The Name Game

Growing up in Philadelphia, and raised in an extreme sports environment, Jayson Stark has always been an idol of mine. In fact it was reading his Philadelphia Inquirer column every week that eventually propelled me into sabermetrics. His columns always combined humor and statistics in order to show all of the hilarious or newsworthy baseball happenings that could not be seen on an ESPN show. Not shocking in the least, ESPN eventually brought him onboard. That being said, I thought I would do my sports-writing idol proud by writing an article in a style similar to his.
The idea for this came to me when the Phillies signed Chad Durbin to be their: (circle the correct answer)

  • A) 5th Starter
  • B) 6th Starter
  • C) Mop-Up Reliever
  • D) Waste of Space
  • E) Who cares, we have Adam Eaton!?

Regardless of the answer you selected, this now gave the Phillies Chad Durbin and J.D. Durbin – two completely unrelated Durbins. Now, it isn’t as if we’re talking about two guys with the last name of Smith. I never knew “Durbin” was a last name until a couple of years ago and now there are not only two in major league baseball but two on the same team?
More interestingly enough, there have only been four Durbin’s in the history of major league baseball and the other two ended their careers during, or before, 1909. The only two Durbin’s in the last 98 seasons of major league baseball are now on the same team – and have no relation to one another.
The Phillies acquired J.D. Durbin after the Diamondbacks placed him on waivers in April. Durbin had appeared in one game for Arizona and surrendered 7 hits and 7 runs in 2/3 of an inning. For the Phillies, Durbin was somewhat serviceable, even throwing a complete game shutout against the Padres.
J.D. Durbin made his Phillies debut on June 29th during the first game of a double-header against the Mets.
At the time of acquiring J.D. Durbin, the Phillies had a minor league prospect with the name J.A. Happ. Due to rotation injuries, Happ made his first major league start on June 30th, against the Mets.
Now that would be odd enough, on its own, however the Phillies also acquired J.C. Romero from the Red Sox. Romero also made his Phillies debut on June 29th, during the second game of Durbin’s double-header.
So, to recap, not only did the Phillies have three pitchers with the first names of J.A., J.C., and J.D., but all three of them made their Phillies debuts within the span of 48 hours from June 29th-June 30th!
And, speaking of the Phillies, they acquired Tad Iguchi from the White Sox towards the end of the season. Since he would not have been able to play for the Phillies until May 15th, if he re-signed with them, he went elsewhere (Padres). The Phillies, in need of another bench player, decided to sign So Taguchi. I guess this way the transition will be easier for the players.
Or how about the Twins deciding to replace Luis Castillo with Alexi Casilla.

  • Believe it or not, the American League had an Ellis, an Ellison, and an Ellsbury.  And no, they were not Dale, Pervis, or Doughboy.
  • The Athletics had Dan Haren and Rich Harden.
  • The American League also had a Joakim, a Joaquin, and a Johan.  That’s never happened before with different players.
  • Lastly, there was the Rays’ Delmon Young and the Dodgers’ Delwyn Young, who sadly never got to face each other.

Speaking of “Young’s,” the NL West not only had two of them, but two Chris Young’s.  They could not be more different, either, as one is a 9-ft tall, white, former ivy-league pitcher and the other is a 6-ft, black, college-less outfielder.  Pitcher Chris Young (PCY for those keeping track) won the 2007 battle as his younger counterpart went 0-10, with a walk and 4 K’s against him.

  •  Orlando Hudson went 2-11, with an RBI and 4 BB, against his “River” counterpart Tim Hudson.
  • Unfortunately, Reggie Abercrombie never got to face Jesse Litsch.  I wonder what Sportscenter would call that matchup.  Reggie and Jesse?  Reggie and Litsch?  Abercrombie and Jesse?  Ugh, who knows…
  • Aaron Rowand and Robinson Cano didn’t face each other this past year either.
  • Somehow, the Blue Jays and Rockies have played nine times and we are still waiting on a Halladay/Holliday matchup.
  • Scott Baker didn’t pitch against, or to, Paul Bako in 2007, though my fingers are crossed for 2008.

