What Pitcher Stats Should I Look At?

What if I told you that I knew of a series of stats that could predict with 92% accuracy that a pitcher will finish with a sub 4.50 ERA?  What if I told you the same stats could predict with 75% accuracy that a pitcher will finish with a sub 4.00 ERA?  Would that pique your interest?

Let me back up.  Someone at Orioles Hangout asked me what stats I look for in a pitcher.  This is how I answered the question.  After posting that I realized that I didn’t set the parameters.  So I did some studying.  These are the boundaries that I came up with:

Strikeout % (Strikeouts / Batters Faced) of at least 17%

K/BB (Strikeouts / Unintentional Walks) of at least 2.5

Groundball % ( Groundballs / Balls in Play) of at least 45%

Strike % (Strikes / Pitches Thrown) of at least 64%

Swinging Strike % (Swinging Strikes / Strikes) of at least 15%

So what did I do once I settled on the parameters?  I have the traditional, batted ball, and pitch data stats for the last three years for each of the last three seasons saved in an Excel file.  First, I looked at the 378 pitcher seasons in which the pitcher faced at least 500 batters in a single season in the three years.  Next, I looked at the 380 pitchers who faced a total of at least 500 batters total in the three seasons.

The following shows how the single season pitchers fared in each category (the number meaning the number of categories in which the pitcher exceeded the minimum):

Five – 22 Pitchers – 4,654 IP – 3.54 ERA – 3.53 FIP ERA

Four – 53 Pitchers – 10,396 IP – 3.62 ERA – 3.57 FIP ERA

Three - 60 Pitchers – 11,355 IP – 4.00 ERA – 3.99 FIP ERA

Two - 65 Pitchers – 11,622 IP – 4.49 ERA – 4.37 FIP ERA

One - 110 Pitchers – 18,373 IP – 4.70 ERA – 4.65 FIP ERA

Zero - 68 Pitchers – 11,354 IP – 4.88 ERA – 4.94 FIP ERA

And the same stats for the 3-year pitchers:

Five - 21 Pitchers – 8,405 IP – 3.45 ERA – 3.46 FIP ERA

Four - 50 Pitchers – 15,095 IP – 3.51 ERA – 3.55 FIP ERA

Three - 64 Pitchers – 16,526 IP – 4.02 ERA – 4.03 FIP ERA

Two - 91 Pitchers – 23,011 IP – 4.43 ERA – 4.41 FIP ERA

One - 91 Pitchers – 26,675 IP – 4.70 ERA – 4.62 FIP ERA

Zero - 63 Pitchers – 18,427 IP – 4.86 ERA – 4.89 FIP ERA

What I liked about the above was the consistency of the ERA and FIP ERA between the 3-year and single year stats. 

Onto some other stats:

75 single season (SS) pitchers met at least four of the stat criteria.  Of these 75 pitchers, 69 (92%) finished with an ERA below 4.50, and all of them finished with a FIP ERA of 4.43 or lower.  56 of the 75 (75%) finished with an ERA of less than 4.00, while 65 (87%) finished with a sub 4.00 FIP ERA.

71 three-year (3Y) pitchers met at least four of the stat criteria.  Of these 71 pitchers, 67 (94%) finished with an ERA below 4.50, and all of them finished with a FIP ERA of 4.30 or lower.  58 of the 71 (82%) finished with an ERA of less than 4.00, while 64 (90%) finished with a sub 4.00 FIP ERA.

How about the inverse? 

178 (SS) pitchers met only one or none of the stat criteria.  Of these 178 pitchers, 114 (64%) finished with an ERA above 4.50, and 121 (69%) finished with a FIP ERA of 4.50 or higher.  71 of the 178 (40%) finished with an ERA of at least 5.00, while 49 (28%) finished with a FIP ERA of 5.00 or higher.

154 (3Y) pitchers met only one or none of the stat criteria.  Of these 154 pitchers, 104 (68%) finished with an ERA above 4.50, and 98 (64%) finished with a FIP ERA of 4.50 or higher.  66 of the 154 (43%) finished with an ERA of at least 5.00, while 41 (27%) finished with a FIP ERA of 5.00 or higher.

