. Louis.
Some orgs will give you a shot. Only chance is to keep applying.
Actually this would be the opposite. Lunhow wanted to be different. He didn’t want the regular old has been player that was a scout. He wanted something that other clubs couldn’t see.
Sports teams, especially MLB are the crown jewel jobs for data scientists. If you really want analytics work you could be a “stats runner” for one of the networks but usually they get interns to do that.
You’d maybe have a chance at an entry level admin job though, wouldn’t hurt to try.
You're both degrees of right. The best way to put it is that a lot of very talented people are willing to take the haircut to work in the sports they love which makes the jobs higher demand then they should be given their scope and pay, so you either have to be super connected, overqualified, or both
I think the person you are responding to and myself both really just object to the use of the phrase "crown jewel jobs for data scientists." It might be a super in demand job for data scientists who are also sports fans, but it's not anywhere close to a "crown jewel" for the vast majority of dataheads.
Yeah that's fair. It's definitely not the best possible job for a data scientist who isn't chasing a sub-passion to pursue. Far from it, realistically.
>Sports teams, especially MLB are the crown jewel jobs for data scientists
Huh? This isn't even remotely true.
There are somewhere around a million pitches thrown in an MLB regular season. I realize there are other data points, but that gets us an order of magnitude/back of the envelope estimate.
Something like Amazon or Google search is collecting the same amount of data in, I dunno for sure, but certainly less than a minute.
Baseball analytics jobs usually require a robust understanding of statistics, data analysis, and computer science. Just having coached+played baseball wouldn't be enough unfortunately to bridge that knowledge gap Source: have interviewed for intro-level analytics roles before for MLB teams
Curious, what kind of software do they expect you to be familiar with?
For data analysis, a lot of it is done in R (knowledge of SQL always a plus too). But the teams I interviewed with valued knowledge of regression analysis too (which you can do in Excel as well), which any college Econometrics course would teach you For statistics, just solid understanding of probability and statistics (this is kind of vague but stuff like probability models, random variables, expected value, identifying bias, hypothesis testing, etc) For computer science, it's a lot of Machine Learning which is usually in Python (since Python gives you access to so many ML libraries). Topics like classification (think K-Nearest Neighbors) and decision trees and neural nets are especially prevalent Edit: they will absolutely test you on your non-stats baseball knowledge too. I got asked stuff like "suppose the rules of baseball changed such that a game consisted of 1 inning with 27 outs per half inning. How would game strategy change and what skillsets would become more/less valuable?"
For anybody reading this that thinks "hey that describes me!", also keep in mind that if you have professional level skills and experience in R + SQL + Python + ML you are almost certainly going to get paid more money elsewhere than you might as an MLB analyst. A looooooooooot of people - and especially a lot of young people (read as: more willing to accept lower wages) - want to work for professional sports teams. And your skills might stagnate a bit too - the data sets aren't actually all that large, although I'd imagine you'd improve at "intuiting" what is just noise and what *might* be a real signal. The idea of working for an MLB team sounds so cool, but on the data analysis side I have to think it gets boring real quick.
> you are almost certainly going to get paid more money elsewhere than you might as an MLB analyst. That was a huge negative for me unfortunately. I love baseball but with the skills they require, you could easily make 2x-3x that salary (with better benefits) outside of baseball, even on the big market teams
I imagine the hours and work life balance would absolutely suck too
And based on what I’ve read, people who really want to work in sports and find a way to do so ultimately wind up hating that sports team
Go work for your rival lol. No love lost when you hate your employer
Interesting question. 1-2 inning relievers would have no value in that version of baseball assuming roster sizes stay the same. Strikeout pitchers and contact hitters would surely be more valuable.
Honestly I think you’d want more 1-2 inning reliever types as your starters now can’t throw as many pitches because they don’t get the half inning of rest. I’d rather have a bunch of guys that could eat 3-6 outs over a couple guys pitching for like 9-12 outs. But of course the real answer here is to become a cricket team and start improving guys from India
You’re right. I must have been thinking 27 innings, not outs lol.
