Fili's SABR link of the day (or couple days, maybe a week) (ball, game)

[filihok]

Dammit...just too many good articles to only post one

Walk Like a Sabermetrician: Runs Anything

Which Phillies Player was more valuable in 2009
1B Ryan Howard: .279-BA 105-R 45-HR 141-RBI
or
2B Chase Utley: .282-BA 112-R 31-HR 93-RBI

Let’s look at an example that I mentioned in passing earlier through the Runs Anything framework: Ryan Howard and Chase Utley in 2009. Howard finished third in the MVP voting, while Utley languished back in eighth place. (Context-neutral) sabermetric measures are unanimous in evaluating Utley’s performance as being more valuable to the Phillies than Howard, but Howard drove in 141 runs to tie for the NL lead while Utley drove in 93. I obviously can’t identify exactly what the thought process was for the NL MVP voters, but it seems like a safe bet that the 48 RBI gap between the two was a key factor in their placement.

Utley scored more runs than Howard, although the gap is only seven (112-105). So by any kind of “runs produced” metric, regardless of whether you take out homers or not, Howard ranks well ahead of Utley.

However, what that analysis does not consider is that Howard made 34 more outs than Utley (444-410). The NL averages were .176 runs and .168 RBI per out, which means that Howard’s R+, RBI+, ANY is 134, 189, 162 and Utley came in at 155, 135, 145.

This is a useful illustration, as we still get the “wrong” result even when using ANY. ANY does not adjust for the way batting order position affects R and RBI production, and the other pitfalls of using actual R and RBI counts are still in play. Still, the gap between 162-145 is a lot less than a cursory look at R and RBI totals for Howard and Utley would indicate. And of course the analysis ignores the difference in fielding value between the two. Even if ANY captures the true offensive value of the two players, the slick-fielding second baseman is going to come out on top when defense is taken into account.

Utley typically batted 3rd, and Howard 4th. So the three hitters hitting infront of Howard would have been the lead-off man, the #2 hitter and Utley. The 3 hitters infront of Utley would have been the same lead-off man, the same #2 hitter and the pitcher. Utley's .397 OBA vs the pitchers' sub .200 OBA is...well...a lot more base runners for Howard to drive in.

Howard and Utley put up similar offensive numbers but the value of Utley's ability to play Gold Glove caliber second base tends to be vastly underrated.

[filihok]

SocratED - Baseball Analysis 101 Course

Do you love baseball, yet get scared and/or confused whenever people start throwing around terms like OPS, VORP, FIP, UZR, or wOBA? These terms can seem overwhelming at first, but when broken down piece-by-piece, even the casual, everyday baseball fan can understand what they mean and learn how to apply them properly. These statistics are merely tools that will help you understand baseball to a greater depth and allow you to analyze baseball games and players more effectively.

A pretty cool site.

It links to a bunch of SABRmetric articles in different categories and goes through them in an orderly way

1) Why Traditional Stats are Insufficient
2) Sabermetric Principles
3) Offensive Stats
4) Pitching Stats
5) Defensive Stats
6) Other Stats

This is by far the best introduction to Sabermetrics I've seen.

You have to register an email address to go through the 'course' but that's good because there is a lot of information and it allows you to read an article or two then come back and pick up where you left off.

This is good, good, stuff. I wish it had had it a couple of years ago when I first stumbled across these advanced statistics.

[filihok]

FanGraphs Audio: Prospect Mavens on The Next Step | FanGraphs Baseball

That's a link to a fangraph's podcast. I'd say to give it a listen because they talk about some interesting things to consider when valuing players.

For example the Yankees' Jesus Montero how much more valuable he'll be if he's able to play catcher instead of DH or firstbase.

Another interesting thing is how Boom vs Bust potential of prospects should be factored into their value.

[filihok]

It’s okay to be mystified by linear weights

At our best, we're open-minded folks who take a reason- and logic-based approach to the game we love. At our worst, we're an avant garde gang of know-it-all cyber-bullies, ready and eager to viciously pounce on any Luddite who still worships at the altar of the run batted in. And I think we're at our worst more than we'd like to acknowledge.

