Starting Pitcher Outside Factors Chart
In the middle to late rounds of a draft, pitchers seem to blend together. Picking between two similar pitchers can be difficult. To help with these decisions, I have created a simple cheat sheet to determine which pitcher has an easier path to success based on several outside factors like schedule strength and bullpen quality.
The chart is simple. I went through each factor which may influence a pitcher’s prediction in which they have no control over. I collected projections on each metric and then found the z-score for each value. Greater than 0 is good, less than zero is bad. Then for each team, I added up the z-scores for a final overall value.
The cheat chart is not perfect. It’s to be used as a guide. For example, if a pitcher is a heavy groundball pitcher, the user may not want to add the team’s outfield defense and home park home run factor. A different user may have the perfect projection set except for bullpen and defense. They can ignore the rest of the information. Additionally, a user may want to create their own category weightings. Again, this is just a guide.
To start with, here are the categories and the where I got the values.
Category: Source
- RS/G: (Runs Scored by Pitcher’s team/Game): Projected standings page
- SOS (strength of schedule): From the process which Jeff Sullivan used in this article
- Overall Home Park (Factors): Park factors page
- Home Run Park (Factors): Park factors page
- OF Defense: From each team’s projection page
- IF Defense: Overall defense minus outfield defense
- Away Park: Average park factor for the other four teams in the team’s division
- Away HR Park: Average home run park factor for the other four teams in the team’s division
- Bullpen: Overal team bullpen FIP
- AL vs NL: +0.5 for being in the NL and -0.5 for the AL
And now the data.
| Team | R/G | SOS | All Home Park | Home Run Park | OF Defense | IF Defense | Away Park | Away HR Park | Bullpen | AL vs NL | Total |
|---|---|---|---|---|---|---|---|---|---|---|---|
| Angels | -0.1 | -0.9 | 1.1 | 0.9 | -0.1 | 1.3 | 0.6 | -0.2 | -0.4 | -0.5 | 2 |
| Astros | 0.0 | 0.0 | 0.4 | -0.7 | 0.4 | -0.3 | 1.0 | 0.8 | 0.6 | -0.5 | 2 |
| Athletics | -1.2 | -1.6 | 0.9 | 0.9 | -1.2 | -1.6 | 0.8 | -0.2 | 0.1 | -0.5 | -4 |
| Blue Jays | 0.6 | -0.7 | -0.4 | -0.8 | 0.8 | 1.3 | -1.0 | -2.6 | -0.4 | -0.5 | -4 |
| Braves | -1.2 | -0.4 | 0.2 | 0.5 | -1.0 | -0.6 | 0.9 | 0.5 | 0.2 | 0.5 | 0 |
| Brewers | -0.9 | -0.4 | -0.7 | -1.6 | -0.5 | -0.6 | 0.3 | 1.0 | -1.3 | 0.5 | -4 |
| Cardinals | 0.9 | 0.5 | 0.4 | 0.8 | -0.7 | 0.4 | -0.1 | -1.5 | 0.7 | 0.5 | 2 |
| Cubs | 1.4 | 1.8 | 0.2 | -0.3 | 0.7 | 1.4 | 0.1 | -0.8 | 1.8 | 0.5 | 7 |
| Diamondbacks | 0.5 | 0.2 | -1.1 | -0.3 | -0.5 | 0.0 | -0.8 | 0.2 | -1.0 | 0.5 | -2 |
| Dodgers | 0.0 | 1.9 | 1.1 | -0.3 | -0.2 | 0.6 | 0.5 | 0.7 | 1.8 | 0.5 | 7 |
| Giants | -0.1 | 1.4 | 1.1 | 2.1 | -0.6 | 1.9 | -0.8 | 0.2 | 1.8 | 0.5 | 7 |
| Indians | 1.0 | 2.0 | -0.4 | -0.1 | -0.7 | 1.6 | -1.2 | 0.2 | 1.5 | -0.5 | 3 |
| Mariners | 0.7 | -0.6 | 0.9 | 0.3 | 1.2 | -0.8 | 0.8 | 0.3 | 1.0 | -0.5 | 3 |
| Marlins | -1.1 | 0.2 | 0.4 | 1.6 | 0.2 | 0.2 | 0.8 | -0.2 | 0.4 | 0.5 | 3 |
| Mets | -0.9 | 1.0 | 1.1 | -0.1 | -0.6 | -2.0 | 0.3 | 0.9 | 0.4 | 0.5 | 1 |
| Nationals | 0.7 | 1.3 | 0.0 | 0.4 | -1.0 | -0.5 | 1.0 | 0.6 | 0.6 | 0.5 | 4 |
| Orioles | 0.3 | -1.5 | -0.4 | -1.1 | -1.7 | 1.7 | -0.9 | -0.8 | -0.5 | -0.5 | -5 |
| Padres | -0.6 | -0.7 | 0.9 | 0.3 | 1.4 | -0.5 | -2.0 | -0.2 | 0.0 | 0.5 | -1 |
| Phillies | -1.9 | -0.7 | 0.2 | -0.9 | 0.2 | -0.8 | 0.9 | 1.4 | -1.3 | 0.5 | -2 |
| Pirates | 0.1 | 0.4 | 0.9 | 1.3 | 0.4 | -1.1 | -0.3 | -1.9 | 0.0 | 0.5 | 0 |
| Rangers | 0.7 | -0.5 | -0.9 | -0.7 | 0.1 | 0.0 | 1.9 | 0.8 | -0.2 | -0.5 | 1 |
| Rays | -0.9 | -1.3 | 0.7 | 0.5 | 2.4 | -0.1 | -1.6 | -1.8 | -0.4 | -0.5 | -3 |
| Red Sox | 2.6 | 0.0 | -1.1 | 0.5 | 1.7 | 0.5 | -0.5 | -1.8 | 0.6 | -0.5 | 2 |
| Reds | -0.1 | -0.8 | -0.2 | -1.7 | 1.2 | 0.5 | 0.3 | 0.1 | -1.2 | 0.5 | -1 |