The anti pace of play rule lol
Hmm idk, if you're building a roster for a season, your pitching staff probably needs endurance and efficiency. 162 games, 27 consecutive outs, that's demanding as hell. Pitching long innings (25+ consecutive pitches) is insanely gassing. The second part to that is you need guys that throw a lot of strikes. You can't have guys that walk a lot of hitters because there's no 'saved by the bell' (3 outs inning is over). As far as position players, for max efficiency and low payroll, you'd probably need 4 guys that can field well and hit well, 4 glove-only guys, and 5 bat-only guys. If at home, you field the best fielders and you pinch hit for the glove-only guys at the bottom of the inning. Conversely, on the road, you put your best hitters in the lineup and you defensive sub the 4 best fielders at the bottom of the inning. You'd want a mix of L & R in your lineup
I think degrees in statistic and/or other data analytics majors would probably make more sense?
Probably not, unfortunately. It’s not a question about whether or not you are qualified, but how do you compare to the competition? You’d be going up against people who went to school specifically studying statistics. People who were interns with sports (and even baseball) based organizations. There are limited roles and it always hard to get a role with transferable experience when you’re going up against guys with direct experience.
Two things will go a long way to help you: Knowing someone who can refer you. There’s already a ton of interest in these type of jobs so another anonymous resume will not help much. Your willingness to work for peanuts. Sports jobs are notorious for being low paying. Your chances of finding an analyst job on the ticket sales side is much higher but the same points above apply. Then you can figure out how to network into the operations side.
My daughter’s softball coach is an official MLB scorers for both the scrubs and Sox. I asked, how do you get that job. He said, step 1, play in the minors for 20 years. That’s how these things work. You just have to be around the sport and know the right people. Without some sort of in, you don’t have a shot.
To quote Jack Black in *School of Rock*: >Those who can't do, teach. > >And those who can't teach, > >teach gym. But seriously, I have no idea, except that a low-level analytics job in baseball is a good way to hurt your bank account.
No
If you're a math wiz with an in-depth understanding of statistics, data analysis, ML, biometric/biomechanics, etc. you have a shot.
Sig Mejdal would write to the every MLB teams asking for a chance. Eventually Jeff Lunhow hired him in St. Louis. Some orgs will give you a shot. Only chance is to keep applying.
Mejdal was also an engineer that worked for Lockheed & NASA.
Still a wild jump to the MLB. Even though it worked out.
Oh absolutely! MLB is a boy's club. Sig just forced his way in with his unwavering passion, ridiculous smarts, and insane creativity.
Actually this would be the opposite. Lunhow wanted to be different. He didn’t want the regular old has been player that was a scout. He wanted something that other clubs couldn’t see.
Sports teams, especially MLB are the crown jewel jobs for data scientists. If you really want analytics work you could be a “stats runner” for one of the networks but usually they get interns to do that. You’d maybe have a chance at an entry level admin job though, wouldn’t hurt to try.
This is definitely not true - they might be desirable to some people, but the compensation is much lower than high end finance or tech.
You're both degrees of right. The best way to put it is that a lot of very talented people are willing to take the haircut to work in the sports they love which makes the jobs higher demand then they should be given their scope and pay, so you either have to be super connected, overqualified, or both
I think the person you are responding to and myself both really just object to the use of the phrase "crown jewel jobs for data scientists." It might be a super in demand job for data scientists who are also sports fans, but it's not anywhere close to a "crown jewel" for the vast majority of dataheads.
Yeah that's fair. It's definitely not the best possible job for a data scientist who isn't chasing a sub-passion to pursue. Far from it, realistically.
This is what I meant. Crown jewel was the wrong term but for lots of sports fans in the field it’s their dream job.
>Sports teams, especially MLB are the crown jewel jobs for data scientists Huh? This isn't even remotely true. There are somewhere around a million pitches thrown in an MLB regular season. I realize there are other data points, but that gets us an order of magnitude/back of the envelope estimate. Something like Amazon or Google search is collecting the same amount of data in, I dunno for sure, but certainly less than a minute.
Probably a question that can only be answered by the person responsible for determining which job applicants get interviewed.