Mike Lamb is 3-9 in his career against Adam Eaton (who isn’t?) as well as 1-7 off of Todd Coffey.
Coffey and Lamb usually don’t go well together, though, but Felix Pie is also 0-1 off of the caffeinated one.
Eaton has never gotten to face Pie yet.  I’d like to put a pie in Eaton’s face.  3 yrs and 24 mil worth of pies!
In what would probably cause the universe to crumble, I am patiently awaiting a Rick VandenHurk vs. Todd Van Benschoten matchup.  I’m feeling 2008 or 2009.
In the long-name department, Jarrod Saltalamacchia went 1-2 against Andy Sonnanstine.  Salty also went 0-2 against Mark Hendrickson.  He went 1-1 against Ryan Rowland-Smit, but Ryan had two last names to reach eleven letters and therefore had an unfair advantage.
Easily the most hypocritical name award goes to Angel Pagan.  You can figure that one out.  Did you know, though, that the National League had “Two Wise Men”?  That’s right – Matt and Dewayne.
Though Matt Wise surrendered a hit to Angel Pagan, he struck out Dewayne Wise, proving what we already knew – Matt Wise is the smartest pitcher ever.
On a sad note,  2007 proved to be a disappointment in the generic name field (not Nate Field or Josh Fields).  Combined, there were only four Smith’s.  Jason, Joe, Matt, and Seth.
Even sadder, we only had three Williams’ – Dave, Jerome, and Woody.  Scott Williamson tried his hardest but that does not count.  Could be a cool sitcom title – Three Williams and a Williamson.
Major League Baseball spanned the endpoints of the life cycle this year.  On one side we had Alan Embree (embryo) and Omar Infante (infant) and on the other there were Jermaine Dye (die) and Manny Corpas (corpse).
Dye has never faced Corpas but is 2-7 in his career off of Embree.  Infante has also never faced Corpas but has doubled in 4 at-bats against Embree.
Jorge de la Rosa and Eulogio de la Cruz did not face each other this year despite being the only two “of-the” names.  And, just to clarify the none of you who asked, Valerio de los Santos would not qualify for this category since de los would technically be “of-them” or “of-those.”
Miguel Cairo has long been the MVP of this group but he welcomed two additions this year in the forms of Ben Francisco and Frank Francisco.  I had always thought of Francisco as a Spanish first name but was very surprised to find it as an American last name.  In fact, if you say Ben Francisco really quickly and in front of a drunk, it could even sound like San Francisco.
I recently got an original NES and could not help but notice that two major leaguers sound like items from a Zelda game.  Don’t both of these sentences make sense?

  1. Link, to defeat Ganon, you must hit him in the lower Velandia.
  2. Use your Verlander to blow up the stones blocking the entrance.

One of my favorite movies is Sinbad’s Houseguest, and whenever I hear the name of Giants’ 2B Kevin Frandsen I am reminded of Sinbad’s character Kevin Franklin.  Something tells me Frandsen never impersonated a dentist.
In addition to everyone else we had six players with job names.  Chris Carpenter and Lee Gardner maintained the stadiums and fields, Scott Proctor made sure they didn’t cheat, Skip Schumaker supplied them all with cleats, while Matt Treanor helped rehab Torii Hunter.
Schumaker did not face Carpenter, Gardner, or Proctor.  Treanor is 1-3 off of Carpenter in his career.  Hunter was 3-6 with a HR and 2 RBI off of Carpenter (career), as well as 2-6 with an RBI off of Proctor.
Clearly, a Hunter is more valuable than a Proctor and a Carpenter.
Point blank – the following names sound incredibly made up and fake:

  • Frank Francisco
  • Dave Davidson
  • Emilio Bonifacio
  • Rocky Cherry

When primitive men first began to speak it was easiest to combine two words together without any intermediates.  Thousands of years later we still have names like Grady Sizemore, Jarrod Washburn, Mark Bellhorn, and Chris Bootcheck.
Speaking of Chris Bootcheck, I wonder what he and Jon Knotts would talk about.
In the anatomy field, Rick Ankiel and Brandon Backe were in the same division, with Ankiel going 0-3 with an RBI off Backe.

  • DIRTY NAME AWARD – Rich (Dick) Harden
  • ACADEMY AWARD – Sean Henn
  • LED ZEPPELIN AWARD – Scott Kazmir
  • FUTURE PIZZA SHOP NAME AWARD – Doug Mirabelli (hon. mention – Mike Piazza)
  • FICTIONAL SERIAL KILLER AWARD – Mike Myers (as usual)
  • NAME TYPO AWARD – Jhonny Peralta
  • MOST FUN TO SAY AWARD – Jonathan Albaladejo
  • IMPERVIOUS AWARD – (tie) James Shields and Scot Shields

And there you have it.  We covered the life cycle, the entertainment (regular and adult) industry, jobs, cities, the bible, and more.
We can only hope that 2008 will finally bring us a VandenHurk/Van Benschoten or a Holliday/Halladay.
Keep your fingers crossed.


