• CruzinToVictory

    RG Product Coordinator

    • Blogger of the Month

    Hey Grinders,

    I’m extremely excited to announce the release of the Beta version of my personal MLB model! I call it the Complete Rating UtiliZation Model, or CRUZ (I know, I’m so clever!). I’ve been hard at work tweaking and honing this thing all season, and while it’s an ever evolving process, I feel like it’s finally ready for a public beta version.

    Note/Disclaimer: Please remember that this is, in fact, in the early beta stage. I’m releasing it in it’s current form as a free tool to acquire feedback before next MLB season. With that in mind, enjoy!

    You can find these models in the Daily Research console, or you can go directly to the DraftKings version or the FanDuel version.

    There are a ton of factors that go into this model, but here are some of the individual stats and factors that go into each rating:

    • Vegas odds
    • Batter splits (L/R, H/A)
    • Batter stats for each split, including: K%, BB%, ISO, and PFwOBA (this is a stat that takes Park Factors into account when calculating wOBA)
    • Pitcher stats for each split, including: K%, BB%, wOBA allowed, SIERA, Batted Ball profiles (GB%/FB%)
    • Bullpen matchup (ERA, K%, SIERA)
    • Position in the batting order
    • Surrounding wOBA – This stat is unique to my model. It pulls the actual lineup (or projected lineup, if it isn’t confirmed yet), and averages the wOBA of the batter before and after the hitter in question to give an idea of how much support he has around him.

    I also wanted to include a bit more emphasis on the bullpen, as I believe it is often extremely underrated when looking at MLB DFS. So, I’ve partnered up with RG’s own Paul Sporer, who’s resume includes our “Sporer Report” MLB series and the Pitcher Breakdown last season. Paul has an unmatched knowledge of MLB pitching rotations, and every morning, he manually adjust each team’s bullpen rating based on many factors, such as which closers will be available that night.

    Model Types

    At the launch of this beta, we have three different model “types” that weigh each category differently depending on the goal of that model. Long term we will be automating this process so that you can adjust the weights as you see fit, but for now we have three versions:

    • A “Balanced” model (this is the one I personally use the most)
    • A “Cash” model that weighs things like Vegas Odds and batting order more heavily
    • A “GPP” model that weighs high upside stats like ISO more heavily

    General Notes

    I’ve tried to include just about everything you might want all in one place while using a model such as this. If you simply want a list of players and ratings, that’s right there for you. But if you want to dig a little deeper, I’ve shown a metric ton of stats for every player based on their matchup, so be sure to check out the Legend if you’re not sure what a particular column means.

    Many columns are also color coded for easy comparison between columns. Blue is the best matchup, followed by dark green, light green, yellow, orange, and red.

    The included players are based on confirmed lineups (indicated by the green check mark), but if there is not a confirmed lineup for that team, it will use the RotoGrinders projected lineups from the MLB Lineups page.

    Be aware that I’ve weighted down players with extremely low sample sizes, but there are instances where a low sample size might inflate or deflate a player’s rating. I’ve shown the number of plate appearances so you can take this into account quickly.

    These models are updated periodically as lineups come in, so be sure to check the “Last Updated” note at the top of the page.


    As we’re nearing the end of the MLB season, I’ve decided to release this in it’s current beta form to get feedback from you all so that I can make even more improvements for next season. Take a look, let me know what you think, and leave any suggestions here!

  • CruzinToVictory

    RG Product Coordinator

    • Blogger of the Month

    @fantasybender said...

    How does ownership play into this model? Any deductions on the GPP model for highly owned players? Please advise.

    Ownership percentages don’t play into the model at all, since it’s extremely difficult to project a player’s ownership percentage.

    Instead, the GPP model favors more “boom or bust” players by focusing on power stats like ISO and the bunch.

  • rsigler65

    daggit! are we off the grid again today?

  • Goodster

    this is absolutely awesome! great work man.

  • rsigler65

    Just wondering about the bullpen data. I noticed in the daily research bullpen tab that Papelbon is still with his old team and the page hasn’t been updated in 3 months. Is that same data used in the model or no?

  • LetsgoMets85

    Will this model be updated for the playoffs?

  • LetsgoMets85

    Can we get Cubs/Pirates stats?

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