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u/Metlover · 24 pointsr/Sabermetrics

I'm usually pretty optimistic for people when it comes to posts asking about "how do I get started in sabermetrics" because I was in that position once as well, and it's worked out okay for me, but I want to be a bit more realistic, because I think there is a big red flag that you should recognize in yourself in respect to this.

There are a couple ways to get jobs in fields that require sabermetrics, but you should be aware: there are very few, they are highly competitive, and they require a good amount of work.

The traditional progression for doing sabermetric work is usually something like:

Stage|Level of Sabermetric Experience|Work you're qualified to do|
--:|:--|:--|
1|You look up stats online to form arguments about baseball|Personal blogging, entry-level analytics writing (FanSided, SBN, other sites)|
2|You put stats into a spreadsheet to visualize data or calculate something new to form an argument about baseball|Personal blogging, entry-level analytics writing (FanSided, SBN, other sites), heavier stuff if you're very lucky and a good writer (bigger sites like FanGraphs, Baseball Prospectus), general baseball coverage that isn’t heavily analytical|
3|You use code with baseball stats to visualize data or calculate something new to form an argument about baseball|Heavier analytics writing (SBN, FanGraphs, Baseball Prospectus, The Athletic), entry-level baseball operations work|
4|You use code to create your own models, predictions, and projections about baseball.|Extremely heavy analytics writing, baseball operations/team analytics work|

From your post, it sounds like you're somewhere between #1 and #2 right now. However: "after trying [coding] out I did not like it." You have a very large barrier keeping you from making the jump to stage 3.

If you actually want to go into a sabermetric field as a career, you need to know how to code. Not with Javascript, mind you, but other languages (Python, R, SQL, etc.). I would advise that you try out Python or R (Analyzing Baseball Data with R is an excellent introduction and gives you a lot of practical skills) and see if those really suck you in - and believe me, they need to suck you in. If you really don't like it, don't force yourself to do it and find some other career path, because you won't be able to succeed if you can't enjoy the work that you do.

FanSided has very low barriers of entry and the compensation reflects that - you cannot make a career out of blogging for FanSided. Even if you get to where I am (stage 4), if you're lucky, you might land a contributing position at a site that pays decently for part-time work. There are extremely few people who are somewhere between #3 and #4 who can make a full-time living off of baseball work, and they do it because they like what they do - if you don't like coding and working with baseball data in that environment, you're not going to be able to beat out everybody else who's trying to get there.

Let's say that you work your rear end off, you get to stage three or stage four. What options are available to you? There's maybe a handful of people who work in the "public" sector - that is, writing for websites like FanGraphs, Baseball Prospectus, The Athletic - who make enough money to make sabermetrics their full-time job. It will take a hail fucking mary to land one of those jobs, regardless of how talented you are, and you'll basically need to work double-duty on both sabermetrics and whatever your main hustle is until one of those positions opens up, and even then, you're not guaranteed anything.

You could also work for a team! There are far more positions available, they pay better, you have more data to work with, better job security - this sounds great, right? Problem is, the market cap for analysts are at about 20 per team, so there's something like 600 analyst positions that could be available in the future (I can't promise that the MLB will ever have 600 analysts total at any given time, but that's an upper estimate). And almost half of those are already full! There's not a whole lot of brain drain from the industry, so it is still extremely hard to break in and you're still going to be competing with the absolute best people in the industry. You will have to love to code and do this work because everybody you're competing with already does, and everybody else is willing to work twice as hard for it.

My advice to you is this: try out R or Python with baseball data. See if it's enough to get you addicted. See if it starts to occupy every ounce of free time you have, and you feel comfortable with it, and you're willing to put yourself out there and advertise your own work. I'm a full time student and basically every ounce of my free time is put towards working with this stuff, like it's a second full-time job for the past three years, and I'm still a bit of a ways away from making a living off of this. If you can't learn to love it, your time and energy are best spent elsewhere.

u/[deleted] · 2 pointsr/Sabermetrics

The Fangraphs leaderboards are hugely helpful for quick analysis. You can use the custom leaderboard feature at the bottom to combine leaderboards for different types of stats - for example putting BB%,K%,FIP, alongside Pitch F/X and batted ball stats. And you can export any leaderboard into Excel. I've spent countless hours over the past 5 years with that stuff.

Not sure how much research/reading you've done, but I'd highly suggest reading The Book by Tom Tango and MGL. It will give you an excellent base level understanding of how things work.

The Fangraphs glossary has helpful explanations of how stats work.

Another worthwhile research tool is Baseball-Reference's Play Index. It's worth the subscription fee.

If you want to go to the next level with Gameday data, you'll need to set up an SQL database. You can download all the data updated daily from Baseball Heat Maps. This is where you can really get into things, but it requires database skills.

