Fantasy sports are huge in America. When fall comes around, my family, friends, and I play the hugely popular fantasy football, which I happened to actually win my league this year. But with the winter out of the way and (hopefully) baseball coming back soon, I wanted to talk about one of my favorite things to do which is fantasy baseball. I have worked on and finished a number based ranking system of position players through Google Sheets and I would like to share it with you guys, even though I know most drafts have probably been completed by now.
First off, I made this more specifically for my fantasy league which is a typical 5x5 category league. But I have a strategy for hitters that I like to use which is to only focus on runs, home runs, and RBIs. I have two reasons for this, one is that I feel that those three stat categories are the most stable from week to week compared to batting average. Reason number two is that stolen bases do not happen as much anymore in a typical baseball game, so I can find one guy that can get me a high amount of stolen bases and that category can still be won on a weekly basis.
For my rankings, each player has three scores: Counting Pick Score, Per Game Pick Score, and Total Score. When I started making the equations for the three, I had decided I should just average the three stat categories. However, I felt that there would be a problem with doing that, as I wanted all three of them on the same scale so I wouldn’t be averaging three completely different numbers. For example, last season Jose Abreu had 85 runs, 33 home runs, and 123 RBIs vs Eugenio Suarez who had 87 runs, 49 home runs, and 103 RBIs. In fantasy, you need to win as many categories as you can and Suarez won the run and the home run categories over Abreu’s win in the RBI category, so Suarez is the better fantasy player, right? Well, if you were to just simply average their stats out, Abreu would be the better fantasy player with an average of 80.33 compared to Suarez who had an average of 79.66. It is a very tough decision of who to choose either way and it may not seem to matter, but every slight advantage helps to win.
That made me decide to put a weight to runs and home runs as players have lower numbers on average in those categories compare to RBI. These weights can be seen below:
I calculated these out by taking the average per-game RBI of all the players in my rankings and dividing it by the average per-game run totals and home run totals to come up with their weight and I just left RBI with the weight of 1 as it did not need to be changed.
So now that I have my weights for my three numbers in my averages, I could start to make the equations. The Counting Pick Score is calculated by taking the counting value of each player and multiplying it by its respective weight and then dividing by 3, the average of this number came out to be 84.6. However, I knew from the start that this number would really only be useful to compare players who played around the same amount of games because it is based on counting stats. This problem can be shown with Joey Gallo having a 56.8, well below the average even though in his 70 games he was a beast. It can also be shown that the range goes from 10.1 (Giancarlo Stanton) to 127.9 (Pete Alonso), a range of 117.8 is not acceptable.
This led to me making the Rate Pick Score, it is basically the same calculation, but it is using the per-game numbers instead of the counting ones and it is multiplied by 100 to make it look nicer. The average for this number came out to be 63.6 with the range being 31.2 (Francisco Mejia) to 87.5 (Mike Trout). These numbers look a lot better, there is not a huge deviation anymore and Giancarlo Stanton is not rated the worst player in fantasy.
When making my total score, I was originally going to just slap the two scores together to make one combined score, but then I realized, if I don’t feel that the Counting Score is as reliable as the Rate Score, why would I make them of the same importance in the final equation? I wasn’t going to just make the Rate Score weighted insanely higher than the Counting Score, though, I felt that it had some importance as well. You need at least some sort of sample size if you want your rate stats to have any credibility, so I gave the Rate Score a weight of 1.5, so that it could be worth more and that there is still some sample size put into the equation. The average of the Total Score was a flat 90 with a range of 35.7 (Mejia) to 124.3 (Bellinger and Trout). Here is a visual of how I calculated these numbers if you’re still confused:
Let me say this though, I would not just look at these rankings while making picks. These rankings are made for how I typically like to draft based on my three core stats. So this would not include the chance of a guy breaking out or crashing down due to his BABIP, hard-hit rate, pull%, flyball%, etc.. Also, this is just based off of the 2019 season (2018 if injured), so it will have a guy ranked very low if they had a bad year (Jose Ramirez) or if they were hurt almost all season (Giancarlo Stanton), that is something I could work on with this in the future, but for now, it is a little limited.
I love fantasy baseball, I think it is one of the best times of the year. Making this was a very fun time for me and I hope you guys can use this to find some sleepers in your draft and possibly even implement the same draft strategy I have! You can find the list below:
Note: not all players are listed, this list has 96 hitters
***ALL STATS FOUND FROM FANGRAPHS
Hozzászólások