Although Carl Pavano had nearly identical FIPs in 2009 and 2010 (4.00 versus 4.02), he achieved them in quite different ways. Pavano, who re-signed with the Twins yesterday, did a great job of limiting walks in both years. But in 2009 he combined that command with average-ish strikeout and ground-ball rates. In 2010, however, had just 4.8 Ks per nine (two per nine fewer than in 2009 and sixth lowest in baseball), but induced grounders on over 50% of balls in play.

Usually such a change in strikeout and ground-ball numbers is the result of a drastic change in pitch usage, see Joel Pineiro’s 2009. But it looks to me like Pavano’s pitch usage has not changed that much from 2009 to 2010:

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Chris Capuano, the Mets’ new left-handed pitcher, has a strange platoon split. Against right-handed batters he gets grounders like Jered Weaver (37%), but against left-handed batters he gets them like Felix Hernandez (54%). The average pitcher has a fairly large difference in strikeout and walk rates by batter-handedness (Capuano’s strikeout and walk splits are standard for a lefty), but a small difference in ground-ball rate. Dave Cameron found that left-handed pitchers get only marginally more grounders against left-handed batters (46%) than against right-handed batters (44%). Capuano’s ground-ball split is out of the ordinary.

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Projecting players is a tough business. Because of the natural tendency to ignore injury risk and reversion to the mean, our instincts lead us to over project. We have seen this with the fans who are about half a win high (and a full win high projecting players on their favorite time) and who are generous with projected playing time.

So it is easy to look at projections and think they look low, and so we should give people a pass when they say so. But when they say so and in the process disparage the projector, I think it’s fair game to call them out. Here is a video of Bob Ryan and Joe Sullivan discussing Bill James’ projections for some Boston Red Sox players (h/t Repoz). Ryan and Sullivan were aghast that Bill James would project Jon Lester for just 14 wins in 2011, joking that their colleague Dan Shaughnessy would say “Bill James doesn’t even like to watch baseball!” and that if James actually watched Lester pitch he might think differently. Ryan claimed that Lester is a 19-game winner for the foreseeable future.

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Yesterday in my Fan Projections 2010 recap I reported that fans do a worse job projecting players on their favorite team than other fans do at projecting those players. This is an interesting finding: these fans probably have more information about those players, but in spite of that do a worse job projecting them. Why is that?
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Yesterday I looked at the 2010 Fan Projections for position players, and specifically how much higher fans of a team projected players on that team compared to non-fans. It turned out to be by about half a win. Commenters to that post wondered which group did a better job projecting the actual performance of the players.

Tango found that the Fan Projections were in the middle of the pack compared to other projection systems: a respectable 10 out of 21, up against the big hitters like CHONE, CAIRO, and Bloomberg. But that was with the Fans as a whole, not split out by the fans’ favorite teams.

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With the opening of the 2011 Fan Projection ballots I thought it would be interesting to look back at the 2010 Fan Projections. The ballots ask fans to identify their favorite team; this allows us to see how differently players are projected by fans of their team than by the fan community as a whole.

Here I will look at this question for the position players (I will look at pitchers in my next post) who had at least 10 ballots by fans of their team. This left 206 position players. I assumed that players would be projected more optimistically by fans of their team than by other fans, and this was the case. On average players were projected half a win higher by fans of their team, with 1.5 runs coming from higher fielding projections and 3.5 runs coming from higher batting projections. Of the 206 players, only 34 were projected worse by fans of their team.

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The offseason offers an opportunity to reflect on the pressing sabremeteric questions of the times: free agent value, fielding metrics, pitchf/x release points. All worthy and important pursuits. Here, though, I hope you will indulge me as I address something much more trivial: the network (or “graph,” as Zuck would say) of baseball players’ twitter accounts.

You see, some baseball players tweet, and, not surprisingly, they follow other baseball players. But what does the network of these connections look like? Are teammates more likely to follow one another? Surely, but how much more likely? If player A follows player B, how likely is it that player B follows player A? And, more generally, how connected is the network — in other words how likely is it that any one player follows another?

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Many commenters to my post yesterday and to David’s original post asked about batter pace. Obviously batters can control the time between pitches (pace) by stepping out of the box often and by spending lots of time out of the box when they do (i.e. step out). Also, based on the results from yesterday’s post, the pace slows for hitters in two-strike counts and when there are runners on, who have a high strikeout rate (because they face more two-strike counts), and who bat with men on base. So I wanted to see how much variability there is in batter pace and take a quick look at the leader board.

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I was excited to see that David Appelman added Pace to the stats pages based on don’t_bring_in_the_lefty’s post at BtBS. It was something I had thought about before when Carson emailed me about including it in NERD. Nothing came of it, but I had the code lying around on my computer and I thought this would be good opportunity to share some of my observations.

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MLB has a crazy new feature that let’s you view the entire crowd of every World Series game and two games from each of the other playoff series. During the game a single camera takes hundreds of photographs of the crowd, which are spliced together into a gigantic panoramic photograph. The photograph is of such high resolution that you can zoom in to see individual faces. It is linked up with Facebook so that you can tag yourself or your friend. It is called TagOramic. This is the full picture from last night’s game.

The boxes indicate how many fans in each section have been tagged. Those tagged have a blue indicator, but only their friends can see who they are. If you are friends with a person the indicator is red, and, if it is you, yellow. Here is a picture zoomed in on a section of the crowd.

Pretty good resolution, MLB gives the details on the photograph:

Panoramic image from the third inning of Game 4 of the World Series at Rangers Ballpark in Arlington, TX. The image is made up of 360 photos (30 across by 12 down) stitched together taken over a 19-minute span. The final hi-res file is 83,287 X 19,158 pixels or 1,596 megapixels. Photos by David Bergman.

I imagine it would be fun to see myself or a friend captured at some random point in the game, but none of my friends have been to any of the games. Even so it is cool to scan around the field and find people mid-hotdog bite, cheering, talking on their phone (it is surprising how many people are talking on or checking their phone), or whatever.

It does feel strange, and a little voyeuristic, to see this one moment in time for 50 thousand-ish people. From a privacy perspective I guess going to a game leaves you open to being projected on the jumbotron, or even being on the TV broadcast, and this isn’t any more of an invasion.

I was on the lookout for a particular group of fans at the game last night and found them in the first row on the first-base line.

Anyway a pretty cool application of high-resolution photography, photo-splicing software and Facebook tagging.