2008 Fan Save Values

One of the main reasons I got involved with sabermetrics was to show fans intimidated by statistical analysis that not all effective evaluative methods consist of complex mathematical formulas. My favorite statistics are ones like FIP, wOBA, and EqA: better indicators of skill and performance but scaled to look similar to the more commonly accepted barometers. In using similar scales more of a chance exists for widespread acceptance.

Through surveys I found that a major reason fans shy away from better evaluative methods is that they are unfamiliar with the baselines. They don’t necessarily know what a good VORP is, or a good WPA; however, they definitely know what constitutes a good or bad ERA or batting average.

One of these stats not mentioned too much is called “Fan Save Value,” and it was created by analyst Ari Kaplan while working for the Orioles in 1990. Essentially, as described in the book Baseball Hacks by Joseph Adler, FSV measures the difficulty level of each save by taking into account the lead with which the closer enters as well as the number of outs he must record to secure a win for his team. When all of the results are added together we are left with a number similar to the saves total but more indicative of how hard a closer had to work.

The formula for FSV is (X/Y)/2, where X=the amount of outs to record and Y=the lead of his team. For instance, recording a one-inning save with a two-run lead would result in an FSV of 0.75; 3 outs divided by 2 runs ahead, then divided by 2. Using this statistic I decided to look at the current saves leaders and determine how hard each has had to work:

Francisco Rodriguez, LAA: 12 saves, 11.3 FSV
George Sherrill, Bal: 11 saves, 7.6 FSV
Joe Nathan, Min: 10 saves, 10.8 FSV
Jonathan Papelbon, Bos: 8 saves, 10.3 FSV
Mariano Rivera, NYY: 8 saves, 9.8 FSV
Huston Street, Oak: 8 saves, 8.3 FSV

Brian Wilson, SF: 10 saves, 10.5 FSV
Eric Gagne, Mil: 9 saves, 8.0 FSV
Jason Isringhausen, StL: 9 saves, 6.5 FSV
Brandon Lyon, Ari: 9 saves, 9.5 FSV
Brad Lidge, Phi: 7 saves, 7.5 FSV
Jon Rauch, Was: 7 saves, 6.1 FSV

The saves leader in each league remains on top when using FSV but the rest of the leaderboard shifts. The biggest dropoffs come from Isringhausen and Sherrill: Both of these pitchers have entered save situations in which their teams led by large margins and/or recorded a couple of 0.2 IP saves.

Papelbon, on the other hand, has pitched more than one inning in a few of his saves. Since the overall result looks similar to the saves total, and saves are commonly used as an end-all when evaluating closers, the FSV is an easy to use and better evaluative tool because it adds context to a normally context-free statistic.

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Eric is an accountant and statistical analyst from Philadelphia. He also covers the Phillies at Phillies Nation and can be found here on Twitter.

Guest
Eli
8 years 3 months ago

Thank you for this post – beyond being interesting, it addresses an issue that doesn’t get brought up nearly often enough.

All these new stats are great, but you’re right, without baseline levels of comparison it’s kinda hard to do anything with them or use them to convert new fans to saber.

Thanks again for bringing this up.

P.S. How does the 0.2 IP save figure in to the math? You use 0.666 when doing the conversion though, right? I’m sure you get where I’m going with this.

Guest
Eli
8 years 3 months ago

Don’t know why I overlooked that… Thanks for redirecting me ;)

Will your book be available on Amazon?

Guest
8 years 3 months ago

Are you actually from Philly? I’m in the suburbs just outside, in Delaware County.

Guest
8 years 3 months ago

I wonder if that formula could be adjusted to get an idea of the value of all relief appearances. Instead of “outs to record to finish the game”, there would be a value for “outs produced”. The value for run differential stays, maybe with adjustment if the reliever gives something up. I think it’d be interesting to see what kind of mid-game “saves” a Scot Shields or Tom Gordon type acquires.

Guest
8 years 3 months ago

I know this simply because I was perusing his game logs not too long ago, but J.C. Romero’s performance this year is misleading. He’s allowed quite a few inherited runners to score already, and he’d blown two saves all the while keeping his scoreless innings streak intact (until Aaron Rowand broke it Friday night).

Guest
8 years 3 months ago

Can you try comparing to WPA, LI, and WPA/LI ?

Guest
8 years 3 months ago

Well, in terms of definitions, WPA, LI, and WPA/LI are a constantly updating stat whereas FSV is only dependant on the situation in which the Closer enters.

If a Closer enters into the top of the ninth, with a 1-run lead, he would get an FSV of 1.50 for that game because it’s just the three outs and one-run lead that matters.

If we look at that with LI, he would be entering into an LI of +2.9. Looking at WPA, getting a 1-2-3 save in the ninth, with a 1-run lead, would result in a WPA of roughly 1.34.

So, using the FSV it would be 1.50, using the SV it would be 1.23, and using WPA it would be 1.34, though WPA takes everything that occurs in the inning into account. The Save Value stats look solely at the entering situation.

In terms of contribution to a team’s wins, WPA and WPA/LI are going to be more indicative, but the SV and FSV make the Saves statistic useful by gauging the difficulty level in recording said saves while still representing it with a number close in appearance to the Saves total.

Guest
8 years 3 months ago

My point is that the function itself may not be valid. The gmLI tells you exactly the impact of his appearance. Does “outs left divided by runs lead” do that? That’s what I’m asking. How well does that function correlate to gmLI. And, it will clearly fail somewhere (like coming in with men on base), so perhaps it can be tweaked somewhat.

Just because you get a number that seems reasonable doesn’t mean it is reasonable. Look at BP’s LEV as an example of a good idea gone bad.

Guest
Jacob
8 years 3 months ago

Eric, if you look at these players WPA only in the games where they got saves (same subset you are using), you should see that WPA roughly correlates with FSV. FSV shows a very rough approximation for WPA by using outs, runs, and the number 2 to come up with a leverage index. Let’s just look at 3 out saves, you could expand this table to show all save situations if you wanted…

from tangotiger’s page
http://www.insidethebook.com/li.shtml

just bottom of the 9th, 3 outs to go, bases empty.
up by 1, 3.6 LI, 1.5 FSV
up by 2, 2.0 LI, 0.8 FSV
up by 3, 1.0 LI, 0.5 FSV

FSV is a nice idea in that it tries to take some of the save context into consideration and put the results on the saves scale. What might be a fun project is to use WPA (which already has the real context FSV tries to approximate, and more, like base state, home vs road) and put that on a saves scale to make it more accessible.