Right around this time last year we looked at how the FAN projections projected the 2010 standings, so now seems to be as good a time as any to take a look at what the 2011 fans have projected the standings to look like based on their individual player projections thus far.

Red Sox       98
Yankees       94
Rays          87
Baltimore     81
Blue Jays     79

Twins         87
Tigers        83
White Sox     79
Cleveland     73
Royals        68

Rangers       85
Angels        79
Athletics     78
Mariners      76

Phillies      90
Marlins       85
Mets          84
Braves        82
Nationals     74

Brewers       84
Cardinals     83
Cubs          82
Reds          80
Pirates       71
Astros        60

Rockies       90
Giants        84
Padres        80
Dodgers       79
Diamondbacks  75

Once again, the fan ballots were a bit optimistic and needed to be scaled back a bit to make the win totals look realistic.

The Braves look obviously low to me (maybe there’s something weird going on there) and the fans really have their hopes up for the Rockies, but I’m pretty pleased with how these came out.

With two of the game’s better players, Justin Morneau and Jason Bay, spending considerable time on the DL last year because of concussions, I decided to take a look at how concussions have been reported and the possible effects head injuries might have on player performance. Thanks to the hard work of Matthew Grosdidier, who compiled most of the data, we have some interesting numbers to look at on head-related trauma.

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Tangotiger posts the official results of his 2007-2010 projection tests. Specifically he tests CHONE, PECOTA, Oliver, ZiPS and the Marcel projection systems using wOBA.

It’s very in depth and there’s a lot of really great information here about how different projection systems fared for different “classes” of players.

With several recent discussions (here and here and here and here) on home team advantage (HTA) – which began with Tobias Moskowitz’s and L. Jon Wertheim’s new book Scorecasting – I decided to see if I could find any reasonable causes for the advantage. I decided to look into areas that I thought home teams may have an advantage, namely errors (not much – about 2 wins league wide) and base running (some), but the number that caught my eye was the differences in batting average on balls in play from the home and away team. Here are the differences in BABIP for the home and away teams over the last few years:

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After analyzing all of the preceding numbers (here and here), I bucketed various players into different bins according to their age, BMI and if they attended college.

The main problem I’ve run into with my analysis is that, as I divide the data, the sample sizes get smaller. With only 947 samples with which to work, the numbers get scattered quickly. For this chart, I’m only looking at the player’s age and his BMI.

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With the general overall numbers available from yesterday’s article, here’s each variable:

Age

I divided the data into several buckets, according to individual pitchers’ ages. Here are the results:

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This is the first in what will be a series on the disabled list. Here’s a link to the data.

I recently posted a projection formula (here and here) that estimated the chance of a starting pitcher spending time on the disabled list. To say the least, it generated several questions.

So I’m going to take a step back and show historic DL numbers for starting pitchers. For the purpose of this post, I’m only looking at pitchers with 20-plus starts and more than 120 innings from the previous season.

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Teams lose players to the disabled list every year, but which teams had the most money tied up with these injured players in 2010? The following list ranks the teams that had the most dollars spent on players on the disabled list and the percentage of total payroll allocated to these days lost:

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Yesterday, I went through the formula used for predicting which starting pitchers have the greatest chances of going on the DL in a given year. Now here are the projections for 2011. Besides revealing the list, a few other points and possible improvements to the process will be discussed.

First, here are the five most and least likely starting pitchers (>20 GS and >120 innings in 2010) to go onto the DL in 2011 (creating these projections is still a work in progress, so no one should take too much stock in them right now):

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I’d like to solicit the help of our community in building a useful fantasy player valuations guide. When we have the parameters set, I’ll code it and put it up on FanGraphs.

There are a couple goals here:

1. Building a useful and easy to use fantasy player valuation guide.
2. Full transparency in how all the rankings work.

I’ve dabbled in this a bit, so I will first give a starting point:

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