| Rockies | 2.0 | 0.5 | -3.9 | -1.7 | -0.4 | 1.5 | 1.0 | 1.1 | -1.2 | 0.5 | -1 |
| Royals | -0.8 | 0.0 | -0.7 | 0.9 | 1.6 | 0.7 | -1.0 | -0.5 | -1.3 | -0.5 | -2 |
| Tigers | 0.5 | 0.5 | -0.2 | 0.3 | -1.5 | 0.6 | -1.3 | -0.1 | -1.5 | -0.5 | -3 |
| Twins | 0.0 | 0.3 | -0.4 | 0.3 | 0.5 | -0.8 | -1.2 | -0.1 | -0.7 | -0.5 | -3 |
| White Sox | -0.6 | -0.8 | -0.2 | -1.1 | -0.8 | -0.1 | -1.3 | 0.8 | -1.3 | -0.5 | -6 |
| Yankees | -0.7 | -1.3 | -0.2 | -1.3 | 0.1 | -0.3 | -1.0 | -0.6 | 0.2 | -0.5 | -6 |
Besides the overall table, here are the teams ranked based on this overall value. Feel free to copy-and-paste the data into a spreadsheet to create custom ranks.
| Team | Total |
|---|---|
| Giants | 7.4 |
| Cubs | 6.7 |
| Dodgers | 6.6 |
| Nationals | 3.7 |
| Indians | 3.3 |
| Marlins | 3.2 |
| Mariners | 3.2 |
| Red Sox | 2.2 |
| Cardinals | 1.9 |
| Astros | 1.8 |
| Angels | 1.8 |
| Mets | 0.7 |
| Rangers | 0.7 |
| Pirates | 0.2 |
| Braves | -0.3 |
| Rockies | -0.6 |
| Padres | -1.1 |
| Reds | -1.4 |
| Royals | -1.6 |
| Diamondbacks | -2.2 |
| Phillies | -2.4 |
| Twins | -2.7 |
| Rays | -3.0 |
| Tigers | -3.2 |
| Athletics | -3.7 |
| Blue Jays | -3.9 |
| Brewers | -4.2 |
| Orioles | -5.3 |
| Yankees | -5.7 |
| White Sox | -6.0 |
Basically, owners should draft pitchers from the Giants, Cubs, and Dodgers and don’t from pitchers on the Orioles, Yankees, and White Sox when picking from two or more options.
Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.
You kick ass. Thanks!
How would catcher framing factor in?
I should include. I might if I can find some projections.
Only gonna help SF and LAD.
Oh this is awesome.
Is any of this already baked into the projections? Home park, AL vs. NL, etc.?
Into some. Also, it can help with finding single week options.
This is awesome execution of a great idea. I’m gonna look back at this in 5 years and laugh about how I tried to keep all this straight in my head during draft day.
How did COL end up middle of the pack?
OK defense and good away park options.
And a great offense!
Come onnnnnn Giants trade for Quintana!
The Giants do not have the prospect capital to trade for Quintana even if they wanted to. Their top prospect, Arroyo, is ranked 69th overall. Their second best, Beede, is ranked 86th. Chicago reportedly wanted Musgrove, Martes and Tucker from Houston. That’s Musgrove, a young starter who is already in the MLB and having some success, plus the numbers 18 and 63 prospects. This suggests that, to match that Houston package, SF would need to include both its top two prospects, plus an MLB ready starter, plus something else to make up for the difference in prospect quality. SF doesn’t have any young MLB starters to trade, so it would have to include a very valuable asset to make up for the young starter and the lower prospect quality. This, The centerpiece of any Giants package would probably have to be Brandon Crawford or Brandon Belt, which is obviously not happening.
R/G, would that only factor into a prediction for Wins? Or do you think that can factor into when a pitcher will get taken out of a game? That is, the more runs the likelier a pitcher stays in, which is typically good for fantasy.
So are we buying Marlins now? They’re the surprise team in the top tier for me
Great work, but I dont see how this is overly helpful other than stating the obvious. Let me explain (and perhaps Im not fully understanding the info)
RS/g, SOS how much does each weight into generating wins, or pitcher IP
Defense, how many actual runs are saved on IF vs OF defense, how does this translate into actual WHIP, ERA or Wins
Bullpen, does this negatively influence IP, but positively wins? By how much and then how much does that compare and weight the other factors.
It seems like taking the standard dev, but not knowing the magnitude of the effect of each on each category and then weighting it, makes the data almost useless except as a potential directional cue on some factors which may be counter effected by other factors.
That being said, thanks for the info.