Effect of pitcher symbols on batter rating

I adjusted my rating method to take average pitcher symbols into account on the batters’ cards. As expected, the effect is most profound for guys with big walk & HR ranges, as can be seen for a few guys in the table below. “Before” means pitcher symbols were not taken into account; “after” means they were taken into account.

[image lost]

The higher-rated players will have bigger differences, simply because lots of homers & walks make them highly rated. Of course, nothing changed in the cards, it’s just that I overrated the batters. Assuming my current ratings are much more accurate, I overrated Burrell’s performance by 7.4%, not an insignificant amount!

Average pitcher symbols

For a calculation, I need to know the symbol content of the average pitcher. I did the starters and relievers separately, using the ABL pitchers. Say that of 53 likely ABL starters, 19 have a B symbol. That means that the average starter has 19/53 (0.36) of a B. The chart below shows the averages for all the symbols. Starters & relievers are combined in a ratio of 7:2, to estimate the pitching over an entire game.

avg-symbols.png

Starters & relievers are quite comparable in terms of the walk symbols, B & L. Relievers have a definite edge for the runners-on symbols, R & H. Not surprisingly, only relievers have Fs.

Series 2: Tally

Game 1 was a heartbreaker. Was out-hit, but had a chance in the top of the 10th. Maybe I should have brought Embree in late.

TV  000 010 100 0  2  6 0
TAL 200 000 000 2  4 12 0

Game 2 was a laugher, until I managed to get the tying run to the plate with no outs. No dice.

I walked Bonds & Dunn intentionally to load the bases, and it cost me one run. That’s probably not bad, and it didn’t cost the game.

TV  010 000 004  5 11 1
TAL 211 030 00x  7  7 0 

No deep rolls in either game!

Hamels got 3 B fouls, including two in a row for an out. No H/R/L/F in either game.

The speedy Terriers were 4 for 5 in steals. No one was caught napping not holding runners on.

Titusville falls to 2-2.

Continue reading Series 2: Tally

quantifying error rating in terms of batting

This is a first step toward measuring defensive in terms of offense. The question to answer is: how much good hitting makes up for poor fielding? Or, to look at it from the other side, to what extent does superior glove work compensate for light hitting?

There are two components to defense: error and range. Let’s consider error rating only for the moment. And let’s hope my logic is correct.

For one PA of his own, a player will be in the field for approximately nine PAs by the opponent. For one opponent PA, the chance of rolling a possible error is 6.3%, which is 60 rolls on 11-70 plus about 20% of the 16 rolls on 81-96 (Park Effects). A possible error will fall on our guy’s position 10% of the time. So, over 9 opponent PAs, the average number of possible errors for our guy will be 9 * 6.3% * 10% = 0.057, which is equivalent to 57 rolls.

Now we have to consider specific positions. Let’s look at 3B/SS, where errors occur the most, and let’s consider the most extreme difference in error ratings. On a possible error, an error-20 thirdbaseman (Jeff Cirillo) will make an error 24% of the time, while an error-1 (Ryan Braun) will boot it 99% of the time. Let’s ignore the more complex outcomes (E(2), 1B+E(1), RG+) and just say that an error is equivalent to a single. In other words, an error made on defense neutralizes a single hit by the same guy on offense. The 57 rolls calculated above will work out to 14 rolls for a Cirillo error/single and 56 rolls for a Braun error/single, a difference of 42 rolls.

One could use these results to adjust a player’s offensive rating. 14 of Cirillo’s average 25 1B range are neutralized by his errors. Via linear weights, Braun’s 56 neutralized singles are equivalent to 18 neutralized HR rolls. (Braun has a 95 HR range vs. L, 35 vs. R.) You could also do a comparison and say that Braun would have to have 42 more 1B rolls (or 14 more HR rolls, or equivalent) than Cirillo to make him equal value, all other things (range, power, etc.) being equal.

These “neutralized rolls” can be similarly calculated for other positions and all the error ratings. The results are plotted in the graph below. I didn’t count E(0)s (dropped fouls) as errors on the catcher.

neutral1.png

The numbers in the chart are just approximations, and each position’s accuracy is different. For example, all the catcher errors counted are of the two-base variety. Anyway, it’s a start.