Adjusted W-L: A Study of the Unlucky

If you have read any of my work on Starting Pitchers and SP Effectiveness it will come as no surprise that I strongly dislike Win-Loss records. 
In the 2005 season, Johan Santana posted the following numbers-

  • 16-7 actual W-L
  • 2.87 ERA
  • 7.02 IP/gm
  • 231.2 IP
  • 0.97 WHIP
  • 5.29 K:BB
  • 3 CG/2 SHO
  • 33 Games Started

In 2005, Bartolo Colon won the AL Cy Young Award.  Any idea of how many of the above categories, which we all intuitively equate to pitching effectiveness, Colon outranked Santana in? 
One.  One category.  Colon beat Santana in only one category in 2005.  Care to venture a guess to which it was?  Combine my sarcastic tone with the title/first line of this article if you need help.  That’s right.  The one category he outperformed Santana in was WINS, 21-16.  Santana outperformed Colon in every other statistical category in 2005 and somehow lost the Cy Young.  Not to take anything away from Colon’s season but he clearly did not perform better than Santana in any category other than wins and they had the same number of starts.  And to say that the Angels made the playoffs strictly because of Colon is just slightly over borderline ridiculous. 
For reasons unbeknownst to me, W-L has become an extremely significant barometer when measuring the quality of a season and of a career.  We invest a ton of stock into a statistic that paints us half of a whole portrait.  Ask yourself this – what does a W-L record tell us?
Does it provide a ratio of how often someone pitched well to how often he didn’t?  No, because a Win does not always equate to a well-pitched game and a loss does not always equate to a poorly-pitched game.
Does it take into account the fact that some teams score more than others?  No, because you get credited with a win if you last at least five innings and your team never relinquishes the lead once you leave.  It does not matter if you give up six runs in seven innings as long as you meet that above criteria.
A few weeks back I introduced my statistic, AQS – Adjusted Quality Start, which refers to when a pitcher either goes 6+ IP while surrendering 3 or less earned runs or 7.2+ IP while surrendering no more than 4 earned runs.  Using the AQS allows us to find the ratio, mentioned in the question above, of how often a pitcher performed well in comparison to not performing well.  Regardless of whether or not you received the deserved decision, or whether or not you even received a decision, if you meet the criteria of an AQS it means you pitched well and, in theory, deserve to win.
Springboarding off of the AQS, I began to separate W-L records into what they really were – a combination of Cheap Wins, Tough Losses, Legitimate Wins, and Legitimate Losses.  The legitimate decisions refer to games that a pitcher either recorded an AQS, and won, or did not record an AQS and lost.  The reverse can be said for the Cheap Wins/Tough Losses.  Failing to record an AQS and getting a win really should not happen and the same can be said for garnering a loss while recording an AQS.
I will use the 2007 season of John Smoltz to put this to use.  By all accounts he had a great year but he often gets lost in the Peavy/Webb shuffle when discussing the best in the NL this past season.  Peavy won 19 games, Webb won 18, and Smoltz only won 14.  Something deep down tells us that Smoltz had a better season than his 14-8 record would indicate, but how much better?
Looking more closely at his 14-8, we see that he had 0 Cheap Wins, 5 Tough Losses, 14 Legit Wins, and 3 Legit Losses.
If we take the Cheapies and Toughies out, Smoltz is left with a 14-3 record of legitimate decisions.  I want to go a bit further, though, because he recorded 22 decisions no matter how we look at it.  He legitimately deserved to go 14-3, but there were five games he lost that he pitched well enough to win.
With that in mind, I began to adjust the W-L records of pitchers and see what would happen if they were credited with a Win for every Tough Loss and a Loss for every Cheap Win, on top of the Legit Wins and Legit Losses.
When we apply that to Smoltz, his 2007 Adjusted W-L would be 19-3.  When we do the same to Peavy and Webb we get a 21-4 record for Peavy and a 20-8 record for Webb.
Essentially, Smoltz should have won 19 of his 22 decisions, Peavy should have won 21 of his 25 decisions, and Webb should have won 20 of his 28 decisions. 
If we are going to use W-L record as a barometer of quality, then we should use this Adjusted W-L instead since it actually does give us the ratio of how many times a pitcher performed well relative to the decisions he received.
Below is a table featuring the Actual W-L records and the Adjusted W-L records of some NL pitchers from 2007.