Food for thought.

Here’s hoping everyone has a great 2008.

Thank you

You Have One Game to Win…

Someone over at the Orioles Hangout asked a great question the other day – if you have one game to win, who would be your starting pitcher? 

I took 20 pitchers who have each faced at least 72 batters during postseason play since 2002.  I originally used the pitchers listed in the OH thread, and then added others as their names came to me.  I only used the regular season numbers for the season in which the pitcher appeared in the postseason.  For instance, since 2002, Curt Schilling has appeared in the 2002, 2004, and 2007 postseasons.  So I compared his 2002, 2004, and 2007 regular season numbers to his 2002, 2004, and 2007 post season numbers. 

First, I want to attack the question using traditional stats, and my favorite – FIP ERA.  Overall, the 20 pitchers combined to post a 3.45 ERA in the 12,400 regular season innings in which they appeared in the playoffs.  The same 20 pitchers combined for a 3.88 ERA in 877 post season innings.  The regular season FIP ERA of the pitchers was 3.65 compared to 4.11 during post season play.  I personally found it interesting that the numbers represented a 12.4% increase in ERA compared to a 12.7% increase in FIP ERA. I will admit that I was surprised that the overall ERA actually increased.  It has always been my assumption that the overall ERA tends to go down in post season play.  Maybe that’s what I get for listening to announcers. 

Now we know that the overall ERA goes up, but do the numbers give us a clue as to why?  BABIP stayed about the same (it increased from .288 to .292).  LOB% is relatively unchanged (73.6% up to 73.8%).  WHIP goes up from 1.18 to 1.26.  K% dropped from 19.7% down to 18.1%, while BB% goes from 6% up to 6.7%.  Command Rate dropped from 3.31 down to 2.72.  So the only relatively big changes seen thus far involved walks and strikeouts.  I suppose this really shouldn’t be a surprise considering these pitchers are facing better hitters.  Want another indicator that the pitchers are facing better hitting?  HR/OFFB% went up a good amount (10.6% up to 12.2%) – this explains the increased ERA as much as anything.   

Of the 20 pitchers in the survey, only six had a better post season ERA than regular season ERA.  This caused me to think maybe the first comparison I made was negatively impacted by those at the bottom.  So I decided to do another comparison, this one taking a look at the pitchers in the survey with the 10 best regular season ERAs.  The ERA change this time was 2.99, compared to 3.13 in the post season.  The FIP ERA change was 3.38 up to 3.67.  Those represent a 5% and 7% increase, respectively.   

We’ve looked at the overall numbers, how’d the pitchers do individually?   

Curt Schilling’s postseason ERA during the time span is 3.17, compared to his 3.39 regular season ERA in the affected seasons. 

The pitcher in the survey with the 5^th best ERA improvement was Andy Pettitte (3.44 down to 3.13 in the postseason). 

Chris Carpenter’s post season ERA was 2.53 compared to 2.95 in the affected regular seasons. 

John Smoltz had the third best improvement in the survey – a 2.76 regular season ERA compared to a 1.96 post season ERA. 

Mariano Rivera’s post season ERA since 2002 was an amazing 0.70 compared to 2.06 in the regular season. 

The biggest ERA improvement from the regular season to the post season?   

Drum roll, please. 

Raise your hand if you guessed Josh Beckett.  His regular season ERA during the 2003 and 2007 seasons was 3.18, compared to 1.78 during those two post seasons.  Before someone says that it’s only two seasons, only three pitchers in the survey have faced more post season batters than Beckett since 2002. 

The three pitchers with the biggest increase in ERA?  Glavine (3.36 to 5.84), R Johnson (3.60 to 7.11), and Wang (3.73 all the way up to 7.58). 

So how did they rank in overall post season ERA since 2002? 

