Here are the four rookie position players above 3.0 WAR in the 2012 season:
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Jeff Zimmerman and I have done lots of work on player aging curves in the past 12 to 18 months. Jeff started things off with a series of hitter aging curves, which focused mostly on standard outcomes and WAR components. Jeff and I then joined forces this year for a series focused on pitcher aging.

This time around, I wanted to know how a hitter’s plate discipline changes over his career. We already know plate discipline statistics are easily the most stable, year over year. That said, I wondered whether I’d see meaningful patterns as players age. Often times, scouts and commentators mention how a hitter’s approach changes over time: less disciplined, less contact as a young player; better bat control and better strike-zone awareness as a hitter matures. But does the data confirm this thinking?

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Before all our attention is focused on the post-season, I thought I’s take a quick look back at free agent signings from the past year and how those deals worked out in 2012. The focus here is just on what teams got for their money. In other words: Did the players meet or exceed the expected value of the contracts they signed?

I focused on major league signings only, so the analysis does not include myriad minor league deals — many of which resulted in players accumulating playing time in the majors this year.

To get a sense of the how the deals turned out, I compared players’ expected values — which are based on their positions and the annual average value (AAV) of their contracts — to their actual values. I uses Matt Swartz’s research on the differences in dollars per Wins Above Replacement (WAR) by position, rather than assume an average dollar-per-WAR, as is typically done.

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I was previewing the Angels and Mariners series that began on Tuesday, kicking off the final nine games of the season for both teams, when I noticed how well the Angels ranked in my metrics. That the Angels are good is no surprise, but the magnitude to which they had improved since they last played the Mariners at the beginning of September caught my notice.

Since that last preview, the Angels went 15-7 with a massive 104-58 run differential. But where did has the dominance burst forth? Over those 22 games, the offense posted a .734 OPS which is only three points above the American League average. On the pitching side, the staff has a 21.7% strikeout rate, a 6.4% walk rate and 3.4% home run rate compared to league averages of 19.4%, 8.2% and 2.8%. That’s an above average line, but not an outright dominant one.

Lacking a breakout in either the bats or arms, it really highlights how well the defense has played. Read the rest of this entry »

There are rate stats for just about every kind of opportunity a hitter faces in a game. Batting average tells you how often a player reaches base via a hit. On-base percentage tells you how often a player avoids making an out per plate appearance. But what about swings as opportunities?

Last year, I played around with the idea of production per swing. The idea was to examine what hitters gave the most value when they took a swing. The methodology was pretty simple: calculate the Weighted On-base Average (wOBA) each hitter generated using their swings — instead of plate appearances — as the denominator*.

Of course, there is a healthy correlation between actual wOBA and wOBA per swing (.83 in 2012), but less so Isolated Power (ISO). (wOBA/swing and ISO share only a .53 correlation.) Some of the results may not be all that surprising, but many certainly are.

Let’s first look at the top-25 so far this year:

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Last Thursday, I took a stab at predicting how batter’s swing influences their ground ball / fly ball splits. One of the most important retorts to the research (a retort made both in the comments and on The Book blog) was that pitch location was the determining factor of bat angles — what I was attributing to hitter tendencies (at least for hitters who have big GB/FB platoon splits).

Consider today’s offering a second puzzle piece — hopefully an edge piece — in what is a 1000-piece puzzle of understanding GB/FB splits. Today I offer the case study of two (essentially randomly picked) hitters with large GB/FB platoon — Adam Dunn and Jay Bruce.

The results surprised me, twice, and in the end, it appears these two hitters employ different swing patterns, suggesting there may be traction with my original theory, even though pitch location does have a considerable affect on swing angles.
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What’s a pitcher’s ultimate goal? In the grand scheme, it’s to help win games. A pitcher needs to do his part to keep runs to a minimum — and strikeouts are the best way to accomplish that. Walking, or hitting a better, can’t help. Those outcomes (plus avoiding home runs) are the three rates, each with somewhat separate skills that most of us watch when evaluating pitchers.

And getting ahead in the count is at least partially responsible for all three outcomes. In my first look at pitching ahead to batters I defined a pitcher’s being ahead in the count as having it 0-1, 0-2 or 1-2. Conversely, batters were ahead in 1-0, 2-0, 3-0, 2-1 or 3-1 counts. Those demarcations were made by simply taking the greater number, aside from full counts.

The aggregate numbers support the difference between the two types. In my self-identified pitcher’s counts, batters are held to a .204/.211/.303 line this season. Shifting to a hitter’s count, the batting line more than doubles to .342/.472/.609. Clearly a pitcher benefits when he’s ahead, but I wanted to know about home runs, as well, and whether this was a good division of counts.

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Dustin Ackley has a strikeout problem. It’s not a problem new to him at this level. Last season in the American League, average hitters struck out on 18% of his trips to the plate. Dustin Ackley did so in 21%. However, it was new to him overall. In the minors, Ackley was terrific at avoiding strikeouts. With Tacoma in 2011, Ackley struck out on 12% of his PAs whilst the average PCL hitter would strike out 18% of the time.

The low strikeouts in the minors made sense. Ackley was billed as a polished hitter with good contact skills and a good eye for the strike zone. And indeed, Ackley has had fewer swinging strikeouts than average at every level, even including his two years now in the Majors.

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We’re only three days from the expansion of major league rosters. On Sept. 1, all players on a team’s 40-man roster will be eligible to play in the big leagues without an accompanying move. Often times, baseball fans are treated to a sneak preview of teams’ top minor league talent as a result of September call-ups; or they’re surprised by a relatively unknown player who manages to contribute over the season’s final month.

In preparation for this year’s roster expansion, I thought it would be interesting to look back at the greatest-ever September call-ups, defined here as players that made their major league debut during the month of September.

There are, of course, two ways to look at this: The first is to look at players — position players and pitchers — who generated the most value for their clubs during their call-up. The second is to look at players whose careers began as a September call-up and then went on to have great careers.

I’m looking at both. Read the rest of this entry »

On July 18, 2009, Willy Aybar, who had not played in 6 days, who could barely play second base and had hardly proven himself as a hitter, got the start at second against eventual the AL Cy Young winner, Zack Greinke. Aybar went 4 for 4 with a game-deciding double.

Rays manager Joe Maddon told the media the choice to start Aybar had been a deliberate one, a decision based in the front office’s proprietary analysis. I remember the event — reading the post-game interview moreso than seeing the game — because it marked the first time in my baseball-viewing experience where I had seen a lineup decision apparently based according to ground ball and fly ball data.

Entering the 2009 season, Greinke had a 37.9% ground ball rate — making him one of the league’s more extreme fly ball starters (this has since changed). Aybar, meanwhile, finished his short career with a .349 wOBA against fly ball pitchers and a .300 wOBA against ground ball pitchers.

Since that July 18 game, the Rays have continued to be one of the very few teams to game the underappreciated GB-FB splits game. I suspect one of the main reasons for that is that teams — namely managers — cannot easily identify and predict the splits. Today, I would like to put forth a theory that suggests we can identify — with decent success — GB-FB splits after just watching a hitter take batting practice. Here is the theory:

THEORY: Batters with an uppercut swing will succeed more against ground ball pitchers, and hitters with a more level plane will succeed more against fly ball pitchers, and — naturally — hitters who can swing on both planes will have a smaller overall split.

Let’s examine:

NOTE: Many GIFs are under the jump. The page may load slowly.
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