Jake Peavy




John Smoltz




Cole Hamels




Brad Penny




Tim Hudson




Ted Lilly




Matt Cain




Ian Snell




Dontrelle Willis




Adam Eaton




As we can see, Brad Penny had the best Adjusted W-L of any NL pitcher as he truly deserved to lose only one of his decisions.  If he received proper run support and was a bit luckier in the games he recorded decisions, he would have posted a 19-1 record.  I wonder if it would have been a different Cy Young picture if he did. 
Look at the cases of Matt Cain, Dontrelle Willis, and Adam Eaton.  Cain finished the season with an actual W-L of 7-16, even though he deserved to go 16-7.  That means he was unlucky nine times.  Dontrelle Willis should have been 15-10 even though he ended up 10-15, meaning he was unlucky five times.  Yes, by all accounts Dontrelle had a down season, but he did really deserve to win 15 of his decisions. It was just how bad his 10 deserved losses and no-decisions were that turned his season upside down.
On the flip-side, Adam Eaton finished the season 10-10, even though he deserved to be 6-14.  While Cain and Willis were very unlucky, Eaton turned out to be lucky four times.
When we look at the number of Cheap Wins and Tough Losses, we can subtract the difference, express it as a + or – number and detail which pitchers were the luckiest and unluckiest.  This is a bit different than the Pythagorean Formulas used to determine what a team’s record should be.  The team formulas look at the season, as a whole, and provide estimates as to what an overall record should be based on how many overall runs are scored and given up.
It does not make sense to use that here, because if a pitcher gives up 10 runs in Game 1, and 1 Run in Game 2, the average would come out to two bad starts, even though the starts are completely separate and the damage was done in one game.  The team formulas evaluate the entire forest without looking at each individual tree.
Looking at each individual tree needs to be done to really show which pitchers were luckiest and unluckiest.
In the case of Cain, he had 0 Cheap Wins and 9 Tough Losses.  Net Luck = 0 – 9, meaning that Cain had a Net Luck Rating of -9, or in other words was very unlucky.  There were no recorded Wins that he should have lost but there were nine recorded losses he should have won, or at least not recorded a loss.
Adam Eaton had 5 Cheap Wins and 1 Tough Loss.  5 – 1 = 4.  Eaton’s Net Luck was +4, meaning he was lucky four times.  Positive numbers correspond to being lucky, negative numbers correspond to being unlucky, and 0 corresponds to receiving exactly what you should have received.
Aaron Harang was 16-6 with 0 Cheap Wins and 0 Tough Losses.  He had a great season and deserved to go 16-6 in his decisions.  He would have a Net Luck Rating of 0, since he was not lucky or unlucky.
When pitchers tie in either luck or lack of luck the statistic we should look to is AQS %, which refers to the percentage of times a pitcher recorded an AQS.  With lucky pitchers, a lower AQS % tells us they pitched well less, and so they are luckiest because they recorded the most amount of Net Luck while pitching well the least amount of time.  For unlucky pitchers we look at the highest percentage because it tells us that the pitcher was not only unlucky enough to lose games he should have won but that he also pitched well a higher percentage of times.
For instance, Scott Olsen, Adam Eaton, and Byung-Hyun Kim all tied with a +4 Net Luck Rating, meaning they were the luckiest NL pitchers.  Olsen had an AQS % of 33.3, Kim at 27.3, and Eaton at 26.7.  Therefore, Adam Eaton was the luckiest NL pitcher because he received four positive decisions that were unmerited and pitched well the least amount of time.
Though Cain, Bronson Arroyo, and Derek Lowe all ranked higher than Dontrelle and Smoltz, the latter two finished at -5.  Dontrelle had an AQS % of 57.1 and Smoltz at 84.4 %.  Therefore, Smoltz was unluckier than Willis because he received five negative decisions that were unmerited and pitched well way more often.
When we apply Net Luck to every pitcher in 2007, in both the NL and AL, we get the following results –

