tangotiger
Interestingly, if you use my suggestion, and look at ALL pitchers to figure out the maximum boundary, you'll get much higher totals (thanks to Niekro, Moyer, et al). Now the max will be more like 220 wins at age 34.

Anyway, if you do use the min/max uniform technique, then being 181 wins away means you have a 20% chance of getting to 300 wins.

That matches what Bill and John have basically been saying.

Of course, if you make the min/max as 22/220, then the average is 121 wins. And we know the average can't really be 121 wins (in between Maddux and Glavine, and we can presume they are not pitchers who have an "average" career path after age 33). So, using that technique means you can't use a uniform distribution.

The reality is that if the average is closer to 90-100 wins than it is to 121 wins, and even if you keep the top-end at 220 wins, you'll have to reign enough players toward the center. You have no choice but to bring it down below 20%.

So, 10% seems to be the plausible maximum expectation if you want to build a model. And closer to 5% for a more reasonable model.


3:12 PM Nov 28th

tangotiger
1. I calculated each pitcher's age as season minus birth year.

2. I took the top 20 pitchers in RA per 9 innings, relative to league, at age 30-33, for pitchers born between 1921 (Spahn) and 1971 (Pedro).

3. I then calculated number of wins from age 34 to end of career. These are the results:

Wins playerID
199 johnsra05
197 spahnwa01
172 clemero02
134 maddugr01
118 glavito02
117 schilcu01
108 seaveto01
106 mussimi01
104 gibsobo01
85 leiteal01
78 fordwh01
72 brownke01
58 coneda01
53 palmeji01
45 stewada01
37 martipe02
35 keyji01
29 scottmi03
25 rogerst01
22 tudorjo01

Given the relatively small number of data points, that actually follows very closely to just a straight line. Indeed, the correlation of those points to a simple straight line is r=0.97.

So, yes, it does not follow a normal distribution, but rather a uniform distribution.

Giving Cliff Lee a 20% chance of getting 181 wins seems on the very optimistic side.

If you try to simulate Cliff Lee's rest of career, you'll be hard-pressed to get him at least 181 wins 10% of the time. My sims give him 5%.

It is possible that a pitcher can remain unusually healthy in an aytypical fashion that allows him to get into a boom-or-bust mode (RJ, Spahn, Clemens being a huge jump from the rest of the gang). That however would have to be demonstrated first.

9:03 AM Nov 28th

bjames
The Favorite Toy would not work for making estimates of this nature, and the system that IS used for these estimates is as different from that as could be. I have Cliff Lee at 20%. . .you want him at 24%? Is that right? There is obviously no way to make distinctions that are that fine, given that we're dealing with the intersection of two data sets--1) Pitchers who win 300 games, and 2) Pitchers who are similar to Cliff Lee.
6:07 PM Nov 27th

tangotiger
Right, it would be a median of 124 wins. But, at that point, we are expecting a fairly normal distribution, so I said average, which is the same thing. But, yes, median is the correct term.
12:14 AM Nov 24th

jedlovec3
I agree with Tangotiger about being careful when rounding ages.

To nitpick one thing: "To have a 50% chance at winning 300 if you have 176 wins means that you are forecasted for an average of 124 wins. "

Technically, a 50 percent chance at winning 300 games means you are forecasted for a MEDIAN of 124 wins, no? The difference is usually irrelevant, since most distributions are close enough to the normal distribution and the median is close to the average. But, sometimes it does make a difference.

As far as the validity of the system and age adjustments, I'll leave that to Bill.
9:05 AM Nov 23rd

tangotiger
The favorite toy would treat the 0.8 difference in birth years as close to 0.5 service years remaining.

If you have an estimate of 15 wins, then that's 7.5 wins that affects the total. If you are short some 120 wins, that affects the probability by 6 percentage points.

So, that's part of an explanation as to the actual magnitude. If your point is that it's six, schmix, then fine.

My point is the difference between bad math and good math. If your point is that it's math, schmath, then fine.
3:45 PM Nov 22nd

tangotiger
b-r.com uses the Bill James "seasonal age".

My point is that the actual difference in age between CC and Doc is a bit over three years.

Bad math says to first convert each person's age into an integer (30 and 34 in this case), and then subtract the two integers.

Correct math says to use the actual date of birth, and subtract the two ages, and report the actual difference, which is 3.2 years apart in this case.

