Win Values Explained: Part One

So, you’ve probably noticed that the Big New Thing around here is Win Values for position players. David has added them to the player pages, the team pages, and even the leaderboards. Now, instead of sounding like a total nerd by telling your friends that Pujols is awesome because he had an .843 wOBA (not his real number, but not out of the question), you can simply tell them that he was a nine win player last year, worth about $40 million in 2008 salary. Nine wins. Forty Million. Everyone understands these numbers.

That’s the beauty of win values – we can express a player’s contribution to his team in ways that are both meaningful and easy to understand. As much as I love WPA/LI, it’s just never going to be something that the casual fan is going to understand without a good bit of explanation. Win values, though – I can tell my mom that Adrian Beltre is a four win player and she’ll understand in 30 seconds. And, without too much more explanation, I can explain that those four wins are worth about $18 million in salary, and so not only is Beltre worth his salary, but he’s actually something of a bargain.

Win Values are a big open door to acceptance of our particular brand of analysis among non-statheady fans, and even within our little insulated community, they’re still a big step forward over the commonly accepted performance metrics of the last few years. However, rather than just telling you that and having you trust us, we figured it’d be a good idea to explain how the win values are calculated and break down each part of the formula for you to see. So, this week, we’ll be looking at the calculations of each part and walking everyone through the steps to create a win value for a particular position player.

This afternoon, we’ll start with the “Batting” component. Sticking with the Adrian Beltre example, we see that he hit .266/.327/.457 last year. However, while that’s interesting, do you know how valuable that is just by looking at it? Me either. That’s why there’s wOBA, which takes all the results of a player’s plate appearances throughout the year and uses run value weights to sum up a player’s production at the plate in a number that is easily converted to runs above average. That number, wRAA, is found right next to wOBA on each player’s page. It is, essentially, a player’s value that he produces at the plate relative to a league average hitter. You can read more about wOBA in The Book, and we went into detail about it a while ago.

However, you may notice that a player’s Batting value doesn’t match his wRAA value on the player cards. That’s because the wRAA numbers on the site are not park adjusted, but to build a proper win value, you have to include the effects of a player’s home environment. Getting back to Beltre, he plays in a park that depresses run scoring, so the runs that he creates are more valuable than they would be if they came in a park where runs were more plentiful. So, while his raw offensive line may have only been worth 3.9 runs, when we adjust for Safeco Field, his Batting value goes up to 5.9 runs.

That number – the 5.9 in Beltre’s case – represents the amount of runs above or below average that each player created with their bat for a given year. This number is not position adjusted, as I detailed my issues with offensive position adjustments back in November. We’ll add the position adjustments in later, so it gets included in a player’s total value, but I think it’s incorrect to add it to the offensive total.

So, when you’re looking at the Win Values section, that’s Batting – offensive runs above or below average, not position adjusted, but adjusted for the run environment of his home park.

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Dave is the Managing Editor of FanGraphs.

14 Responses to “Win Values Explained: Part One”

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  1. Matt H. says:

    Excuse my ignorance, but are the wins adjusted for playing time? Like for instance Hanley Ramirez played more than Chipper, even though Chipper was slightly more valuable

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    • mymrbig says:

      Matt H, “valuable” is one of the most slippery words in the baseball lexicon and probably should never be used amongst those with a passion for baseball. My understanding is that the wins added and dollar value are adjusted for playing time (but wOBA is not). But saying that “even though Chipper was slightly more valuable” than Hanley gets to the root of your whole question. Even though Chipper was allegedly more “valuable” on a per plate appearance basis, he gets docked for less playing time.

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  2. Eric Seidman says:

    Matt, the wRAA numbers are found by the following formula: ((Individual wOBA – league wOBA)/Scale)*PA.

    So, if you have two players with identical wOBA numbers, but one has 600 PA and the other has 300 PA, the 600 PA player is going to be worth more runs above average.

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  3. thephaithful says:

    Where is the ‘scale’ found? Im pretty much following everything except this 15% line. Also, where I can read more on HR = 1.72 and single = .77 ?

    Very interesting stuff.

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    • Matt H. says:

      google “the book”, or Tom Tango. I believe his blog has all the weights

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    • Colin Wyers says:

      “Scale” is used to fit wOBA to the average OBP of that season. I believe stock wOBA uses a scale of 1.15. (That’s the 15%.)

      As for the weights, I presume you mean these:

      HR 1.70, 3B 1.37, 2B 1.08, 1B 0.77, NIBB 0.62.

      Those are simply linear weights values above the out. If the LWTS value of an out is -.30, then you get:

      HR 1.40, 3B 1.07, 2B 0.78, 1B 0.47, NIBB 0.32

      As for how you figure out those weights… I’ll try and give the thumbnail sketch version here.

      Every base-out state — as in, bases empty, no outs; or runner on second, one out — has an expected run value, or the average number of runs that score between now and the end of the inning. The linear weights value of an event is the average change in that run expectancy after that event.

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  4. Rob says:

    How are the park adjustments done? Is this information available on the fangraphs website, too?

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  5. IvanGrushenko says:

    Where can I find park adjusted Batting Runs for players before 2002? Why bother publishing the non-park adjusted Batting Runs at all?

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  6. Paqs says:

    “As much as I love WPA/LI, it’s just never going to be something that the casual fan is going to understand without a good bit of explanation. Win values, though – I can tell my mom that Adrian Beltre is a four win player and she’ll understand in 30 seconds.”

    Actually, I tried to explain this to your mom, and she still didn’t get. Ba dum tish!

    I’ll get my coat.

    (Btw I’m not a troll and I love your work, keep it up)

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  7. Kevin M. James says:

    Okay, I’ve been trying to reverse-engineer these nifty statistics so I can use them for a fictional simulated baseball universe. (Yes, I’m a sim-game geek.) I keep hitting walls though…I guess I don’t quite understand this stuff well enough yet.

    I think I’ve managed to fake it regarding adjustments for run environment. I hold no hope for being able to do the full wOBA year-by-year calculations as described, as the Baseball Databank obviously doesn’t apply, and even if it did the SQL is Greek to me. But I can gin up a runs-per-out number for a season in my fictional league, and compare that and the home run total to past years to find a decent fit in the Iwts_woba spreadsheet, and I can live with that for now.

    I’m really stuck with the park adjustments though. I’m trying to get from wRAA to the Batting value, but just can’t figure out the correct equation to put into Excel–or if I’ve found the right park adjustment data at all. I’d hoped there was a simple factor I could multiply the wRC or wRAA by…but it’s obviously more complicated than that. I’m stumped, and have no idea how to get to the Batting value figures found here.

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  8. JAYjay says:

    So….. essentially the Batting Value is wRC+, with a different scale?

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  9. Jordy Stephens says:

    I am unable to correctly calculate WAR using the formula that’s presented in this guide. I will use Jose Reyes in 2012 as the example:

    11.5 + (-2.8) + 0.2 + 7.3 + 23.9 = 40.1 40.1/10 = 4.01 WAR
    wRAA + UZR + UBR + POS + REPL

    Jose Reyes is listed as having 4.5 WAR in 2012. Could you please let me know where I’m going wrong?

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