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Basic Sabermetrics: What Will You See on Fish Stripes?

Note: This is a very basic introduction to the numbers we will use on this site. Every week, I will go into a more in-depth discussion about how these numbers are derived and what they really mean. Right now, we all just want to talk about the Marlins, so I will not yet spend too much time on this. At the end of the piece, there are three takeaways that I'd like for everyone to get. If you Fish Stripers can get those three takeaways, you won't have to worry about the rest of this for now.

Later today, I am going to begin discussing in detail the various aspects of yesterday's plan for offseason success. In the process, I will be throwing in some numbers that will regularly be used on the web site. But do not fear! These are not numbers that should scare anyone. Like many aspects of sabermetrics, these numbers have a firm basis on logic behind them and are useful for telling us something about players that we perhaps did not know. In the end, numbers and observations are the tools we use to enlighten us about the game of baseball. With both our eyes and the numbers on our side, we can learn a lot about the game.

What will follow is a brief introduction to some of the numbers that we will be using here on the site. There will also be various links to simple explanations about these statistics, so that if you want a better grasp on what is going on, you can find out.

Before we go into that, I would like to point out a part of the links section that was not previously there.

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Click to embiggen

This set of links will provide tremendous assistance towards understanding some of the statistics that are used to talk about the Marlins here. Resources like Alex Remington's great Everything You Wanted To Know series on Big League Stew and FanGraphs' Sabermetrics Library are excellent starts on the way to learning more about the numbers.

However, if you just want to hear what these silly acronyms and numbers mean, let me summarize them for you.

Some Acronyms You Might Want to Know

OPS: On-Base Plus Slugging. We know that on-base percentage and slugging percentage are good. Mashing them together allows us to have a measure of both numbers at the same time for comparison purposes.

OPS+: All "plus" metrics are designed to be adjusted two things: league and park. There are park adjustments made to the numbers, and those numbers are compared to the league average. In OPS+, a number greater than 100 implies a percentage better than average, and vice versa for less than 100.

wOBA: Weighted On-Base Average. Here's the problem with OPS. For one, it doesn't take a math genius to figure out that adding two fractions with different denominators does not yield a "real" number. Secondly, because OBP and SLG are on different scales, OPS does not properly weigh those numbers; it overvalues SLG and undervalues OBP. How then can we put together the total value of a hitter? How can we resolve that issue?

Enter wOBA!

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wOBA is derived from a concept called linear weights, which is a measure of how many runs on average an event was worth. We all understand that not all hits are worth the same (like batting average thinks), nor are walks worth the same as home runs (like OBP thinks), nor are home runs four times as valuable as singles (like SLG thinks). wOBA uses the run values of all events such as walks, singles, home runs, and steals, and weighs them properly. For example, a home run is not really worth four times a single, but rather more like three times. A walk is worth about 2/3 of a single. All of the numbers are properly weighed and put to an OBP scale.

Here's an example of the wOBA leaderboards for this year:

Player wOBA OPS
Jose Bautista .441 1.056
Miguel Cabrera .436 1.033
Ryan Braun .433 .994
Matt Kemp .419 .986
Prince Fielder .408 .981
Adrian Gonzalez .406 .957
David Ortiz .405 .953
Joey Votto .403 .947
Lance Berkman .402 .959
Jacoby Ellsbury .402 .928

There's also a wOBA calculator if you want to tinker around and find out how your favorite hitters did.

Runs Above Average: So as you can see from above, there are not a whole lot of surprises, as wOBA and OPS generally agree on the order. So why use wOBA? Well, if you wanted to know how much better a player was compared to someone else, wOBA would let you do that. We can also compare how well a player hit versus the league average and find out how many runs a player produced above average. Remember, wOBA is on an OBP scale, so the average is around .320 to .330.

If you want to find out runs above average from wOBA, you can subtract the average wOBA from the player's wOBA, divide that by 1.2 (the factor that puts it on the OBP scale), and multiply by the number of plate appearances.

UZR / TotalZone / FRAA: These are acronyms for various fielding metrics. These fielding metrics attempt to tell us how many runs above or below average a position player produced on the field compared to his position peers. For example, in 2007 Hanley Ramirez was rated as somewhere around 20 runs below average compared to other shortstops (remember that terrible year?). On the other hand, Omar Infante was good enough on the field this season that the various metrics had him between 8 and 15 runs above average. More on these in a later piece.