If you want to do Pitch F/x without getting into databases, [Brooksbaseball] (http://www.brooksbaseball.net/) is the best tool around.

u/jonnypedantic · 1 pointr/Sabermetrics

My suggestion is to pick up an introductory stats text and learn about the basics before you even start this project. I don't want to discourage you from this undertaking, but this simply isn't the kind of project that you can do with your current level of statistical knowledge, to be frank. This is the textbook we used in my intro class. It's not perfect, but it does cover, well, the basics. That's just a start, of course. Your project will probably require more advanced techniques that aren't covered in that book or most intro texts. Good luck to you!

u/JoshuaSP · 1 pointr/Sabermetrics

So this is not the answer you are looking for just a heads up.

If I was just breaking into the sport and wanting to dive deep I would buy this book: http://www.amazon.com/Big-Data-Baseball-Miracles-20-Year/dp/1250063507

It's not a teaching type of book but it talks about the ins and outs of how Pittsburgh took the use of saber metrics to a entirely new level. It dives into the statistics and not only what they saw In them but how they applied them and the results of it. It's all written in narrative form so it's more of a story than a tutorial.

I personally think it is the best recipe for learning saber metrics from a global point of view and it can be entertaining enough to get the foundation you'd need to jump in yourself.

It also shows you just how much further these franchises are compared to the every day fans with their databases which I was surprised with.

u/immoralminority · 2 pointsr/Sabermetrics

I strongly endorse The Book from Tom. It's a really great read.

u/gilpdawg · 1 pointr/Sabermetrics

I can recommend several books.

Baseball Between the Numbers by the BP folks.
It's old, and some parts of it are outdated, but I cut my saber teeth on that thing. There's also another book in the same vein by the same group called Extra Innings.
https://www.amazon.com/Baseball-Between-Numbers-Everything-About/dp/0465005470/ref=sr_1_1?ie=UTF8&qid=1501900503&sr=8-1&keywords=baseball+between+the+numbers

The Book by Tango and MGL.
It's very nerdy, so it's not for everyone.
https://www.amazon.com/Book-Playing-Percentages-Baseball/dp/1494260174/ref=sr_1_3?ie=UTF8&qid=1501900528&sr=8-3&keywords=baseball+between+the+numbers

The newer(ish) Keith Law and Brian Kenny books are pretty good too. I'm too lazy to link to those and they are easy to find.

u/s1ax0r · 3 pointsr/Sabermetrics

This book is an excellent resource. It is composed of articles that tackle some fundamental concepts using sabermetrics. I would also recommend reading Moneyball and The Extra 2% to get an idea of the impact that sabermetrics are having on the game, and specific ways teams are implementing them.

u/noitamroftuo · 8 pointsr/Sabermetrics

yes, and its not, read this https://www.amazon.com/Book-Playing-Percentages-Baseball/dp/1494260174

ask yourself this: why would a hitting strategy work better to win 3 out of 5 games than 100 out of 162 games? answer: it wouldn't. the commentators on these playoff games are bad

u/JamminOnTheOne · 6 pointsr/Sabermetrics

Chris Jaffe has probably done more analysis of managers (and various strategies, like starting pitcher usage) than anybody in history. Here's his archive at Hardball Times (he was a prolific writer, there's a lot to scroll through), and his huge book on managers.

u/Waaait_For_It · 2 pointsr/Sabermetrics

I just picked up The Book and its fantastic.

u/Fetterov · 8 pointsr/Sabermetrics

Baseball Between the Numbers from Baseball Prospectus is a good read. I picked it up for $0.75 at a used book store!

u/DavidRFZ · 1 pointr/Sabermetrics

Unfortunately, the best metrics are proprietary. baseball-reference uses Baseball Info Solutions:
https://www.amazon.com/Fielding-Bible-Baseball-Info-Solutions/dp/0879465417

Fangraphs uses UZR which was developed by Mitchell Lichtman (MGL)

http://www.fangraphs.com/blogs/the-fangraphs-uzr-primer/

Fielding metrics on a play-by-play basis is very noisy. There is significant grey area as well -- positioning can often be as important as defensive skill and its hard to know who to credit for that.

Anyhow, qualitatively different fielding metrics tend to agree but it doesn't have anywhere near the same level of quantitative accuracy as PA-based offensive calculations.

u/Tallowo · 8 pointsr/Sabermetrics

Analyzing Baseball Data with R

https://www.amazon.com/Analyzing-Baseball-Data-Chapman-Hall/dp/1466570229

​

Walks you through learning the program using baseball stats as the foundation.

u/dankney · 3 pointsr/Sabermetrics

https://www.amazon.com/Analyzing-Baseball-Data-Chapman-Hall/dp/1466570229/

It's an introduction to baseball data, statistical analysis, and the R programming language.

u/slapnscratch · 3 pointsr/Sabermetrics

Check out this book: https://www.amazon.com/Game-Plan-Approach-Decision-National/dp/1475233353
It discusses the ages and such in which coaches decision making peaks.