A Much Improved Formula To Successfully Streaming Pitchers


Part II


In part one of trying to find a formula for successfully streaming pitchers, I used opponents stats based on the previous 14 days. I received a lot of feedback on that article, which was amazing! A lot of people suggested looking at pitcher stats as well. While that is something to be done in the future, my goal here was to create something easy. Easy enough for anyone to be able to use it (ie. the common fantasy player). As for the formula looking at the last 14 days, the best ERA I arrived at was 4.63. That just wasn’t good enough. I just had to dive deeper. So here we go, part two (much better results coming)!


This account and website were built on streaming pitchers, so who better to dive in and figure out a formula that can lead to streaming success? After asking a few people in the industry which offensive stat holds the most weight, the most common answer was wRC+. Using wRC+ combined with other stats produced some very interesting results, but before I get into that there is a caveat here.

It is impossible to find ownership rates on players for specific days in the past. For this study, I wanted to use pitchers who were owned 30% or less on the day of their start. Pitcher’s ownership fluctuates a ton, for instance, Lance Lynn was streamable in April. The subset of pitchers used was based on my streaming sheet from last year (everyone I streamed was 30% owned or under via Yahoo) and by using the obviously available streamer options such as Antonio Senzatela.

For this study, I looked at a team’s stats over the last 7 days. My thinking is you can find a team on a current cold streak. For instance, let’s say it was May 14th and I wanted to stream a pitcher. I would look to see which team was at the bottom of the league in wRC+ from May 7th to May 14th. Changing from the last 14 days to the last seven days really helped capture cold streaks. Side note: this can all be found on Fangraphs.com.

70 wRC+ Threshold



Right off the bat, streaming against teams who produced under a 70 wRC+ in the last seven days gave you a better ERA (4.52) than the other study’s best ERA (4.63). This is a good sample size and not only is the ERA slightly above average but the WHIP is right there as well. This was a great start and really showed that looking at the last seven days was the way to go. Before we go any further, I took these innings and found some fun and interesting stats.


Here are the pitchers who had the most starts in this sample size, as well as the underrated Miami Marlins staff.



Yusei Kikuchi was ridiculously random last year, opponents didn’t matter at all. How about Reynaldo Lopez’s stats? Streaming him with this method would have given you Jacob Degrom like numbers for seven starts. Then you have the entire Miami Marlins rotation. When meeting our threshold you could have streamed Brandon Woodruff with ten fewer innings. Awesome stuff here, let’s move on to improving the formula from here.


70 wRC+ Threshold + Pitching At Home


What is the first rule about pitchers that everyone knows? They usually pitch better at home (minus Coors). Therefore I took the above data and broke it down into pitchers who pitched at home.



Really good results here, the ERA and WHIP are well below league average and the K/9 ain’t too shabby either. Some pitchers whose stats were similar to this in 2019 were Miles Mikolas, Joey Lucchesi, and Zach Eflin.


70 wRC+ and 12.0 SwStr% Threshold


I could have stopped there but I really wanted to combine wRC+ with other stats to see if I could better this formula even more. I tested out a lot of different ones and the best one ended up being SwStr%. Streaming pitchers against teams who had an under 70 wRC+ and over 12.0 SwStr% in the last seven days produced these results:



This is just .01 better than the previous chart. The WHIP certainly went up but the better K/9 counters it. This is closer to Max Fried’s numbers from 2019.


70 wRC+ and 12.0 SwStr% Threshold + Pitching At Home


Just like I said earlier, I have to dissect the previous data and take a look at the pitchers who pitched at home. Here is what I got (drum roll):



Wow. The best part about this is you got 403.1 innings worth of it, which means you had plenty of opportunities to stream pitchers last year under these terms. Everything here is just great and these numbers are better than Eduardo Rodriguez’s 2019 and slightly worse than Jose Berrios’s 2019. If you took every streamer using this formula last year, you acquired two SP2’s out of it.


But Michael, what if I could only stream one of them per day? Don’t worry, I thought about that! In 2019 some of these starts by streamers had two or three guys going on the same day. If you only took one pitcher a day using this formula, here is the worst possible outcome you would have gotten.



Still great results, plus what are the chances you happen to take all of the worst possible starts within the formula? Even if so, you got Zack Wheeler x 1.5. All for free.


The Future


This is certainly a step in the right direction. The worst part about all of this is I cannot test this going further into the past, but what I can do is test it in the future. 2020 is basically a ruined season in terms of numbers. We have no idea what teams will do with pitching and there won’t be nearly enough innings pitched to test this out. Come 2021 I will certainly be tracking this method and others to see if it indeed is viable year after year. Until then, thank you for reading and let me know if you have any questions!


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