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By Tangotiger 07:14 PM

?This is how I did it 30+ years ago. The last time I played was 30+ years ago. I had no interest to do this blog post other than someone asked me. I have an hour, so here we are.

If someone wants to argue that my method is lacking, feel free to point out where and why. My only argument is: I know what I’m doing. At least, I think I do, or I’ve convinced myself of it. If that’s not good enough for you, that’s fine! Feel free to stop reading right now. If my argument is good enough for you, then jump over the line.

The key is simple: standard deviation. That’s what you want to focus on, that’s what you care about. That’s how this whole thing works. If someone out there has a system that does NOT use the words “standard deviation”, then that system is doing something totally different than what I am doing.

In this blog post I will assume a 15-team league. And I’ll focus on pitchers only. Each team drafts 9 pitchers. There’s no team IP minimums.

There’s going to be circular logic, as I create a point system, select the top 135 pitchers, recalculate the points, and re-select the top 135. I keep doing that until I get stability.

I am using Seasons 2016-2019 for this. Based on these 4 seasons of the top 135 pitchers, one standard deviation for the Wins (*) category is just under 5. For Saves (**) category, one SD is just under 12. This means that one Win has over 2X the impact of one Save. So, if we were to give a Win 10 points, we’d give a Save 4 points. For Strikeouts (***), one SD is 57. That means each K gets 0.9 points. Or, make it easy, and say 1 point per strikeout.

(*) Ugh.

(**) Ditto.

(***) Finally!

For ERA and WHIP, things are a bit more complicated. A 4.50 ERA pitcher is going to hurt you far more if it’s from a 200 IP pitcher than if it’s from a 60 IP pitcher. Similarly, a 3.00 ERA 200 IP pitcher is going to help far more than a 3.00 ERA 60 IP pitcher. The MOST IMPORTANT THING here is to figure out what the “average” ERA is going to be in your league. Now, if I take the top 135 pitchers each season, I’m going to end up with an ERA just barely above 3.00. But, that’s based on the idea that I know, after the fact, what everyone’s ERA is going to be. I’ve tried to find out, unsuccessfully, what a standard 15 team league ERA is. Not knowing nothing about nothing, I’m just going to use 4.00 ERA as my flat number. (I adjusted it slightly for each season, since the run environment changes each season. But I’ll go with 4.00 for this blog post.)

So, what we want to do is figure out the “Runs above average”. The calculation itself is simple: IP * 4/9 - ER. The “4” is the baseline average, which as I said, I guessed. When you do that, that will show you how much your ERA will help, or hurt, in this particular league. In my calculations, I have pitchers going from +52 runs above average down to -44. For the OVERALL top 135 pitchers, their range is +52 to -14, for one standard deviation of 9.5. Since we give out 10 points for one Win, we give out 5 points for one Run Above Average.

Now remember, an RAA is IP*4/9 - ER. So, if we multiply all that by 5, we end up with each IP worth just over two points, and each ER as minus 5.

Note: if we REALLY want to do this right, we’d look at ACTUAL leagues, and see what ACTUALLY happened. We’ll probably be close, in terms of the point system. To the extent I am not correct on the point system shown above, I’d be able to get that right if someone sent me the results of 100 leagues.

Anyway, let’s now look at WHIP. I’m using 1.27. Again, if I had a better number, I’d use it. But I need to use something. Similar to the ERA calculation: runners above average = IP * 1.27 - (H+BB). One standard deviation is almost 18 runners. Since 10 points is one win, then one runner is 2.7 points. I’ll round that to 3. Since we have IP * 1.27 - (H+BB), then multiplying all that by 3 gives us: almost 4 points for an inning and minus 3 for each hit and walk.

Now we can tally all that up.

10 Win

4 Save

1 Strikeout

6 IP

-5 ER

-3 H

-3 BB

So, you apply all that to each pitcher’s forecast. Take the top 135. Subtract from each pitcher’s total the value of the 136th pitcher. And voila, you have a point value for each pitcher. Let’s call these marginal points. I get about 20,000 marginal points per season. The top pitchers have about 700 points.

To convert that to dollars requires you figure out how many dollars pitchers should get. Let’s assume, because I want this blog post to end right now, that it’ll be one-third. So, of the 260$ x 15 teams, you allocate 87$ per team. I’ll round that to 89$ per team. Every pitcher is paid at least 1$. That leaves us with 80 marginal dollars per team. Or for a 15 team league, that’s 1200 marginal dollars.

To convert the points to dollars: 1200 / 20000. In other words, each point is worth 6 cents. The top pitcher with 700 marginal points gets 42 marginal dollars. Plus 1. So, 43$.

That’s it, that’s all I’ve got in me. Hopefully, the aspiring saberists out there will take what I did, refine it, and help out the folks out there.