  • Luckiest NL SP = Adam Eaton (PHI), +4
  • Luckiest AL SP = Odalis Perez (KC), +4
  • Unluckiest NL SP = Matt Cain (SF), -9
  • Unluckiest AL SP = Dan Haren (OAK), -6

Though Haren pitched well and still finished 15-9, he should have been 21-3.  Odalis Perez actually tied Felix Hernandez of the Mariners at +4, but Hernandez’ AQS % was 57.1 whereas Perez came in at 30.8.
Honorable Mentions for Luck in 2007 go to:

  • Scott Olsen, +4
  • Byung-Hyun Kim, +4
  • Paul Byrd, +3
  • Boof Bonser, +3
  • Jeremy Bonderman, +3

Honorable Unlucky Mentions in 2007 go to:

  • Bronson Arroyo, -7
  • Derek Lowe, -6
  • John Smoltz, -5
  • Mark Buehrle, -5
  • Gil Meche, -5
  • Dontrelle Willis, -5

Though I do not have all of the data compiled right now, something I am going to investigate over the next few weeks are which pitchers, from 2000-2007, have been the luckiest and unluckiest.
Another usage of Net Luck that fascinates me, and that I am currently researching for my book, involves an application to 300 game-winners, as well as those who are close.  Something tells me that I will find some guys with 300 wins who maybe should not have 300 wins, as well as some guys who are short of 300 that really should have it.  After all, if we are going to use 300 wins as a Hall of Fame barometer, we should at least make sure the wins are deserved.
I am currently involved in conducting this research and if anyone would like to help, please get in touch with me.

2007 NL Starting Pitching Analysis

When it comes to analyzing and comparing pitchers, those conducting the comparisons will often find themselves in a tricky situation.  Sure, certain pitchers are better than others, but what are they specifically better at? 

How can we conduct an honest analysis when there are so many variables to consider?  And how can we truly determine which pitchers were better than others when some are on terrible teams with no run support and others are on tremendous teams with tons of run support?
The first step is to determine what we are measuring.  If we want to know who the best strikeout pitcher is, we should look at the raw total for strikeouts and also an average of K/IP, since some guys will make less starts than others.  To figure out who walks the least, we measure the number of walks each pitcher gives up and a walk-IP ratio.
These measurements are contingent on one category, though, and cannot tell us who is better or more effective than the rest.  All of the research and ideas presented in this article are designed to measure the “effectiveness” of a pitcher. 
In order to determine this effectiveness, a whole heck of a lot of numbers need to be measured and properly weighted/scaled so that everybody has a fair shot – whether or not they are on a great team.
I took the 1-3 best pitchers from each National League team and entered their statistics into a database, measuring everything from their raw Innings Pitched totals to their Adjusted Quality Start % (you’ll read more on that below).  After entering all of the statistics, and crunching numbers until my brain turned to mush, I came up with my weighted points system.  I assigned the corresponding point totals and added everything up to determine what I feel is a very accurate measurement of pitching effectiveness amongst the NL’s best. 
This was not applied to every single NL Pitcher in 2007 (I will do that another time) but rather amongst these 30 selected #1, #2, or #3 starters.  For instance, a guy like Jeff Suppan may have been more effective than Jason Bergmann but I wanted to have at least one person from each team.
The system is not 100% perfect and does not take into account every single statistic (do you know how many statistics there are??), but it definitely levels the playing field between those on good or bad teams, those injured/called up or just plain bad, and those who got lucky or unlucky with run support.  The points are assigned based on the areas I, as an intense student of the game, feel are most important to determine true effectiveness. 
The basic idea of this system is to measure the true quality of a pitcher over his season – IE, what would happen if a pitcher was rewarded every time he pitched well and discredited every time he pitched poorly – something that happens perfectly just about 0% of the time. 
We will begin by going over the statistics involved, what their points scale was, and why they are used.  The idea behind these corresponding point totals is to properly weight the areas in which most people intuitively attribute to success and quality.
The points given to each statistical subset are designed to separate the aces from the workhorses and the workhorses from the seemingly replacement level pitchers.  They may seem arbitrary and could be replaced with different numbers, or fractions/decimals, however the difference between the points in subsets was based on the amount of pitchers who fall into certain categories.
In order to be as effective as possible, a pitcher needs to make as many starts as he can.  How can we say that a pitcher with 14 starts is more effective than one with 34-35, even if his numbers in those 14 starts are tremendous and the numbers of the one with 34-35 are a bit worse?  His numbers may be better than the pitcher with 35 starts, however the latter pitcher was involved in 21 more games and proved to be durable enough to pitch an entire season, and solid enough to maintain his SP status for 162 games. 
This does not mean that a pitcher with 35 starts is necessarily “better” than one with 14-16, but rather he is more effective because he is involved in more of his team’s season. 
If the pitcher with 14-16 starts posted the same numbers in 32 starts, it would not be a contest.  But, he didn’t – it was only 14-16.  You cannot have as much of an effect on your team (actual play, not motivational or anything) unless you are out there as often as possible.
***What the end result of this effectiveness points system showed is that those with average numbers, over 30+ starts, were equally as effective, or slightly better/worse, than those with good numbers over 16-20 starts.***
If somebody makes only 14 starts in a season, it could be because he was injured for half of the season or was called up from the minors during the season, so he should not be penalized with negative points for that – he just should not be rewarded as highly as someone with 30+ starts.