Our arrogance comes from the strength of our position; we’re right about baseball and we know it. The problem is that things have become almost cultish; our alphabet-soup language poses a formidable barrier to entering the club. And that’s where these primers come in. If we can walk people through the silliness of pitcher wins and ERA, they’ll greet FIP with open arms. That’s the plan.

Fair Points

Accepting the principles above will make any baseball fan intuitively aware of the nuanced approach sabermetricians take to the game, regardless of an understanding of our language. Very recently, Baseball Prospectus’ Will Carroll urged:

We need a gateway drug. We need an educational initiative. We need a PR campaign. We need to evangelize. We need to market. We need to explain, over and over. We need to find ways to engage and educate each and every baseball consumer who’s willing to listen and wants to learn. We need to fight the anti-logic bias this country has and we need to do it soon.

*****

Wins

1. The only stat that matters. The only way to pick a Cy Young winner. The thing Billy Beane can't get in the playoffs, no matter how many fancy computers he hires to play baseball for him.

2. A simply awful pitching statistic that should be swallowed up by the earth itself, personified, given ears, and forced to listen to a tape loop of Bermanisms for all of eternity. The reason being—and again, you know this, intuitively, even if you have never quite expressed it to yourself —if Carl Pavano gives up 19 runs in five innings but the Yankees score 20 runs, and they hold on to win, and Pavano gets the win, is Pavano a good pitcher? No he is not. […] If Francisco Liriano throws nine innings of no-hit ball, but gives up a run on four consecutive errors by Terry Tiffey and gets a loss, is Francisco Liriano a bad pitcher? No he is not. Wins stink to high heaven as a way to value pitchers because they are in very large part dependent on the actions of the other guys on the team.

[Milwaukee City]

Originally Posted by filihok

For some reason there tends to be conflict between old school stat people and SABR stat people. I don't know why. Both groups enjoy baseball, enjoy the history of baseball, enjoy arguing about who is the better baseball player

This is like Liberal v Conservatives. I am a little of both in terms of a SABR guy and a traditionalist. People wonder why they call baseball fans "numbers geeks" or "sports nerds" I love it! what other sport is so complex like baseball.

[filihok]

https://chrome.google.com/extensions...mlolomilmndoaa

Not technically a SABR link, but pretty damn cool (for Google Chrome users)

The coolest search tool ever created specifically for baseball geeks. Player Search lets you query any one of the top baseball stats sites, or several at once. Incredibly useful if you're doing research, a fantasy draft, or arguing with your friends about which guy is better.

[filihok]

Inverted records

Inverted records
by Geoff Young
March 17, 2010

On page 186 of The Bill James Baseball Abstract 1987, he introduced something called "Inverted Records," which attempted to represent a hitter's output as a pitching line. Why? Well, why not?

James conducted his exercise on the 1986 Cleveland Indians and extended it to include several other prominent players of the day. His method was simple:
Start with a player's hits, walks, and strikeouts.
For runs, use runs created
For earned runs, multiply runs by .9.

Let's walk through a quick example. We'll use one of my favorite players, Adrian Gonzalez, and translate his 2009 hitting stats into a pitching line.

First we take the necessary inputs:
Outs RC H BB SO
428 124 153 119 109
And turn it into this:
IP H R ER BB SO ERA SO/9
142.2 153 124 112 119 109 7.07 6.88

We're having fun, right? But it's impossible have too much fun, so let's go a little further. Let's see if we can find a pitcher that produced this actual line, or something close to it. A quick spin of Baseball-Reference's Play Index tool spits out the following:
Player Year IP H R ER BB SO ERA SO/9
Adrian Gonzalez 2009 142.2 153 124 112 119 109 7.07 6.88
Jason Bere 1995 137.2 151 120 110 106 110 7.19 7.19

Kinda spooky, huh? You could, if you were so inclined, say something like, "Adrian Gonzalez hit pitchers in 2009 like they were all Jason Bere in 1995" and be pretty well on the mark. Useful? I dunno, maybe. Fun? Most definitely.