It’s interesting that, with the exception of the catcher & outfielders, all the lines are nearly parallel. So the difference between an error-20 & an error-1 at a given position is pretty much the same for either 1B, 2B, SS, 3B, or P.

average batter card

Using the rating data (the best half of the free agents plus the Titusville roster), an average batter card can be calculated.

   vs L                vs R
---------           ---------
  0 -  10    Crazy    0 -  10
 11 -  70    Error   11 -  70
 71 -  80     LO     71 -  80
 81 -  96    Park    81 -  96
 97 - 140     1B     97 - 134
141 - 152     2B    135 - 144
153 - 174     DP    145 - 166
175 - 218     1B    167 - 204
219 - 221     3B    205 - 206
222 - 229     SF    207 - 215
230 - 245     HR    216 - 229
246 - 250     HB    230 - 234
251 - 278     RG    235 - 270
279 - 324     BB    271 - 302
325 - 399     K     303 - 379
400 - 412     2B    380 - 389
413 - 441     RG    390 - 426
442 - 499     EF    427 - 499

In terms of ranges, it looks like this:

  vs L             vs R
 ------           ------
   11.0    Crazy    11.0
   60.0    Error    60.0
   10.0     LO      10.0
   16.0    Park     16.0
   43.5     1B      37.9
   12.0     2B       9.7
   22.5     DP      22.2
   44.0     1B      38.4
    2.9     3B       2.3
    8.1     SF       8.3
   16.0     HR      13.9
    4.5     HB       5.2
   28.5     RG      36.1
   46.3     BB      32.2
   75.0     K       77.1
   12.4     2B      10.2
   28.9     RG      36.6
   58.3     EF      73.1

You can see why lefty pitchers can have a hard time.

Rating for the draft

For the draft I developed a rating based on linear weights. The basic idea was to predict run production for batters & run surrender for pitchers. I did not use SB, CS, (AB-H), or GIDP. I simply tallied the ranges on each side for 1B, 2B, 3B, HR, BB, & HBP.

I computed ratings vs. each side, then combined them according to the average number of arms/bats faced. This was not a very good choice, an opinion that the Commish shared. Next time I’ll use weights that also depend on the bat/arm of the player. That is, instead of just saying that a pitcher faces a righty bat 59% of the time, I’ll take into account that a lefty pitcher faces a righty bat 73% of the time, while a righty pitcher faces a righty bat 54% of the time.

Deeps and power were accounted for by using some of the Deep Engine work. Pitcher symbols B, H, R, & L were taken into account.

Things not taken into account:

  • defense
  • speed
  • double plays
  • pitcher symbol F
  • stamina
  • age
  • injury

For the draft I rated the 15 keeps and about half the free agents, who were selected by simply eye-balling the cards quickly.

Here’s the list of batter ratings. First, all batters are listed, followed by separate lists for each position. The columns are:

  1. name,
  2. position(s),
  3. overall rating,
  4. rating vs. righty arms,
  5. rating vs. lefty arms.

Here’s the list of pitcher ratings, separated into starters, shorts, longs, & closers. The columns are:

  1. name,
  2. arm,
  3. stamina/relief
  4. symbols,
  5. overall rating,
  6. rating vs. righty bats,
  7. rating vs. lefty bats.

Series 1: C-Bay

  • We got each other once apiece stealing third with no one holding on second.
  • Two of three SB attempts against Castro were successful. Commish thinks he will lead in CS as well as SB, simply because the attempts will be so high.
  • C-Bay is loaded w/ switch hitters—game 2 saw four in a row, for a total of six lefty bats against Hill.
  • Need to keep an eye on Timlin (H) with runners on. I left him in with the tying run at the plate, Hamilton. That increased the deeps from 21 to 68! In fact, he rolled a true deep and had, I think, 36 or higher to homer, but rolled under. Whew!
  • My defense chart wasn’t very useful.
  • TV pitchers hit four batters.
GAME 1