  • if over 30 starts, +5
  • if 25-29 starts, +3
  • if 20-24 starts, +2
  • if under 20 starts, 0

Just like Games Started, IP can only get you positive numbers, because the low raw number of IP can be attributed to injury or a midseason call-up.  Those with more IP get higher point totals, though.  The reason for 0 points for under 100 innings is because you were not necessarily a bad pitcher, but the lack of innings (whether due to injury or a call-up) limits the effectiveness.

  • if 230+, +8
  • if 220-229, +7
  • if 200-219, +5
  • if 150-199, +3
  • if 100-149, +2
  • if under 100, +1

This is where negative numbers can begin.  If you were hurt, or called up from the minors, you are not penalized with negatives for the raw number of innings pitched or games started, but if you posted a high number of starts and low number of innings, this statistic will bite you in the rear.  IP/Game separates the hurt or called up from the downright below average or bad.  It also helps reward those with a couple less starts than others but with more raw innings pitched.  These types of pitchers were in the same GS range but some went deeper into games than others.  Nobody averaged over 7 IP/gm, so we start lower.

  • if 6.5-7 IP/gm, +7
  • if 6.0-6.49 IP/gm, +5
  • if 5.5-6 IP/gm, +3
  • if 5.0-5.5 IP/gm, 0
  • if below 5.0 IP/gm, -5

If you cannot average over 5 innings per game, or exactly 5 innings per game, you should not be a starting pitcher.  Even Adam Eaton averaged over 5 IP/gm in 2007.
Quality Starts can be an inaccurate statistic because it takes into account games in which a pitcher goes 6+ innings and gives up no more than 3 earned runs… and nothing else.
If a pitcher goes 8.1 innings and gives up 4 runs, it is arguably the same ratio and an equal game in terms of quality, but does not get counted as a quality start.
With that in mind, I came up with the stat of Adjusted Quality Starts, which takes into account all regular quality starts as well as games in which someone goes 7.2-9 innings and gives up no more than 4 runs.  This measures the true number of games in which a pitcher had a good-great performance.
***If you wonder why it is 7.2 IP, instead of 8, the number was derived from the amount of times a pitcher was lifted after 7.2 IP for a specialist, or other sort of reliever, and from the sheer low average of innings pitched/game by a starter this year.  Reaching the 7th inning is now a great feat, let alone coming within one out of finishing the 8th.  Though the previous ratio for a QS was 2:1, due to the data mentioned above, going an extra 1.2 IP to get to 7.2 IP merits being able to give up one more run.***
I used the percentage of AQS to the total number of Games Started to measure effectiveness in this area.  Someone over 75% almost always pitches a good-great game, whereas someone under 50% only pitches a good game less than half of the time – not very effective.

  • if AQS % is above 75%, +5
  • if AQS % is 67-74%, +3
  • if AQS % is 50-66%, 0
  • if AQS % is below 50%, -3

If you’re keeping score at home, AQS= 6+IP with ER =< 3, AND, 7.2+IP with ER =< 4, where =< is the blog version of greater than/less than or equal to. 
In addition to AQS, something that needs to be taken into account is how often a pitcher went for a complete game, since they are so rare.  We also need to take into account a shutout, since they occur even less. 

