This article was originally published on WahooBlues.com.

Everyone knows that money matters in baseball. I’m a Cleveland fan, so you don’t need to convince me that my small-market Indians are at an unfair disadvantage when competing against teams like the Yankees and the Bank of Steinbrenner (in the immortal words of Ken Tremendous, “It’s like Scrooge McDuck’s gold coin-filled pool”). There’s no question that franchises with the financial flexibility to retain their stars, import new ones, and remain contenders even when their well-paid players bust have a leg-up from the get-go.

But we all know that money isn’t everything. Omar Minaya and the New York Mets gave us a years-long crash course in what happens large payrolls are spent poorly. Meanwhile, plenty of underfunded teams have had success, including last year’s Rangers and the Rays of both 2008 and 2010. Check my facts on this, but I’m pretty sure one or two low-budget Oakland A’s teams have had some mild success in the past too.

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Often I would like to have an estimate of a player’s true talent in a past year. Projection systems are always only focused on predicting future performance based on past results, but what I wanted was the best estimate of the expected performance for a player in a given year, based on his results in that year and the surrounding years.

I wanted to find suitable weights to assign to performance in the given year, plus the years immediately before and after, and have the right amount of regression to the mean. But I kept running into the same mental block; how to assign a weight to the given year’s performance, since that is exactly what I am trying to “predict”?

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On the surface, Brett Gardner looks like a Bobby Abreu protege (without any power). Since 2010, Brett has shown off his great eye for pitches, posting the 2nd lowest chase rate in baseball at 18.1%.

His ability to make contact with pitches is also astonishing, as he makes contact with 97.2% with pitches in the strike zone, behind only Juan Pierre and Marco Scutaro. Of the 2789 pitches Brett has seen since the start of 2010, he has only swung and missed at 265 pitches.

Where Brett Gardner lacks is in his ability to swing at pitches in the strike zone. Over the last two seasons, Brett has swung at a major league low 45.2% of pitches in the strike zone. He owns this record almost 6% (next lowest is Elvis Andrus at 50.9%) and is almost 20% below the league average. Combined with his low chase rates, its only natural also that Brett has the lowest swing rate in MLB at 31.3%, compared to the league average of 45.6%.

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All major league sports division winners gain entry into the playoffs–the difference is HOW those division victors are determined. For example, the NFL places a greater weight on division record, so much so that a 8-8 division winner (like the 2010 Seahawks) is seeded higher than a wild card with a better record (like the 2010 New Orleans Saints). The NBA gives the top three seeds in each conference to the division winners, with winning the division based on overall instead of division record.

I was curious how baseball playoffs would be affected if a team’s division record determined the division winner, and I expected to see a handful of changes. I was VERY surprised with what I saw. Read the rest of this entry »

This article was originally published on WahooBlues.com.

There’s no question that Albert Pujols is one of the greatest players in the history of Major League Baseball. As the active leader in wOBA (.434) and wRC+ (169), it’s not easy to come up with a superlative that sounds like hyperbole for Pujols. But a commenter on his stats page gave it a try last week:

ALBERT Einstein had an IQ of 160. That means he is 60% more intelligent than the average human.

Albert Pujols has a wRC+ of 177 during the past 3 seasons. That means he is 77% better at the plate than the average big leaguer.

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How accurate were our Steamer Projections?  Which system or combination of systems should we use to prepare for our fantasy baseball draft?  Thanks to MGL’s work we already know that Steamer had great success projecting pitcher quality in 2010 and less success projecting batter quality.  Here will we attempt to discover why some systems are having more success than others by breaking hitting and pitching performances into components.  This should also serve as a follow-up to our analysis from a year ago.

Full Disclosure

As the creators of Steamer Projections you may be justifiably skeptical of our ability to serve as an unbiased judge of projection systems.  In an attempt to allay your concerns we are making our data set available here so that anyone can check our data or pursue their own analysis.

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After an apparent breakout season in 2009, Adam Lind regressed somewhat drastically trying to follow it up in 2010. The idea of Lind being able to play left field was all but completely abandoned in 2010 and he served as the team’s primary DH for much of the season. That was a move that couldn’t be argued against heading into 2010 because his defense was well below average and he looked to have a good enough bat to bring solid value from a DH role.

That however, is not what happened last season as Lind went from being a 3.5 WAR player in 2009 to a -.3 WAR player in 2010. His health had nothing to with the drop in production either, Lind played in 150 games last year after playing in 151 in 2009. The drop came entirely from his bat as his batting runs above average fell by 40 runs, from 35.9 to -5.9. Moving almost exclusively to DH actually helped his fWAR in 2010. His fielding and positional adjustment cost him 22.4 runs in 2009 but only 17.2 runs last year.

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I made some mistakes, some careless, some unknown, with the charts included in my post titled “The Elusive Clutch Hitter,” and I wanted to clear them up.

The first correction shows the batters in my sample who had an increase of at least 10% in batting average with runners in scoring position (RISP) vs. no runners in scoring position (nRISP). It was my intention to do this all along–indeed, I had posted earlier and woke up the next day and realized I had compared RISP batting average with career batting average, which would cause an overlap in the data. I trashed that post prior to it being published, but it appears I made the same mistake, at least with this particular chart. Here’s the corrected chart:
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It’s (almost) spring (training), and a young man’s thoughts turns to baseball metrics. I’ll start with two charts:

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If you haven’t heard anything about what Albert Pujols’ value will be over the next 7-10 years, I suggest you go here…Or here…Or here…Or take a look at the discussion here. Haven’t had enough? Read on.

Somebody is going to sign Pujols to a massive contract in the next 12 months. That contract will likely be hard to justify in projected on field value alone. If you are a fan of the team that gets him, after you get done saying PUJOLSAWESOMEBASEBALLYAY, you may want to know what his expected value will be and then take some time rationalizing the contract to yourself and justifying it to rival fans.

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