[filihok]

This one is a little heavy, I apologize.

Statistically Speaking | MVN - Most Valuable Network » Blog Archive » 525,600 minutes: How do you measure a player in a year?

525,600 minutes: How do you measure a player in a year?
By Pizza Cutter | November 14th, 2007

What does a year really tell you about a player? Seriously. If I gave you the seasonal stats for any player last year (or the year before), how much could you really tell me about him? If I told you he hit .300 last year, are you confident that deep down, he’s really a .300 hitter? How do you measure a year in the life?

What we’re talking about here is a concept known in social science research as measure reliability. It’s the idea that if I took the same measure over and over again, I’d get (roughly) the same answer each time. This shouldn’t be confused with measure validity, which is whether or not the measure I’m using is actually measuring what I think it does.

In social science, we look for a magic number, which is .70. For example, one way of estimating measure stablity and reliablity is to look at things from one time point to another, in the case of baseball, from one season to another.

MOD CUT

A few very interesting stats didn’t stablize, even after 650 PA. Those stats, with their split-half correlation at 650 PA in parentheses.

Batting Average (.586)
BABIP (.586) [sic]
2B + 3B rate (.401)
WPA (.403)
Context neutral WPA (.590)
Even after 650 PA, batting average isn’t an ideal descriptor of a player’s true talent level, at least in so much as his ability to put up a repeat performance of that same AVG. Why do we make such a big deal out of batting titles?

I'd just like to point out that the reason batting average and BABIP don't stabilize is because they aren't in the batters control. The rate at which batters get hits is highly dependent on the defense. This is why using batting average isn't a good way to judge a player's ability.

[filihok]

How to Pitch Miguel Cabrera - Royals Review
by Jeff Zimmerman (TucsonRoyal) on Mar 29, 2010 12:17 PM EDT

The following is a look using heat maps at how to pitch Detroit's Miguel Cabrera (RHH). I am going to go through an overview of his hitting and then looks at his hitting pattern depending on the count

The scale is the number of called strikes over the total of called strikes and balls. The values is a decimal form where 0.5 is 50%. All images are from the catcher/umpire's perspective, the box is the rule book strike zone and the circle is added for reference:

The following image shows the average run value for each pitch in that location. The values are taken from this article by Joe Sheehan at BaseballAnalysts.com are used. Basically each ball and strike or play result is given a run value. Positives value are good, negative values are bad



Miguel has few areas where he can cause problems, low and inside, in the middle and higher and away. If you want to throw him a strike and general have a positive results, throw is low and away or pitches up and in.

These are Miguels overall patterns. Next is a look at how he performs at each count (some of the heat maps may have to go to a less detailed image as the sample of data decreases)

An interesting look at how pitch F/X data can be used as a scouting tool

[filihok]

This article fits in too well with the one I posted previously

The effect of pitch sequence on batting eye and selectivity
by Craig Glaser
March 29, 2010

Pitch sequences have always been extremely interesting to me. Throwing pitches in an intelligent sequence is one tool which a pitcher has in order to gain a significant advantage over the batter. When I first started writing about batting eye this was one of the topics I thought would be interesting to look into. In fact one of the first comments I got was from Russell 'Pizza Cutter' Carleton asking when I was going to write about pitch sequences. I think that batting eye and selectivity are new tools which we can use to see what effect pitch sequence has on the batter's ability to perceive the second pitch and their bias on whether to swing or not.



Here we see the complete opposite of the previous three types of pitches, the fastball actually is most difficult to perceive when it follows another fastball. Once again, change-up to fastball is not a very good combination for fooling batters. There doesn't seem to be much difference in selectivity on fastballs based when it comes to pitch sequence. Slider-Fastball seems to be the combination that enables batters to see the fastball best.

MOD CUT.