Price Guide Source Code Now on GitHub

A commenter suggested that it would be nice to have the source code for the Price Guide available. I’ve thought about that a bit as I find myself with fewer resources to devote to this site. The more I’ve considered it, I’ve decided that it’s a pretty good idea. So the Price Guide source is now available on GitHub:

https://github.com/mayscopeland/priceguide

I have always tried to be very transparent about how the Price Guide works — writing up a lengthy explanation of the full details on the old site. So I view this in that same spirit. Most of the Price Guide ideas aren’t mine, so I feel like I don’t have a claim for keeping them a secret. So now both the concepts and the implementation are out there for everyone to see.

I’ve put the code out under a Creative Commons license that reflects my desire for the Price Guide to continue to be free (that’s gratis, not libre). That means it’s only available for non-commercial use. I’ve always offered the Price Guide as a free tool, and I would like for it to stay that way.

With the limited functionality of its current parking spot, I hope that someone is at least interested in putting the Price Guide up somewhere that restores the ability to enter keepers, upload projections, and run in-season stat updates. (Of course, that might also involve some maintenance of player IDs and formatting projections.) I’d still be willing to help out a bit.

Even better would be if someone had the desire to take this to the next level. I’m sure lots of people could top the design of my current interface. I’m sure there are features that would make the Price Guide much better. (I’ve always had a plan for adding rest-of-season projections — let me know if you want the details.) If that’s you, here’s your chance to to do it.

I’ll keep the site up-and-running in the meantime. But it will probably be similar to the way it has been for the past couple of seasons with limited updates.

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14 thoughts on “Price Guide Source Code Now on GitHub

  1. No matter where last player picked “goes” it is a credit to you that you did it and maintained for as long as you did. Thanks

  2. (posting here because I don;t know if there is a better place)

    When I do the price guide by 2013 stats, it doesn’t remove players from the NL when I set it for AL only.

  3. I’ve tried the code on github but have not been able to get it running yet. Any chance the 2013 stats will be updated?

  4. The price guide appears to be down. Mays, do you think it’s something you’ll iron out, or does anyone know if any other sites that have used May’s code to reproduce the price guide? Thanks!

  5. what an awesome tool — wish I had programming skills or I would get the source and host it for all of us. it’s a tough loss to the fantasy baseball community.

  6. Mays, one of my website members informed me the LPP source code was available (I hadn’t visited here in a while). Although I haven’t done much with it yet, I added 2013 stats and 2014 Steamer-Fangraphs projections and published it on my website, here:

    http://www.draftbuddy.com/baseball/lastplayerpicked/

    I removed some options that didn’t appear to be working in the short time I’ve spent with it so far, like ability to import and edit projections. Great to see it in its original glory though. Thanks very much for making it available.

    • The price guide was such a great tool … I have been googling like crazy to find a replacement to upload projections / enter keepers and spit out some auction values. I don’t have the ability to upload the source code to a website or maintain the infrastructure, but I’m really hoping it becomes available somewhere! Will check out draftbuddy…

    • Thanks for putting this up Mike. I’ve been working on my own spreadsheets using the post Mays made a long time ago how the Price Guide works and happily the results I get from what you have up matches very closely (using Steamer Razzball projections so some slight variation) which tells me I’ve been doing things right.

      However that also leads me to one irregularity I have come across with my pitcher rankings. I’m in a 10 team NL only 4×4 league with 9 pitchers (no distinction between SP and RP) and historically we have roughly a 60 SP/30 RP ration drafted. However when I run the iterations through my spreadsheet I get the opposite breakdown of 60 RP/30 SP and I noticed that the Price Guide is now spitting out a similar breakdown. I don’t think this happened before but I don’t have any of the original data I used from the guide from previous years to check. Looking at the results it appears the issue is with the xERA, it doesn’t seem to be valuing the IP difference between most SP and RPs enough (and because the iterations have spit out so many RPs the average ERA is a lot lower than if more SPs were involved). I know I can force a 60/30 split if I need to but I rather than it happened naturally and I’m just not seeing how right now. Any ideas?

      • Hi KG. I’m seeing what you are seeing from the LPP output using the Steamer projections. If we put it at 9 P then RP dominate the rankings in dollars and quantity, but forcing the starters as 6 SP, 3 RP, there are a lot more SP in the mix.

        When I first read your note I was going to say just because your league drafts 60 SP/30 RP, doesn’t mean that from a pure dollar value and projections perspective, it shouldn’t be reversed as 30 SP/60 RP. Maybe the RP provide better bang for your buck… if everyone hits their projections. The problem with stockpiling RP – even the top ranked ones – is they are a lot more risky. Closers get replaced at the drop of a hat. They don’t get as many opportunities (innings), so much smaller sample size to earn their stats, and the actual results are going to vary a lot more. Grabbing quality SP will be a much safer route to build a team around in your league… leading to the 60/30 split.

        As for the details of the math, you’re probably much closer to it than I am at this point. I haven’t had much time to go through the code in detail, or refresh myself on Mays’ methodology. WIth the results I’ve run, I think your ERA theory looks right. I’m seeing $5 for Clayton Kershaw’s ERA at 3.09 or $2 for Cliff Lee, each in 192 IP, while Jason Grilli is $7 at 2.49 or Kenley Jasnon is $9 at 2.22, each in 65 IP.

        There are a lot of middle relievers in here. Is it possible to set a combination of Save and IP minimum to form your draftable player pool? For example, start with Saves, say you include every RP with at least 10 Saves. Then every other pitcher to form your pool of 90 has to have a minimum X IP. That might be one way to approach it.

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