FIP: Fielding Independent Pitching. There has been a lot of research that says that, at the major league level, pitchers do not have nearly the same amount of control over balls in play that they do over fielding-independent outcomes like strikeouts, walks, and home runs. FIP is an ERA estimator that uses strikeouts, walks, and homers to determine an estimated ERA. In the equation, it assumes a league average performance on balls in play for a pitcher. The other three numbers are based on linear weights, so they accurately weigh each event against each other. Here is a FIP calculator you can use.

BABIP: Batting Average on Balls In Play. It is exactly what it sounds like: either a hitter's batting average on balls that stay on the field (not including strikeouts or home runs) or a pitcher's batting average allowed on balls in play. The difference is that hitters tend to be able to control BABIP better than pitchers do. Hitters face a lot of different defensive teams every year, so the effect of the defense is not as great on them (it tends to average out). A pitcher pitches in front of (more or less) the same defense all year, so his BABIP is very dependent on his defense's performance. So when a pitcher has a high or low BABIP compared to average (around .300), we tend to think that will go back towards the average significantly in the future.

WAR: Wins Above Replacement. The simplest way to explain this is with an example. Assume your team is a set of Willie Bloomquists, including the pitching equivalents to Willie Bloomquist. How many wins do you think a team of Bloomquists would win? The estimate is somewhere around 50 wins on average. Now, start filling that team up with quality major leaguers. Each of those major leaguers should be able to produce more runs and wins than Willie Bloomquist. Since Willie is the quintessential replacement level player, the amount of wins a player produces over Willie is his Wins Above Replacement.

(Note: If you don't think Willie is a perfect example for replacement level, check it out: in 10 seasons and 2437 PA, he has produced just 1.3 Wins Above Replacement.)

This is calculated by adding all those runs above average for hitters at the plate and on the field, adjusting for position, and adding in the difference between league average and replacement level. For pitchers, it's a little more hazy, so we won't get into it here.

That Was Too Much, What Do I Do?

The important thing is to not worry! It's not important that you understand everything right now. Here's a good takeaway:

1. wOBA is good for comparing hitters' total offensive contributions, including on-base, slugging, and steals.
2. WAR is a measure of wins, and it shows the relative value of players.
3. FIP can be used to see what a pitcher's ERA would be if he performed at the league average on balls in play.

If you can get that for now, I will definitely go through much of this at a later date. Every Thursday, I plan on having a little "Saber 101" article on basic concepts that are easy to understand. Right now, it may seem like a lot, but once you get a foundation, it will be much easier to grasp. If you are interested, please read the links mentioned above and ask around in sites like Beyond the Box Score.

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Love it!

You have me sold on the direction of the blog. Absolutely love it.

I will say that I think that this will have the opposite effect on a lot of fish stripers from before.

by boozer on Nov 3, 2011 12:35 PM EDT reply actions  

Thanks

I hope that this doesn’t scare people away. It’s only new vocabulary, we’ll still be using it to admire Mike Stanton!

by Michael Jong on Nov 3, 2011 12:50 PM EDT up reply actions  

Awesome.

This is an objective way of measuring talent across the board.

Looking forward to learning more about sabermetrics and using more often in my analysis.

Founder of the "Rob Ryan for Head Coach" Bandwagon.
Assistant Janitor of the Luckfleet

by Zag on Nov 3, 2011 12:37 PM EDT reply actions  

Would FIP basically be an inverse of pitcher BABIP?

Seems like they compare the exact opposite of each other.

Thank you for doing the stats this way. I try and read a good bit into Football Outsiders and Football Study Hall but I’ve gotten bogged down with sabermetrics because there’s so much to learn. Breaking it off in chunks like this is much easier. Hopefully I’ll be able to keep up.

by evenflow58 on Nov 3, 2011 5:49 PM EDT reply actions  

FIP is scaled to ERA

So it basically measures run impact of strikeouts, walks, and home runs.

BABIP, on the other hand, is just batting average on those balls in play, without measuring any additional value of those hits.

No problem, I think it’s best learned in chunks. It took me a while to really catch on to what is a continuously growing field.

by Michael Jong on Nov 3, 2011 5:58 PM EDT up reply actions  

i feel like i'm going to need to bring a calculator to visit this site anymore

baseball already uses numbers more than any other sport, why cloud it up with more?

by FishNFinz on Nov 3, 2011 7:41 PM EDT reply actions  

No calculator necessary

We do the work for you!

