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Monday, August 18, 2008

What Does Xavier Nady’s Fluke Season Tell Us?

The Yankees still have a long hill to climb if they're going to be in the playoffs this season, but that's not Xavier Nady's fault. Since being acquired from Pittsburgh on July 25, Nady has been killing the ball, with a line of .312/.391/649 as a Yank, with 7 HRs in only 77 AB. Nady has an OPS+ of 145 overall this season including his time in Pittsburgh, after never breaking 107.

Nady is 29, which means he's past the point where gains are typically made, but that doesn't mean that he hasn't improved. He's likely not as good as he appears to be right now, but there's a very good chance that he'll be better in 2009 than he has been in every season other than 2008

Nady's performance to this point got me thinking about fluke seasons and if they have any predictive value. So, I pulled up my Lahman database and started messing around with it to see if there was anything I could put together that would help me answer my question.

After fiddling around with a few different things, I came up with an approach that made sense to me.

1. I did very basic Marcel-like retroactive projections back through 1978. I used a 3/2/1 weight for seasons N, N-1, N-2 (where N is the current year). I did not do any projecting of the first two years of any player's career, and I did not include any MLEs or park factors. I then added in 500 league average plate appearances from the season in question to regress towards the mean and factored in aging for the component stats as well.

2. When that was done, I compared the projections for every season and player to what they actually did. If a player exceeded his projection by a certain amount, I considered that a fluke season.

3. I then calculated two separate projections going forward (N + 1) from every fluke season. One using the actual fluke season data, and one used the projection entering the fluke season instead. Those two projections were then compared to the actual performance in year N+1.

4. For the comparisons, I used wOBA (weighted on base average), which is basically the rate version of linear weights, scaled to OBP. So, a wOBA of .300 is bad, a wOBA of .330 is around average, .400 is great, etc., wOBA is easily converted to runs using the formula PA x wOBA / 1.15.

5. I set my cut off for a fluke season at a wOBA 15% better than projected. I also eliminated any seasons of fewer than 300 plate appearances. Why 15%? Because according to this post at The Book blog, the standard deviation for wOBA is SQRT(wOBA*(1.1-wOBA)/PA). So looking at an average .330 wOBA over 500 PA, we get an SD of .022, which means that 2 standard deviations better than that would be around 14%. Also, I'm only looking at positive fluke seasons for now.

6. This is not supposed to be a rigorous study. If it was, I'd want to do a lot more adjusting for context, with league and park adjustments and I'd probably include more than just the past 30 seasons. This is just a quick and dirty look to see if there's something there.

I don't know about most of you, but when the term 'fluke season' comes up, I instantly think of Brady Anderson in 1996. Anderson entered 1996 with 72 HRs in 3271 career ABs, with a career SLG of .393. At 32, odds of him improving would seem slim. So what happened? Anderson hit 50 HRs and slugged .637. It was one of the most incongruous performances in MLB history.

Now, obviously Anderson was never that good again, but it's interesting to look at what happened in 1997.

Player Brady Anderson
Year 1996
Age 32
Projected wOBA for 1996 .346
Actual wOBA for 1996 .431
wOBA Difference 24.7%
Original Projected wOBA for 1997 .342
Revised Projected wOBA for 1997 .379
Actual wOBA for 1997 .375
Original Difference 9.6%
Revised Difference -1.0%


So we see that coming into 1996, Anderson was projected to have a wOBA of .346, but he was 24.7% better than that at .431. Anderson's original projection for 1997 just used his 1996 projection instead of his actual 1996 numbers. The revised projection used the actual numbers. You can see that a subsequent comparison shows that even though his 1996 was a fluke, it did tell us something, as Anderson's revised projection was much closer to his actual 1997 performance than his original projection would have been.

One example doesn't make a case of course, so here are a few others to look at.

In my mind, the second biggest fluke season ever was Adrian Beltre in 2004. Beltre had youth on his side as well as a very good reputation as a prospect, but had hit just .262/.320/.428 for his career entering 2004, with an OPS+ of 97 and a career wOBA of .313. His 2004 retro-projection would have been for a line of .250/.303/.425 (wOBA of .310) thanks in large part to a dreadful 2003 where he hit just .240/.290/.424.

So what happened?