TV  000 102 022   7 10 1
CB  010 000 010   2  5 0

GAME 2

TV  003 020 200   7 11 1
CB  110 010 001   4 13 1

Continue reading Series 1: C-Bay

Titusville roster

HOWARD, RYAN       3          144 156vR 102vL  5/1 1
CASTRO, RAMON      2          132 132vR 133vL  3/0 1
UTLEY, CHASE       4          128 133vR 108vL  7/8 2
BLALOCK, HANK      5          123 129vR 101vL  5/3 1
BURRELL, PAT       7          120 118vR 128vL  5/0 1
LUDWICK, RYAN      7;9        119 134vR  65vL  3/0 4
ROWAND, AARON      8          109 106vR 120vL  6/3 3
ROLLINS, JIMMY     6          106 104vR 109vL 10/9 1
NADY, XAVIER       9;8;7      102 103vR  95vL  6/2 1
WILLINGHAM, JOSH   7           97 108vR  58vL  7/7 1
WERTH, JASON       9;7         97  82vR 152vL  7/6 3
COSTE, CHRIS       2           92  80vR 135vL  4/0 4
BYRNES, ERIC       7;9;8       84  83vR  90vL 10/9 2
DOBBS, GREG        5;3;7       83  88vR  62vL  6/3 1
GOMEZ, CHRIS       5;3;6;4     78  78vR  77vL  4/0 5


STARTER

LILLY, TED         L 29/  B  L   45  39R  54L
HILL, SHAWN        R 27/  B  L   50  31R  77L
HAMELS, COLE       L 33/  BR L   53  40R  71L
HERNANDEZ, ORLANDO R 27/         53  38R  74L

SHORT

PERCIVAL, TROY     R  0/s B  L   22   9R  39L
GUERRIER, MATT     R  0/s B  L   41  25R  63L
TIMLIN, MIKE       R  0/s B HL   42  50R  31L
MYERS, BRETT       R  0/s  R     57  66R  44L
EMBREE, ALAN       L  0/s    L   62  75R  43L

CLOSER

DEMPSTER, RYAN     R  0/c        54  45R  68L

The cryptic numbers are explained in the ratings post.

ABL Draft

The big needs going in: starting pitching & a thirdbaseman.

  1. Ted Lilly, starter. He was my top-rated starter.
  2. Hank Blalock, 3B. My second choice after Ryan Braun.
  3. Troy Percival, short. My top-rated reliever. Absolutely kills righty bats.
  4. Ramon Castro, C. Top-rated catcher by far. +3 throw is a drawback.
  5. Ryan Ludwick, LF/RF. Will platoon with Werth in right.
  6. Shawn Hill, starter. My fourth-rated starter, equivalent to Harang.
  7. Mike Timlin, short. The best guy left against lefty bats. Neither he nor Percival will be around for long, of course.
  8. Xavier Nady, RF/CF/LF. Utility outfielder with good, balanced hitting.
  9. Chris Gomez, 3B/1B/SS/2B. Utility infielder.
  10. Matt Guerrier, short. About the only short left in my top 20.
  11. Jose Molina, C. Can pinch-hit against lefties, but as third catcher will go down to the taxi team.
  12. Orlando Hernandez, starter. Despite the age & the 3 injury, he was still rated much higher than my fourth starter at the time, Kendrick, who goes down to the taxi team.
  13. Ryan Dempster, closer. Not many outstanding closers in the draft.
  14. Alan Embree, short. Not highly rated, but I didn’t have a single lefty in the pen.
  15. Eric Byrnes, LF/RF/CF. Got him for his speed.

I almost thought that Braun might last to the second round, and the bullpen is a bit of a mess, but all in all I’m happy with how Tit made out.

Deep Engine 3

The 2008 ABL schedule is out, so I can calculate the Deep numbers for the Perfectos’ games, half of which will be played in Busch III.

     power:     5        4        3        2        1

   homerun:   33.23%   17.83%    7.99%    2.95%    0.78%
    caught:   62.87%   78.26%   88.10%   93.14%   95.32%
      foul:    3.90%    3.91%    3.91%    3.91%    3.90%

Compare this to the average of all the 2008 ABL parks…

     power:     5        4        3        2        1

   homerun:   40.45%   24.74%   12.86%    5.28%    1.54%
    caught:   55.65%   71.36%   83.24%   90.82%   94.56%
      foul:    3.90%    3.90%    3.90%    3.89%    3.90%

…and the average of all the MLB parks:

     power:     5        4        3        2        1

   homerun:   48.55%   32.38%   19.18%    9.26%    3.11%
    caught:   47.55%   63.72%   76.92%   86.84%   92.99%
      foul:    3.90%    3.90%    3.90%    3.89%    3.90%

So, the Perfectos will not hit many out on Deep rolls this season, but neither will the opposition.