  • For every CG, +2
  • For every SHO, additional +1

***NOTE: Aaron Harang had two games in 2007, one where he went 9 IP, and one where he went 10 IP, when he did not get a decision.  Even so, I am counting these 2 as a combined 1 CG, since he went 9+ innings.***
W-L Records are the most deceiving statistics because they do not take into account the true quality of the games pitched.  Just because a pitcher goes 14-7 does not mean he was necessarily a great pitcher.  He could have pitched terribly and had great run support in 10 of 14 wins, but brilliantly with terrible run support in the 7 losses.
The whole point of the adjusted W-L records is to get an AQS, since that means you pitched well and should be rewarded, even if your team (offense or bullpen) does not help you. 
After all, Ian Snell cannot control the Pirates’ offense.  It is not his fault that 4 of his 12 losses were “Tough Losses” and all 11 of his No-Decisions were games in which he pitched brilliantly and had an AQS, yet he received little to no offense to help garner him a ‘W’.
With that in mind, I changed W-L to the following 5 stats:

  • Cheap Wins: wins in which one does not get an AQS (-1)
  • Tough Losses: losses in which one does get an AQS (+2)
  • Legit Wins: wins in which one does get an AQS (+2)
  • Legit Losses: losses in which one does not get an AQS (-2)
  • ND-AQS: no-decisions in which one gets an AQS (+1)

I received some questions for how these numbers came to be, and to keep it simple, the statistics that actually have an effect on the W-L record are valued higher (negatively and positively) than the statistics like ND-AQS, which prevent a pitcher from winning but do not hurt him with a loss.
ND-non AQS is not used here for the same reason that Cheap Wins is only negative one, which is that not every Cheap Win or ND-non AQS was a terrible start.  A large bulk of them were games in which a pitcher had a good outing but only went 5 or 5.1 innings.   Cheap Wins loses you a point (not two, only one) because you do not get an AQS but it does effect your win-loss record.  ND-non AQS means you do not get an AQS but it does not effect your win-loss record, which is why I decided to just leave it out.
Though I am not too fond of this statistic and originally tinkered around with separately evaluating H/IP and BB/IP, using WHIP just seemed to make things easier.  Though it does not tell us which pitchers walk less and give up more hits, or vice versa, or tell us how many “empty innings” a pitcher had (innings where no baserunners got on), it does provide a valid average of baserunners to expect in a given game since it does not equate to a per-9 inning scale.

  • if WHIP 1.00-1.15, +3
  • if WHIP 1.16-1.25, +2
  • if WHIP 1.26-1.30, +1
  • if WHIP 1.31-1.40, 0
  • if WHIP above 1.40, -2

Instead of using K’s, I wanted to use the ratio of strikeouts to walks, since not every pitcher is a strikeout pitcher.  Even so, you do not have to be a strikeout pitcher to be an accurate one, and because of this I rewarded those with high K:BB ratios.  Greg Maddux only struck out 104 in 34 starts, but only walked 25 – a K:BB of 4.16.  This meant that Maddux kept more runners off-base by striking them out and not walking them.

  • if K:BB above 4, +7
  • if K:BB above 3, +5
  • if K:BB above 2, +3
  • if K:BB above 1, 0
  • if K:BB 1 or below, -3

Now that we have the points, let’s test it out and put it to use.  We will use Ian Snell and Carlos Zambrano.
The table below shows Ian Snell’s 2007 numbers and points he receives for each in my points system.

Starts 32 +5
Innings 208.0 +5
Cheap W 0 0
Tough L 4 +8
Legit W 9 +18
Legit L 8 -16
ND-AQS 11 +11
AQS % 75% +5
IP/Game 6.52 +7
WHIP 1.33 0
K:BB 2.60 +3
CG 1 +2
SHO 0 0

When we add up all eleven of these numbers, we get Snell’s Effectiveness #, which comes to: +48.
Now, let’s look at Carlos Zambrano’s season numbers in the table below and add his point totals up.