Player Adrian Beltre
Year 2004
Age 25
Projected wOBA for 2004 .311
Actual wOBA for 2004 .418
wOBA Difference 34.5%
Original Projected wOBA for 2005 .314
Revised Projected wOBA for 2005 .359
Actual wOBA for 2005 .305
Original Difference -2.7%
Revised Difference -15.2%


Yeah, Beltre hit .334/.388/.629 instead, good for a wOBA of .418. When compared to his projection coming into 2004, this was an even bigger fluke than Anderson's, although as I mentioned before Beltre was relatively young which made improving more realistic for him.

Unlike Anderson, Beltre gave back all of his gains and then some in 2005, as his projection for 2005 would have been closer if we used his 2004 projection instead of his 2004 actual line.

I've got one more single case to look at, which I'm hoping is predictive in the case of Nady,

Paul O'Neill came to the Yankees in a trade for Roberto Kelly in the 1992-1993 offseason. O'Neill was about to turn 30 and to that point had hit .259/.336/431 for his career in Cincinnati (wOBA of .323). He'd have projected to hit .256/.345/.418 (wOBA of .322) in 1993. Instead, he hit .311/.367/.504(wOBA of .370).

Player Paul O'Neill
Year 1993
Age 30
Projected wOBA for 1993 .322
Actual wOBA for 1993 .370
wOBA Difference 14.9%
Original Projected wOBA for 1994 .325
Revised Projected wOBA for 1994 .346
Actual wOBA for 1994 .435
Original Difference 33.6%
Revised Difference 25.7%


In O'Neill's case, he had tangibly improved and 1994 saw him hit even better.

Lastly, here's a look at the combined data for all players who exceeded their projected wOBA by 15% or more in any given season from 1978 - 2007.

Player All
Year N
Projected wOBA for year N .324
Actual wOBA for year N .389
wOBA Difference 20.1%
Original Projected wOBA for N + 1 .324
Revised Projected wOBA for N+1 .352
Actual wOBA for N+1 .346
Original Difference -6.5%
Revised Difference 1.6%


The general point here is that a fluke season can often be an indicator of a change in a player's skill. While the fluke season itself overstates it, when it is rolled into the player's projection going forward, we can see that in many cases the player has tangibly improved. This is probably common sense but I always like to validate CW statistically if i can.

Player Xavier Nady
Year 2008
Age 29
Projected wOBA for 2008 .339
Actual wOBA for 2008 .411
wOBA Difference 21.2%
Original Projected wOBA for 2009 .335
Revised Projected wOBA for 2009 .353
Actual wOBA for 2009 TBD
Original Difference TBD
Revised Difference TBD


Let's hope Nady's more Paulie than Adrian.

Update: More Random Pie Charts!




--Posted at 8:14 pm by SG / 129 Comments | - (978)




Thursday, February 7, 2008

Top Twenty Offensive Yankee Seasons - Right Field

We're getting towards the end of my rundown of the top twenty offensive seasons by a Yankee at various positions. As exciting as DH will be, I've decided to go with right field next.

For those just catching up, I've described the methodology I'm using here. It's important to remember that this methodology compare players to their peers of the same season, so you can't just compare raw stats. Context counts.

If you don't know the guy who's all over the RF list, you don't know baseball.

Rank Player Year Team Lg Pos G AB R H 2B 3B HR RBI SB CS BB SO AVG OBP SLG BRAA psOPS+
1 Babe Ruth 1920 NYA AL RF 142 457 158 172 36 9 54 137 14 14 150 80 .376 .533 .849 88 255
2 Babe Ruth 1923 NYA AL RF 152 522 151 205 45 13 41 131 17 21 170 93 .393 .545 .764 79 213
3 Babe Ruth 1927 NYA AL RF 151 540 158 192 29 8 60 164 7 6 137 89 .356 .486 .772 76 196
4 Babe Ruth 1924 NYA AL RF 153 529 143 200 39 7 46 121 9 13 142 81 .378 .513 .739 75 205
5 Babe Ruth 1931 NYA AL RF 145 534 149 199 31 3 46 163 5 4 128 51 .373 .495 .700 67 181
6 Babe Ruth 1928 NYA AL RF 154 536 163 173 29 8 54 142 4 5 137 87 .323 .463 .709 57 171
7 Babe Ruth 1930 NYA AL RF 145 518 150 186 28 9 49 153 10 10 136 61 .359 .493 .732 49 158
8 Babe Ruth 1932 NYA AL RF 133 457 120 156 13 5 41 137 2 2 130 62 .341 .489 .661 47 164
9 Babe Ruth 1929 NYA AL RF 135 499 121 172 26 6 46 154 5 3 72 60 .345 .430 .697 41 146
10 Reggie Jackson 1980 NYA AL RF 143 514 94 154 22 4 41 111 1 2 83 122 .300 .398 .597 38 156