Given that the entirety of the discussion rests on the gap in their ages in return for the 12-win headstart for Doc, then it makes a big difference if we treat the difference in their age as 4 or as 3.2.

2:34 PM Nov 22nd

tangotiger
The only way it makes sense that someone who is a bit more than three years older (please, don't round to an integer first and then subtract... that's just bad math), and with just a 12 win lead can have the same chance as the other guy to reach 300 wins is if he's much better than the other guy.

Let's use the Favorite Toy, and work our way backwards. To have a 50% chance at winning 300, if you have 188 wins means that you are forecasted for an average of 112 wins.

To have a 50% chance at winning 300 if you have 176 wins means that you are forecasted for an average of 124 wins.

Let's give Halladay 7 remaining years, and CC 9 remaining years. That means Doc is going to average 112/7= 16 wins a year and CC will average 13.8.

I suppose it's possible that Doc is really much better than CC (notwithstanding NYY v PHI offense support). But, it sure seems hard to believe that Doc can average 16 wins a year for 7 years.

I showed that the best pitchers in history averaged 13 wins a year for 7 years. You can push it to 14, I doubt you can go to 15, and 16 is really really pushing it unreasonably.

Anyway, without the benefit of seeing the system, as well as the testing of the system, it's hard to say more.
8:49 AM Nov 22nd

glkanter
If it's something counter-intuitive, I don't see it.

They both win in the neighborhood of 20 games a year, year after year.

The two pitchers are the 4th most similar for each other.

CC's most similar list at age 30 beats the heck out of Halladay's most similars at age 34 regarding 300 win seasons, guys that came close, and longevity.

CC has 5 years plus a vesting year with the Yankees. That's a team that will give him ample win opportunities all 6 years.

Halladay has 2 years plus a vesting year with the Phils.That's a team that will give him ample win opportunities all 3 years. But not as 'certainly' as the Yankees.

It seems to me the only way the two projections wouldn't have CC with an advantage in getting to 300 is if his projected remaining years were fewer that Halladay's. He's missed starts due to a spring training groin injury, one season.

I don't get it.
8:02 AM Nov 22nd

glkanter
According to b-r.com, CC is 65 wins ahead of Halladay at age 30, 176 - 111.
10:38 PM Nov 21st

jedlovec3
To answer a few questions posed here:

- These numbers are not typos or miscalculations. As with everything in the Bill James Handbook, these were verified multiple times by Baseball Info Solutions staff before sending the book to the printer.

- This 300 Win predictor does NOT use the Favorite Toy formula. Bill developed a separate formula specifically for this purpose.

- In this example, Bill's formula considered the age difference between Halladay and Sabathia roughly as significant as the difference in career wins to date; hence the similar probabilities for 300 wins.

- Keep in mind that pitchers do not usually age like hitters do. Hitters have a nice improvement phase followed by a steady decline phase. Such aging trends are much harder to follow with pitchers. As a result, age is typically a much smaller factor in projecting future pitching performance.

Ben Jedlovec
Baseball Info Solutions
6:13 PM Nov 21st

tangotiger
I made some changes to the sim to try to string more good seasons together. This keeps the overall average at 90 wins for rest-of-career, but it widens the extremes. The best I could do is get it to 6% chance of at least 181 wins.

However, in so doing, I also increase the chance of the 125+ wins rest-of-career. And, it ends up much higher than the empirical.

My best guess is that the chance that Cliff Lee gets at least 181 wins (and finish with at least 300 wins) is under 5%. His chance at 250 wins is 20%-25%. 20% is what I get from the empirical data, and 25% is what I get from the simulator.

The favorite toy sets the odds for Cliff Lee at 7% for 250 wins.
2:52 PM Nov 18th

taosjohn
Maybe this is too simpleminded an analysis-- but Hallday has 12 more wins than Sabathia. 12 is 4% of 300.

So it looks to me like Sabathia's age is giving him a 3% advantage here...

And while I'm being simpleminded-- Early Wynn is a guy who cut it about as close as you can and still make 300, is he not? He won 156 after age 32.

Randy Johnson won 191 after age 32 to reach 303; but he had to pitch at really really obscene levels for 6 years AND pitch into his 45th year to do it. Seems to me Lee could be excellent for a long career and not get there...
11:57 PM Nov 17th

tangotiger
Cliff Lee, through his age 32 season, has 119 wins. Among all pitchers through their age 32 season, he ranks #207 in wins.