Deep Engine 2

More data from the Deep Engine. All results are based on ten million trials.

Here’s the results for all 30 parks from the TPB 2007 data:

     power:     5        4        3        2        1

   homerun:   48.55%   32.38%   19.18%    9.26%    3.11%
    caught:   47.55%   63.72%   76.92%   86.84%   92.99%
      foul:    3.90%    3.90%    3.90%    3.89%    3.90%

As expected, no significant changes from 2006.

I re-ran with the 12 2008 ABL parks, using the TPB 2007 data.

     power:     5        4        3        2        1

   homerun:   40.45%   24.74%   12.86%    5.28%    1.54%
    caught:   55.65%   71.36%   83.24%   90.82%   94.56%
      foul:    3.90%    3.90%    3.90%    3.89%    3.90%

Wow, there are some big parks in the 2008 ABL! It’s much harder to homer, especially for the light hitters who will find it almost twice as hard to hit them out in the ABL compared to the 30-park circuit.

Now let’s see how the numbers look for the different hitting types. Again, this is ten million trials in the 2008 ABL parks.

Rsp
     power:     5        4        3        2        1
   homerun:   39.79%   24.05%   12.36%    5.01%    1.44%
    caught:   57.61%   73.34%   85.03%   92.38%   95.95%
      foul:    2.60%    2.61%    2.61%    2.60%    2.60%


Lsp
     power:     5        4        3        2        1
   homerun:   39.96%   24.20%   12.48%    5.02%    1.46%
    caught:   57.44%   73.19%   84.91%   92.38%   95.94%
      foul:    2.60%    2.60%    2.61%    2.59%    2.60%


Rp
     power:     5        4        3        2        1
   homerun:   40.83%   25.34%   13.35%    5.72%    1.68%
    caught:   53.98%   69.47%   81.46%   89.09%   93.11%
      foul:    5.19%    5.19%    5.19%    5.19%    5.21%


Lp
     power:     5        4        3        2        1
   homerun:   41.23%   25.34%   13.21%    5.37%    1.58%
    caught:   53.55%   69.47%   81.58%   89.43%   93.23%
      foul:    5.21%    5.19%    5.21%    5.20%    5.19%

Not surprisingly, the pull hitters end up with more foul balls. In spite of that, they still end up with a greater probability of homering.

This data can be combined with the batter’s power & the average deeps to estimate the number of home runs a batter will get with Deep! rolls against an average pitcher. Actually, the difference in home-run potential is so similar among the hitting types, that it’s not worth making a distinction. So, for example, a power-5 hitter will homer on about 40% of his 18.7 deep rolls against the average pitcher, effectively giving him an additional 7.5 home-run range.

Combine this with the power distribution, and the probability of a home run on a Deep roll works out to 20.4%. That’s an important number for rating individual pitchers against the average batter.

average power

To assess deep ranges I need stats on the power ratings. The breakdown for the 212 franchise players:

power  #   pct
-----  --  ---
  5    60  28%
  4    50  24%
  3    33  16%
  2    33  16%
  1    36  17%

The average is 3.31 (3.29 vs L, 3.32 vs R). These numbers are likely inflated, as the franchise hitters surely have more power compared to the entire field, but the franchise players will get most of the PAs.

L/R averages

Another vital parameter: How often does a batter face a righty/lefty pitcher? From the 2007 ABL stats: 78.3% of innings pitched were by right-handers, 21.7% of the IPs were from lefties. I had guessed it would have been about a third lefties.

Another way to figure this is to figure the total splits for 2007 PAs at Baseball Reference. (NL, AL) Can figure the batting sides while we’re at it.

       TOTAL     NL       AL
       -----    -----    -----
RHP    72.6%    71.8%    73.4%
LHP    27.4%    28.2%    26.6%

RHB    58.9%    60.6%    56.9%
LHB    41.1%    39.4%    43.1%