Starts 34 +5
Innings 216.1 +5
Cheap W 0 0
Tough L 2 +4
Legit W 18 +36
Legit L 11 -22
ND-AQS 0 0
AQS % 53% 0
IP/Game 6.36 +5
WHIP 1.34 0
K:BB 1.75 0
CG 1 +2
SHO 0 0

We look at his numbers and add up the totals to get his Effectiveness #: +35.
Zambrano had more legit wins but also more legit losses, and of Zambrano’s 3 no-decisions, none were ND-AQS, whereas of Snell’s 11 no-decisions, all were ND-AQS. 
That tells us that if each player got a win for every game he pitched well, and a loss for every game he did not pitch well (did not get an AQS), and the only no-decisions they received came from no-decisions that they pitched poorly in or did not go a full 6 IP, their records would look like this –

  • Carlos Zambrano (18-13) would actually be 20-11
  • Ian Snell (9-12) would actually be 24-8

Snell went further into his games, had a better K:BB ratio, and had that higher AQS %.  It also tells us that of Snell’s 32 starts, 24 of them were of great quality, whereas Zambrano had 18 good-great starts and 16 average-bad starts.
This essentially tells us that while Zambrano’s good-great starts may have been better than Snell’s good-great starts, when Zambrano had his bad starts, Snell was still having good-great ones.
As mentioned before, I used this points system to evaluate 30 National League pitchers.  I compiled a group of spreadsheets, ranking the pitchers in order in different categories to show that certain stats we rely on do a bad job of proving effectiveness.
To view all of my results, click on the links below.  You can use this data in other areas, but please credit my work.

  • To see the list of pitchers and their statistics used to assign points, click here.
  • To see the list of pitchers in order of effectiveness points, click here.

I do not want to post a ridiculously long table on this article, so you will need to look at the linked files to see the results, but I will list the top 15 pitchers and their effectiveness points.

  1. Jake Peavy, +74
  2. Aaron Harang, +69
  3. John Smoltz, +69
  4. Brandon Webb, +67
  5. Cole Hamels, +65
  6. Brad Penny, +64
  7. Tim Hudson, +63
  8. Ted Lilly, +60
  9. Matt Cain, +52
  10. Roy Oswalt, +50
  11. Ian Snell, +48
  12. Bronson Arroyo, +47
  13. Derek Lowe, +47
  14. Greg Maddux, +45
  15. Adam Wainwright, +45
  16. Jeff Francis, +45

And, again, these points were assigned to statistics based on how important they corrolate to effectiveness.  The points system essentially covers the statistics and averages from all angles.
The most shocking part of this was how low Chris Young of the Padres came out.  Young went 9-8, with a 3.12 ERA, in 30 starts.  He should have been more effective, I thought, based on those numbers.  After looking at his game logs, though, I changed my mind and realized it made sense.
Of his 30 starts, he was essentially two different people.  In the 19 starts in which he went for 6+ innings, he was 9-1 with a 1.64 ERA, averaging 6.6 IP/gm, with a 0.85 WHIP and 129 K’s in 126.1 innings.
In the other 11 starts, he was 0-7, with a 7.14 ERA, only going 4.2 IP/gm, with a 1.76 WHIP, and 38 K to his 36 BB, in 46.2 innings.
After analyzing his situation and the points system I realized that my effectiveness model favors consistency and lower standard deviations (the average of how far someone strays from his average).  To me, that truly defines effectiveness.
I would much rather have a guy who I knew would amass an AQS 67% or more of the time than a guy who might strikeout 20 batters and pitch a two-hitter in one game, but give up 5 runs in 6 innings for the next three, before again pitching a brilliant game.
As long as the consistency is of a good nature, consistency in this model proves effectiveness.
I know, we’re finally at the end of the article, right?  I apologize for the length but it took this long to get everything across. 
Looking at Jake Peavy, the most effective NL pitcher at +74, we see that the only counted statistic in which he led was AQS.  Peavy had the most good-great starts of any NL pitcher.  While he may not have led in IP, IP/gm, K:BB ratio, or least losses (Brad Penny only had 1 legit loss), he led in consistency and being consistently good-great.
These results also show that Cole Hamels, with 6 more starts that he missed due to injury, would likely challenge Peavy for #1 in effectiveness – however, as my model dictates, the fact that he missed those 6 starts and Peavy did not shows that Peavy was more effective.
Yes, there were more stats we could add to this, and more variables to account for, but I feel this accurately levels the field of play between pitchers in distinctly different playing situations, and levels the difference between 2007 reputation and 2007 actual performance.
I must remind you before I come to a close, though, that this is only a measure of effectiveness, not the end-all solution to determining who the “best” pitchers are.
However, for this Sabermetrician, effectiveness directly corrolates with quality and value.