And for me, the numbers don’t cloud anything up. It’s all about using the right numbers. For a long time, all we had was AVG/HR/RBI. There’s so much more to hitters than these three numbers, so much that tells us what they do at the plate and on the field. That’s all these numbers are trying to show. And that’s what really helped me figure out what was happening; instead of clouding it up, I found baseball to be more understandable. It’s why I share this information with people on the blog!

by Michael Jong on Nov 3, 2011 7:53 PM EDT up reply actions  

Great piece on Sabermetrics

Sounds geared toward those that have no idea (like me). I’m sure I’ll get it eventually. So just to check my comprehension, say a pitcher has a decent FIP, but a high BABIP. Is that indicative of a crappy defense behind him?

Miami Marlins? Don't know if I'm ready. Seems like saying goodbye to an old friend.

by marlinsfan315 on Nov 4, 2011 1:32 PM EDT reply actions  

Indeed, that could be part of it

Part of it could also be that he was unlucky in the types of balls he let in play (too many up the middle instead of a few feet to the left or right, for example). Generally we can expect most pitchers who show a one-year high BABIP to go back near the average after that.

by Michael Jong on Nov 4, 2011 2:29 PM EDT up reply actions  

That makes sense...

But if ALL the pitchers experience the same phenomenon, then it would seem to be a defensive issue.

Miami Marlins? Don't know if I'm ready. Seems like saying goodbye to an old friend.

by marlinsfan315 on Nov 4, 2011 2:43 PM EDT up reply actions  

Again,part of it is definitely dependent on defense

and certainly part of it is definitely dependent on pitcher skill. And part of it is the luck of the draw. But what has been found is that there is so little spread and so much regression in the case of BABIP year-to-year that we would expect a pitcher to return to the mean significantly.

Think of it as a spread: pitchers are going to end up in a spread of values, but that spread is very small and, when examined in a subsequent time period, any group of pitchers (low or high) from one time period usually revert to the average in the next time period. This is a function of not only a small spread in skill but a significant effect by defense.

by Michael Jong on Nov 4, 2011 3:23 PM EDT up reply actions  

I think

He’s asking for a team as a whole. If a team has a .330 BABIP one year, and one starting pitcher has a .330 BABIP that year against a .300 career rate, it’s possible that the .330 isn’t necessarily the result of ‘bad luck,’ as much as it is on bad defense.

Obviously, it’s important to remember that, from the perspective of analyzing an individual pitcher’s skill set, this is still ‘bad luck.’

by CTowers on Nov 4, 2011 3:43 PM EDT up reply actions  

Exactly

I’m not trying to say that luck doesn’t play into BABIP, but it would seem to me that if it’s more than just one pitcher, it would seem to be a symptom of something else. Although I guess it could be park factors. Like I’ve said, still new to the world of Sabermetrics.

Miami Marlins? Don't know if I'm ready. Seems like saying goodbye to an old friend.

by marlinsfan315 on Nov 4, 2011 6:42 PM EDT via mobile up reply actions  

Yeah

Sometimes it’s luck, sometimes it’s bad defense, and some guys have proven to totally confound advanced metrics entirely and consistently over or under perform expectations on all sorts of things.

Most of the time it’s never just one thing that you can point to. Sometimes, it certainly is. But sometimes, guys just give up a really hard hit ball that will make their BABIP inflate.

by CTowers on Nov 4, 2011 7:22 PM EDT up reply actions  

I actually had a pretty spirited discussion one time...

About park factors and strike outs. Eventually it showed me the error of my ways and showed me just how much I had to learn. Lol.

Miami Marlins? Don't know if I'm ready. Seems like saying goodbye to an old friend.

by marlinsfan315 on Nov 4, 2011 7:00 PM EDT via mobile up reply actions  

Hey

I just think it’s great that you’re trying to learn. Some people see something they don’t know or don’t immediately understand, and they just totally shut themselves out.

by CTowers on Nov 4, 2011 7:23 PM EDT up reply actions  

Absolutely

Anything that has a base in logic is worth learning, I think. I’m thinking of actually suggesting incorporating like a weekly quiz into some form of ichthyomancy. Maybe a separate entity or something, although I don’t know what that would do to the logistics of running this site. Just a thought, I guess.

Miami Marlins? Don't know if I'm ready. Seems like saying goodbye to an old friend.

by marlinsfan315 on Nov 4, 2011 7:55 PM EDT via mobile up reply actions  

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