Rivera (0.70), Beckett (1.78), Smoltz (1.96), Carpenter (2.53), Pettitte (3.13),Schilling (3.17), Lackey (3.63), Oswalt (3.66), Santana (3.97), Wells (4.08),Zito (4.11), Mussina (4.19), Pedro (4.39), Clemens (4.50), Morris (4.96),Hudson (5.10), Glavine (5.84), Wakefield (5.91), R Johnson (7.11), Wang (7.58). 

If you have one game to win, who would be your starting pitcher? 

Based on this survey, Josh Beckett seems to be the best bet to me. 

In my next post I’ll take a look at the question from a different angle. 

Thanks. 

Go Rockies!

The Schilling Theory

During Boston’s first trip to Baltimore, Gary Thorne talked about Curt Schilling’s theory of which team would win the division title.  According to Schilling, the opening day five-man rotation which made the most combined starts would win the division.  So, is Curt Schilling on to something? 

The opening day rotation for the Blue Jays made a total of 85 starts.  Their overall total was hurt by the early loss of Gustavo Chacin, who made only five starts.   

The Orioles rotation made 96 starts, with the early exits of Loewen and Wright hurting the overall total. 

The Yankees?  105 starts, with Pavano’s two starts bringing down the total. 

The big surprise to me was Tampa Bay’s rotation, which actually combined for 116 starts.  They actually had three pitchers (Kazmir, Shields, and Jackson) with at least 31 starts. 

For those scoring at home, it looks as if Schilling was right, at least in terms of which team would win the division.  The opening day Red Sox rotation combined for an amazing 140 starts, including at least 23 starts from each member of the rotation. 

The cases of Jeremy Guthrie and Roger Clemens caused me to take it a step further and add the sixth starter to each rotation.  How much of an effect did this have? 

Boston             150 starts

Tampa Bay     138 starts

New York         122 starts

Baltimore         122 starts

Toronto            112 starts 

Kudos to Schilling, at least in terms of forecasting the division winner.  The thing I can’t remember is if he said the final division standings would be determined in the same manner.  If he did, then he wasn’t so right.  I’m probably in the minority here, but seeing Tampa Bay rank so high should make the rest of the division real nervous going into 2008. 

Hearing Thorne talk about the Schilling Theory gave me an idea.  I made a list I called “You’ll Know the 2007 Orioles Had a Bad Season If…”  For instance, one item on my list was “if Rob Bell winds up facing at least 250 batters.” 

I never posted the list because I realized that there was no way so many things could go wrong with one pitching staff.  So I held on to the list until now. Here goes: I’ll know the 2007 Orioles are in trouble if …

• Jon Leicester, Victor Zambrano, Kurt Birkikns and someone named Victor Santos combine for more combined starts (12) than opening day rotation members Adam Loewen and Jaret Wright (9). 

• Jeremy Guthrie starts 26 games.  (Of course, if he somehow gives the team a 3.70 ERA over 175 innings pitched, I would consider this one to be a good thing.)

• Daniel Cabrera shows signs of regression by posting a 5.55 ERA with a 23% lower K-Rate.

• Erik Bedard is not able to start at least 30 games or garner 200 innings pitched.

• Steve Trachsel is actually allowed to start 25 games.  (Of course, if he pulls off the miracle of all miracles and posts a 4.48 ERA, then this would be a good thing.)

• Rob Bell ends up facing at least 250 batters, while Chris Ray faces less than 180.

• Chris Ray and Danys Baez combine for a 5.52 ERA with only 19 saves and only 93 innings pitched.

• Scott Williamson is released following 16 appearances and 14.3 innings pitched.

• Someone or something named Rocky Cherry is a key cog in the bullpen by September.

• Paul Shuey is needed to appear in 25 games.

• The team would need to give starts to 13 pitchers.

• The team would need to use 27 pitchers.

• 19 of the 27 pitchers used posted an ERA higher than 5.00.  (In fact, I would have bet this could not possibly happen.)

• The final overall team ERA is 5.19.

 As I said, I had to keep this list hidden because it was just too far out there.  It’s a good thing none of those things actually happened.

Okay, you got me.  I didn’t make this list five months ago.  No one has an imagination like that.