2013 Marcels Added and Available for Download

OK, I have finalized the 2013 Marcel’s data which Tom Tango may or may not release this season:


Also, the data has been added to the Marcel comparison tool (looks for similar players and how they produced in the year of the projection - a way good to find % chance of under or over performed).


With the default values, Trout had no comparable 22-year-olds. By spreading out the criteria, I got 3 comps since 1952, Hank Aaron, Frank Robinson and Miguel Cabrera. Not a shabby list.

Updates: Starting Pitcher Injury Factors and Batted Ball Distance

First of all, I have finall completed my starting pitcher injury factors in an article on James Shields at FanGraphs. Here is my description on how the tool works:

• It is slow, almost painfully slow at times. With everyone possibly using it right after this article is released, it may be even slower. Right now, it takes over 1 minute to process one pitcher for just one year. If it is too slow over the next day or so, try it again when less people may be using it.

• Predicting possible injures is an imprecise science. Two pitchers could have almost identical values, but one may need Tommy John surgery and the other one wouldn’t. All I have done is make data available on traits which have been previously known to lead to injuries.

• Directions: Select a starting pitcher (tool only really works with starters because a minimum number of pitches needs to be thrown) and date range. Press submit. Next will come up a most common pitches chart for the pitcher. Pick the most common fastball (to use FA if going back to 2009). Press Submit and have a drink or take a nap because this may take a while. The results will eventually appear.

• The first graph is pretty simple. An average velocity graph for the selected pitch with a 5 game average curve.

• The second graph measures late game consistency. A 100 value is an inconsistent pitcher and 0 value is a consistent pitcher. I got the values by looking at pitchers with major arm issues in a season and pitchers without arm issues in a season. Then, I compared one group of pitchers to the others over the last 10 fastballs thrown in each game. Velocity, release points and break were examined using logistic regression. In the end, I got a formula which detects inconsistencies. The exact cause of the inconsistent is not outputted. The user will need to go look at the game data to find the pitcher’s exact issue. Note: Pitchers, like Bruce Chen, who have two distinct release points, will have all their values near 100. I have not been able to work out this problem yet.

• The final graph is the pitcher’s Zone%. A value under 47% (baseline value on graph) means the pitcher had issues throwing strikes and is more likely to be injured.

• In the near future, I will be going back and looking at how the values can be applied to other pitchers and situations.

Let me know of any issue or ideas for improvement.

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Colorado Center Fielders and Defensive Metrics

Defensive metrics, specifically UZR, does not like think Colorado center fielders (CF) are good defenders. From 2002 to 2012, they are ranked second to last in total UZR. I am going to take a brief look to see if UZR under rates the defense of Rockies’ center fielders.

The easy solution to see if a bias exists would be to compare the home and away UZR values, but those numbers don’t exist. Instead, I will use my own defensive metric, Out% to create home and away defense values. Out% just looks at the number of outs a position/player makes taking nothing else into account. Here are some baseline values for the situation:

Criteria (2002 to 2012): Out%
All CF from 2002 to 2012: 9.4%
COL CF (home and away): 8.7% (ranked last)
COL CF (away):9.1%
COL CF at home:8.4%
Other teams at COL: 8.9%

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Two New Leaderboards - Edge% and wBABIP

I have written a couple articles recently at FanGraphs on wBABIP and Edge%. I have added the two metrics to the pitcher application menu.


From the Rotographs article:

The idea behind using wBABIP is to see if a pitcher gave up an abnormally high number of extra base hits. The the cause of the extra base hits could have been from the pitcher throwing meatballs or slow footed outfielders. The goal is to see if the damage done from batted balls was evenly distributed or were there some extreme cases.

As a whole, I didn’t find the enhancement on BABIP was really needed. Not enough extra information can be extracted from wBABIP to use it in addition to BABIP. Initially, I though I would find a little extra information on some pitchers. In the end, I found wBABIP was just overkill.


From the FanGraphs article:

Pitchers can be productive with a Zone% around 45%. The key is to limit the amount of pitches right down the middle of the plate. A pitcher needs to throw at the inside and outside edges of the strike zone. Pitches near the edge of the plate are hard to hit solidly.

Results of Knuckleball Throwers In Domes

With R.A. Dickey throwing in a dome for 1/2 of his games in a dome. Here are the results of pitchers in domes instead of in open air for comparison. It looks like knuckleball pitchers throw a bit better in domes.

Steve Sparks BABIP K% BB% HR/9 ERA
Open 0.295 27.9% 22.0% 1.10 5.00
Dome 0.275 36.9% 24.2% 0.66 3.89
Joe Neikro
Open 0.275 31.7% 22.1% 0.85 3.94
Dome 0.268 42.9% 27.9% 0.40 2.95
Phil Nekro
Open 0.273 44.5% 23.3% 0.80 3.35
Dome 0.281 49.2% 19.0% 0.85 3.31
Charlie Hough
Open 0.254 46.0% 31.2% 0.92 3.76
Dome 0.248 42.9% 33.8% 0.80 3.56
Tim Wakfield
Open 0.277 40.9% 22.0% 1.18 4.43
Dome 0.260 48.9% 28.8% 1.06 4.29
Tom Candiotti
Open 0.283 43.4% 21.4% 0.82 3.69
Dome 0.293 47.4% 22.3% 0.90 4.31
R.A. Dickey
Open 0.293 43.5% 17.2% 1.04 3.91
Dome 0.307 44.3% 23.7% 1.13 4.41

Updates to Batted Ball Angle and Distance Including Leaderboards

1. Batted Ball Leaderboards (link - under Applications - Batters - Batted Ball Leaderboards)

Two leaderboards were created for each season. The first if the average home run and flyball distance for the top 300 flyball hitters in the league. The data is divided up by handedness. The second list, is the angle of the ground balls and line drives a player hits by handedness. This list shows the most likely hitters to pull a ball and therefore are more likely to see some form of shift against them.

2. In the previously created batter applications (example), a hitters handedness data can now be selected