Archive for Cardinals

With Prince Fielder and Albert Pujols hitting the free-agent market this offseason, there have been many discussions on how the two of them will age. Lots of work has been done on how an average player ages, but Pujols and Fielder aren’t your average players. Which begs the question: How do stars age, compared to the rest of the league?

One of the hardest aspects when looking at elite players’ aging curves is knowing when to consider them elite. Several hitters who are playing right now appear to be sure-fire hall-of-famers — just as long as their careers don’t do an Andruw Jones nose-dive toward uselessness. To generate a list of players who seem headed toward stardom, I selected players since 1980 who had a total of 20-plus WAR during a three-year span. Also, I took the players who generated WAR of 9.5 or more in a single season.

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Mayhaps this is the season of hiring the un-experienced?

Last October, the White Sox announced a surprise decision to hire Robin Ventura — a once-great third baseman who had been hired four months prior as a special assistant. Ventura, who played some high quality baseball in some three decades, has managed nary a single MLB or MiLB game in his life.

Then, weeks later and a few dozen hours ago, the St. Louis Cardinals hired Mike Matheny — a once-illustrious catcher and he of the ne’er .300 wOBA — to replace likely first ballot Hall o’ Famer Tony La Russa. Like Ventura, Matheny has not yet scribed a professional-league lineup card or even tossed a base in anger. He enters the 2012 MLB season a complete unknown to fans and writers and presumably of good number of his own players.

But then again, what do fans and writers really know about even Tony La Russa? He made some strange decisions, he made some smart decisions, and he made some bad decisions. He gave a good interview, and he presided over a few championship teams.

But what does that really tell us? Where does that leave the ledger? For years we have debated the veracity of certain managers, but what measures and records can we go to?

One thing is for sure: The world of managing needs more statistics.

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On Tuesday, we took a quick look at the competitive balance in the MLB, and I made the claim that baseball may have more parity than most leagues, but it also has want of greater balance. During the course of the piece, I made this statement:

The NFL has decided it wants payroll to have essentially no impact on winning, so teams basically trot out the same amount of money every Sunday and hope their money was better-spent. Is that what the MLB wants?

Aft’wards, Paul Swydan pointed out to me that indeed NFL salaries are not flat. Despite their hard cap, their hefty revenue sharing, and their tight spandex pants, the NFL still exhibits nearly a $77M gap between the biggest and lowest payroll — impressive, but still nothing compared to the MLB:

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Yesterday afternoon, Jayson Stark considered the question, “Is the MLB’s competitive balance a joke?” His answer was a rather blunt no:

MLB’s competitive balance is NOT a joke.

It beats the NFL.

It beats the league formerly known as the NBA.

And … I can prove it.

Stark’s method of proving it — plucking facts from the recent playoff series and comparing them generally to the NFL and other major leagues — was less than rigorous. In general, I agreed with his assertion: Parity in the MLB exists naturally far more than any other sports league.

HOWEVER, if my foot has less gangrene than your foot, does that mean I don’t need a doctor? No. I probably still need a doctor, and I probably need to stop playing barefoot tag on Rusty Nails Pier.

Relative success does not necessitate absolute success. And frankly, I feel the “parity” in the MLB indeed has a gangrene of sorts, a disease that is causing only specific segments of the league to rot while the rest hum along uncaring.

Of course, it is one thing to suspect something and demand more research, but it is another to pull the sabermetrician stocking over your head and answer that suspicion with a Falcon Punch of data.

Let’s do just that.
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Previous entries:
Primer
The Full Story
Batters

In a series with a 16-7 game and an 11-10 game, and one in which the big moments were dominated by the hitters, it can be easy to forget about the pitchers. And although the performances of Chris Carpenter and Derek Holland pale behind those of David Freese and Lance Berkman, they deserve to be remembered.

On the other side of the coin, Jason Motte, who was so excellent in the first two rounds of the playoffs, was bailed out by his teammates in the final two games. As poorly as Motte pitched, it was the entire Rangers bullpen that collapsed, with Scott Feldman, Neftali Feliz, Alexi Ogando, and Mark Lowe all coming up well negative for Ron Washington and the Rangers.

Observe, the leaders and trailers in pitcher series probability added for the 2011 World Series:

Click to see the fully functioning visualization and follow the jump for more.

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Yesterday, Cubs President of Baseball Operations Theo Epstein announced the Chicago Cubs and manager Mike Quade have parted ways. Kudos to Theo Epstein for not doing what we all expected him to: Fire Quade immediately.

It appears Epstein — like he has approached most everything in his young Cubs reign — decided to withhold judgement until he had fully investigated the matter himself. Like Joe Maddon is wont to say, “Tell me what you think, not what you heard.”

Quade’s managerial time with the Cubs was both short and possibly undeserved. Taking the helm when Lou Piniella suddenly retired in 2010, Quade inherited a team that was predisposed towards failure. But, despite that, the team went 24-13 to close out the season. That was enough proof for Jim Hendry to vault Quade not only into the manager discussion, but the manager’s chair:

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In yesterday’s primer, I introduced the basics behind World Series win probabilities. Today, we begin looking at the 2011 World Series through this lens.

The first natural use of win probabilities, especially on FanGraphs, is the win probability graph. Observe, the graph of series win probability for the St. Louis Cardinals throughout the World Series:

Click to view the graph in a new window with all the bells and whistles provided by the Tableau software.

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Tony LaRussa announced yesterday that he will not return to manage the St. Louis Cardinals in 2012. He used the word “retirement” so we’ll take him at his word that after 5,097 Major League Baseball games, LaRussa’s managed his last one.

You’re likely familiar with his career highlights:

• 2,738 career wins as manager, 3rd most after Connie Mack and John McGraw
• .537 career winning percentage as manager
• 3 World Series titles as manager
• 3 American League pennants as manager
• 3 National League pennants as manager
• 14 postseasons as manager
• 4 Manager of the Year Awards (with another one likely this year)

But these numbers only begin to scratch the surface of Tony LaRussa’s managerial career.  Let’s take a closer look.

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Disclaimer: this post will not contain any wOBAs, xFIPs, or UZRs. This is the story of Game 7 from the perspective of one fan — me.

As soon as David Freese’s home run landed in the grass beyond the centerfield wall, ending Game 6, I made up my mind that I was going to the stadium for Game 7. It was an interesting and amazing night, and I thought I’d try to relay that experience.

On Friday in St. Louis everyone seemingly adopted new salutations. Gone were “hello” and “goodbye”, instead, every conversation started with, “Could you believe that game last night?” and ended with, “The Cards have to win tonight.” Everyone at my office spent most of their Friday passing around emails with the best links about Game 6 (the win expectancy graph being one popular option). Cardinals fans are always crazy about their team, and we’ve been in two World Series recently, but I’ve never seen anything like the buzz for Game 7.

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Over the next few days, I will be running out a series based on win probabilities from the World Series not only using single game win probabilities like the ones in our game graphs, but also using overall series win probabilities, which will be introduced today.

The idea behind the series win probabilities is based around the same idea as the single game win probabilities we use here: both teams have a 50% chance of winning each game. As such, this flow chart describes every possible path for a team through the World Series (or any other seven game series; the part from 1-1 up would describe a five-game series):

Click to embiggen, and then follow the jump for more on what’s inside.

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