What’s All Included in the DFS Baseball Projections Model

I fired off a few tweets yesterday explaining what is all included with the baseball projections and why I’ve embarked on this project. This fall I started making hockey projections DFS Hockey Projections and after a few growing pains and some self-taught lessons in excel; I was able to put out a product that was both used by some of the highest bankroll players in NHL DFS and was profitable for the new players who picked up hockey during the NBA All-Star break. 

I am now transitioning that same process to baseball. The beauty of baseball is it’s all about the numbers, especially the split stats. How well does Chris Davis hit RHP in Toronto? What’s the reasonable expectation that Bryce Harper hits a home run on opening day? It’s right about 38% by the way. How well does Madison Bumgarner project to pitch on opening day against Milwaukee? He’s my highest projected pitcher on DraftKings, and the topic of my next article.

I have over 120 different metrics calculated to produce the expected fantasy points for each hitter on five different sites. Included is data for Draft Kings, Fan Duel, Fantasy Aces, Draft Day, and Fantasy Draft. 

The Basics


Your basic dashboard has all the information you’d want right at your finger tips, like which hand the player hits with, which position he is eligible for by site, who the opposing pitcher is, what hand that pitcher throws with, and the split stats against the starting pitcher like on-base percentage, slugging percentage, weighted on-base percentage of isolated power.

The important numbers are the ones listed in green/red in the middle. In the column “DKEFP” you will see the expected fantasy points for that day. This is the magic number you want to use if you only have a little time to look at the data. Over 120 statistics are used to project that one particular number magic number. The next column over has the salary information for that site listed as “DK$”. The next column to the right is maybe the most important one. There you will find the value for each player. This is calculated by taking the salary divided by the expected fantasy points, and it gives you a dollar per point number.  Take a look in that column, there is some real value in Ben Revere and Daniel Murphy on opening day. 

The Details


Further down the sheet is some more detailed information split into each specific category where each player will accumulate points for the day. These are broken down by projected points for singles, doubles, triples, home runs, RBI’s, runs, stolen bases and walks. While we are talking about fractions of totals here, you can easily see which players project well based on the conditional formatting used and the ability to sort each column of data. 

Here you see Denard Span and Ben Revere have a pretty good chance of getting on base via a simple base hit. Daniel Murphy, Denard Span and David Ortiz project well to finish the day with a double, while Chris David and Bryce Harper are the most likely to hit a home run. 


Factored into each of these categories are the numbers you don’t see. The graphic above shows you the stats used to calculate just the likelihood of each player drawing walks during the game. Three year splits as well as last years split are weighed against each other for the hitter along with the pitchers penchant for issuing free passes, weighed both over three years and last season. Each stat is weighed by the split of both the hitter and the pitcher. Lastly a bullpen factor is used and correlated to each plate appearance every batter is expected to see that day. 

Every single category of data has this same engine behind it, and will be updated every day of the season for both hitters and pitchers. The time used to research this information is expensive; and baseball is a long season. Give yourself the edge with data needed to win consistently this season by checking out our membership options. It’s #DataForWinning

Adam Jazdzewski

I am the founder and owner of DFS Datalytics. I've been stats minded even as a kid. I used to write down my own stats in NHL '95, I've played season long fantasy sports since the mid 90’s and have made the jump to DFS three seasons ago. I specialize in NHL and NASCAR. Catch my on twitter @LedgerSko and @DFSDatalytics #DataForWinning

ledgersko has 223 posts and counting.See all posts by ledgersko

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