Ideally, we'd look for more comps, like guys who were great in their last 3-4 seasons.

Scanning the list of pitchers real quick, you get names like non-300 winners Luis Tiant, Orel Hershiser, Curt Schilling, Kevin Brown, Ron Guidry, Tommy John, David Cone, Dennis Martinez.... and Randy Johnson. My guess is that if you spent more time looking into it, and were more methodical, that you'll find it's probably closer to 10% (at best), that a great pitcher will get at least 181 wins after his age 32 season, after pitching great for the previous 3-4 seasons.

Just a guess.
9:16 AM Nov 17th

rgregory1956
My guess is that Halliday's percent probability is either a typo or simple miscalculation, plugging in some wrong numbers somewhere in the formula. There is a website that has Bill's Favorite Toy, that one can punch the numbers into, and will calculate the results for you. So I did with C.C. and Roy. C.C. comes out at 45% and Halliday at 25%. I'd assume that, in the rush to get the book out, the proof-readers didn't use due diligence.
8:15 AM Nov 17th

Steven Goldleaf
If we were betting, wouldn't you take the 30 year old with 176 wins to finish ahead of the 34 year old with 188? I would.
2:16 AM Nov 17th

chrisnickell
Trailbzr,

That would be interesting but I'm not saying it is necessary. Actually, I don't mean to sound like I'm backtracking or anything but I am not meaning to be critical at all here. My assumption is that this is based on Bill's old Favorite Toy method for assigning percentage values to future events. I don't think this has ever been meant to be super-accurate. It is more of a formula based opinion I think. And that has value - formulas aren't distracted by some of the things we are as people but in this case what you include in the formula is still just opinion.

I'm wondering about the backtesting mostly because it seems pretty simple to do. Something like this - run the numbers for 1960, 1970 and 1980. Assign points based on the predicted percentage versus actual results. Either only count the people who crossed 300 as positive or assign partial values - either method could be interesting. Then tweak the formula - consider the player's most recent year as 5 times as important instead of 2 times as important for example - and see what happens to the scores. This seems really easy to do - just a spreadsheet and the numbers. I'm sure Bill did something like this while working out his formula in the first place. I'm mostly wondering if anyone ever tested it independently in this way.

For my part, I like articles like this. It doesn't answer all the questions but I enjoy that it raises them in my own mind. And I like the discussion it creates. And I'll admit - I continue to be surprised that 300 winners are not actually dying out. It seems so unlikely that they would continue to happen with the changes in the game but they do.

Thanks,
Chris
6:07 PM Nov 16th

chrisnickell
Trailbzr, thanks, I guess not. I wonder if this is an error in the book or there is something else in the formula at work.

What is funny to me is that when I read the article another item in that chart stood out to me. If Verlander won 69 games in two years - 34.5 wins each year - he'd have the same totals as CC. No matter what the formula is now, doesn't it seem like that should mean there is a bigger spread between the two of them percentage-wise? Obviously he is not going to average 34.5 wins a season but if he did wouldn't you think his likelihood of reaching 300 would climb by more than 17%? Maybe not, just feels wrong.

Does anyone know if the formula they are using has undergone any real back-testing? Tweaking it and seeing what changes might have made it more accurate in the past? I'm totally speaking from ignorance here - someone may have done this - I'm really asking.

Thanks,
Chris
5:35 PM Nov 16th

chrisnickell
Not looking at the handbook but going from memory - I'm pretty sure this method uses recent performance also - not just the columns shown in the article. So if Halladay has more wins in the last couple of years he is projected to win more going forward. That is - career wins matter because they affect how much is left to accomplish but momentum and age deal with how much they'll win going forward.

Chris
3:32 PM Nov 16th

DaveFleming
Yeah...that was my thought, too. Just checking their nearest comparables:

Halladay's winningest comparables are Hubbell, Mussina, Pettitte, and Bunning...no 300-game winners in his lot.

C&C Music Factory has three 300-game winners among his ten comparables: Clemens, Maddux, and Seaver.

I would've thunk that Sabathia's three years on Halladay (it's three, not four) would give him a slight edge at reaching 300.
12:04 PM Nov 16th