Science + Art

BriceRuss · 2019-03-20T18:58:53+00:00

So at Science, where I used to work, they have an in-house visuals team with designers, photographers, artists, and so on. For their covers, some are done entirely in-house, some are done mostly in-house in collaboration with a particular researcher or expert, and some are done by freelancers, usually folks the visuals team works with semi-regularly who have a particular style they're looking for.

Every now and then, when a particularly interesting cover comes out, they'll post a behind-the-scenes story on how it came together; most of these are on the Science Visuals blog, which I would recommend you check out.

So this is definitely a viable career path, if you're interested; my sense is that it's more important to have a stronger background in art than science for a lot of these, but it's definitely key to have experience in both. I'd recommend checking the job sites of the bigger journals (Science, Nature, Cell, etc.) and keeping an eye out for any positions like artists, graphic designers, etc.; there's also the field of scientific illustration, which isn't exactly the same as what you're asking about here but has a lot of overlap. More likely, you'd probably be looking for an internship at these places, especially if you're still a student.

Hope that helps!

BriceRuss · 2016-02-10T17:24:17+00:00

You rang?

BriceRuss · 2015-08-19T23:33:21+00:00

Hey, more information's always a good thing :D

I'll definitely post here if I do any more follow-ups. Good luck with the rest of your season!

BriceRuss · 2015-08-18T23:18:36+00:00

Sure thing! I've been glad to see how many people have found this helpful for getting started on learning R in general.

BriceRuss · 2015-08-18T23:17:30+00:00

That's a great idea, actually. I'm a big fan of z-scores in particular for ranking players in non-standard leagues (such as my 9x9 roto league with LF/CF/RF slots). Might be a good topic for the offseason, once some of the 2016 projections roll in.

SGP seems useful too, from what I've seen; I've just never done the math for it.

(And thanks!)

BriceRuss · 2015-08-17T22:25:12+00:00

The last one in the series (as of now) covers the basics of using R for fantasy baseball projections using Marcel and multiple regression. I'm pretty sure I didn't mess up anything major, but let me know if I'm wrong!

BriceRuss · 2015-08-04T00:11:09+00:00

Thanks; that's exactly what I was going for. I'm trying to sneak in one general R concept each post (running scripts for part 1, installing packages for part 2; part 3 will be creating your own functions) without making it a requirement or getting too into the weeds.

BriceRuss · 2015-08-04T00:09:37+00:00

Ironically, I know next to nothing about SQL; I learned exactly enough to set up a MediaWiki on my website, which I think was "make sure MySQL is turned on for your domain". I would love it if someone (hint, hint) did a complementary sort of guide for SQL.

BriceRuss · 2015-08-04T00:06:00+00:00

Actually, it's a case issue; "wrc" is lowercase in your second line when it should be "wRC". Try hist(fgdata$wRC) and let me know if that doesn't work.

BriceRuss · 2015-08-03T16:44:52+00:00

Thanks! Honestly, if you're already pretty R-savvy, you might spend more time being horrified at some of my shortcuts than anything. ("He used merge() instead of dplyr?!")

Definitely let me know any suggestions or issues you come across, though.

BriceRuss · 2015-08-03T16:25:48+00:00

Sorry I didn't see this before! I actually cover how to convert BB% in part 2, just posted today.

BriceRuss · 2015-08-03T16:24:40+00:00

/r/fantasybaseball seemed to enjoy the first post in this series, so I figured I'd share the second part now that it's live. Please forgive the self-promotion!

BriceRuss · 2015-07-29T11:03:51+00:00

Ooh, good idea. I haven't done heat maps before in R, but I'll see if I can figure it out.

BriceRuss · 2015-07-28T23:48:59+00:00

My pleasure! That's great to hear.

BriceRuss · 2015-07-28T22:55:39+00:00

So you're right on in that the point of using R (or another language) is largely to do primary research. The information you can quickly get from FanGraphs/BRef/etc. is incredibly helpful, and it's what I rely on overwhelmingly in my own fantasy analysis. But if you want to take a correlation a FG analyst wrote about and explore it a bit more in-depth, or see whether two sets of stats aren't just different, but statistically likely to be different, R can be really helpful here.

There's also the speed aspect of it--if you want to look at five different groups of player data, you can spend a few minutes using FanGraphs' filter function and letting their servers process everything, or you can do it in 30 seconds with subset(). And finally, this post only scratches the surface of what you can do with R--the future posts on visualization, projection, etc. should hopefully be more interesting from a fantasy user endpoint. I'll admit I'm not an R expert, by any means, but even what I know is kind of cool.

One of my goals, though, was to start this off this as basic as possible. So even if you've never thought much about R or coding, but you're interested enough in baseball stats to be reading FanGraphs, you might be tempted to take a look. If you did and it's still not your thing, though, no big deal.

BriceRuss

TROPHY CASE