Babe Ruth - 1920
I have Ruth's 1920 season as the third best offensive season relative to position ever, behind Barry Bonds in 2001 and Ruth himself(as a LF) in 1921. How good was Ruth in 1920? He SLUGGED .849 in a league that OPS-ed .732.

Babe Ruth - 1923
The idea of Ruth hitting 13 triples is comical to me, but in his youth he was supposedly quite an athlete. Ruth's .393 batting average in 1923 remains the Yankee record although I expect Robinson Cano to beat it soon.

Babe Ruth - 1927
Ruth's most famous season, although not his best. 60 homers will do that for you.

Babe Ruth - 1924
As impressive as this run of seasons by Ruth was, it does need to be tempered against the talent pool he was facing.

Babe Ruth - 1931
I've run out of stuff to say about Ruth and I still have four more seasons to go...

Babe Ruth - 1928
...

Babe Ruth - 1930
Interesting stat from this season, Ruth had 21 successful sacrifice bunts. Why would you ever bunt Babe Ruth?

Babe Ruth - 1932
Even at 37 Ruth was plugging along.

Babe Ruth - 1929
...

Reggie Jackson - 1980
Reggie Jackson's 1980 cost Babe Ruth his chance at Gehrig-ing the top ten list for Yankee RF. George Brett's .390 season cost Jackson the MVP as he finished second with five first place votes, but this was Jackson's best season as a Yankee and second best season of his career (behind 1969).

Here's 11-20:

Rank Player Year Team Lg Pos G AB R H 2B 3B HR RBI SB CS BB SO AVG OBP SLG BRAA psOPS+
11 Babe Ruth 1933 NYA AL RF 137 459 97 138 21 3 34 103 4 5 114 90 .301 .442 .582 37 148
12 Roger Maris 1960 NYA AL RF 136 499 98 141 18 7 39 112 2 2 70 65 .283 .371 .581 33 139
13 Dave Winfield 1988 NYA AL RF 149 559 96 180 37 2 25 107 9 4 69 88 .322 .398 .530 31 144
14 Roger Maris 1961 NYA AL RF 161 590 132 159 16 4 61 142 0 0 94 67 .269 .372 .620 30 126
15 Paul O'Neill 1994 NYA AL RF 103 368 68 132 25 1 21 83 5 4 72 56 .359 .460 .603 29 155
16 Babe Ruth 1934 NYA AL RF 125 365 78 105 17 4 22 84 1 3 104 63 .288 .448 .537 27 142
17 Danny Tartabull 1992 NYA AL RF 123 421 72 112 19 0 25 85 2 2 103 115 .266 .409 .489 24 146
18 Reggie Jackson 1977 NYA AL RF 146 525 93 150 39 2 32 110 17 3 74 129 .286 .375 .550 24 126
19 Dave Winfield 1984 NYA AL RF 141 567 106 193 34 4 19 100 6 4 53 71 .340 .393 .515 24 128
20 Tommy Henrich 1948 NYA AL RF 146 588 138 181 42 14 25 100 2 3 76 42 .308 .391 .554 23 128


Now we start to see some non-Ruth names including Roger Maris, Dave Winfield, Paul O'Neill, Danny Tartabll?, and Tommy Henrich. O'Neill's 1994 deserves a special mention due to the shortened season. If he played 145 games that year at the same rate of production he passes Ruth's 1929 and Jackson's 1980 in value. Of course odds are that the more he played, the more he would have regressed towards his true talent level.

And our top twenty breakdown...
Babe Ruth: 11
Dave Winfield: 2
Reggie Jackson: 2
Roger Maris: 2
Danny Tartabull: 1
Paul O'Neill: 1
Tommy Henrich: 1

We're through all the position players, but there's one more list coming up, the great hierarchy of Yankee DHs.
--Posted at 1:06 pm by SG / 39 Comments | - (1031)



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