Tm | Lg | YEAR | G | AB | R | H | BB | SO | 2B | 3B | HR | RBI | SB | CS | BA | OBP | SLG | BB% | SO% | BABIP | G/L/F % | $4x4 | $5x5 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
NYY | AL | 2018 | 112 | 413 | 77 | 115 | 76 | 152 | 22 | 0 | 27 | 67 | 6 | 3 | .278 | .392 | .528 | 15 | 31 | .368 | 42/23/35 | 23 | 22 |
NYY | AAA | 2019 | 5 | 16 | 2 | 2 | 3 | 7 | 0 | 0 | 1 | 2 | 0 | 0 | .125 | .263 | .312 | 16 | 37 | .125 | n/a | ||
NYY | AL | 2019 | 102 | 378 | 75 | 103 | 64 | 141 | 18 | 1 | 27 | 55 | 3 | 2 | .272 | .381 | .540 | 14 | 32 | .360 | 40/27/32 | 17 | 17 |
NYY | AL | 2020 | 28 | 101 | 23 | 26 | 10 | 32 | 3 | 0 | 9 | 22 | 0 | 1 | .257 | .336 | .554 | 9 | 28 | .283 | 39/20/41 | 15 | 15 |
NYY | AL | 2021 | 148 | 550 | 89 | 158 | 75 | 158 | 24 | 0 | 39 | 98 | 6 | 1 | .287 | .373 | .544 | 12 | 25 | .332 | 41/23/36 | 33 | 30 |
NYY | AL | 2022 | 157 | 570 | 133 | 177 | 111 | 175 | 28 | 0 | 62 | 131 | 16 | 3 | .311 | .425 | .686 | 16 | 25 | .340 | 37/19/44 | 54 | 48 |
Career | 7yrs | 729 | 2638 | 535 | 748 | 472 | 908 | 121 | 4 | 220 | 497 | 40 | 15 | .284 | .394 | .583 | 15 | 29 | .345 | n/a |
Welcome! You are invited to wander around and read all of the comments that have been posted here at Patton & Co., but as soon as you register you can see the bid limits that Alex, Peter and Mike propose for each player, and you can post your own comments. Registering is free, so please join us!
Props to Mike, by the way. In a six-battle between the three experts leagues and the three of us here, he's the winner.
Nov 25 '17
Prices for Judge in the experts leagues:
CBS $5
LABR $6
Tout Wars $3
The first sentence of On Winning AL-Only Tout Wars, by Mike Pdhorzer: "Aaron Judge, my thank you card is in the mail."
https://www.fangraphs.com/fantasy/on-winning-al-only-tout-wars/
Nov 25 '17
Foreman's point that despite the WAR parity the voters clearly agreed on who was the MVP is a good one. Why did James pick this terabull fight now?
Nov 21 '17
Sean Forman posted his own argument on baseball-reference. I had replied to him saying Bill James had sacked him when he was away for the weekend, with a comment about how this reminded me of lurking on usenet. Turns out he mentioned that in his statement, linking to a 1997 discussion.
Nov 21 '17
It's pretty neat, actually. The final step in the calculation:
6. Baseball Players Set Their Own Standard
Now that we have established a chance of winning for a team from any
situation, the next thing is to be able to convert that chance of
winning into a meaningful value so that we can award Win and Loss
Points. Here's what we've come up with.
The chance of winning is, naturally, expressed in percentages. That's
awkward, so we have converted them to whole numbers. Then, for reasons
of simplicity, instead of a start of a game being 50-50, we set the
value at O. We set the end of a game at +1000 for a home team win, and
-1000 for a visitor win.
Now, as the game progresses, the visitors are attempting to move the
game to -1000, while the home team is striving for + 1000. Each player,
depending on his action, is then awarded points, based entirely on how
much he has increased or decreased his team's chance of winning. We
already know what the chances of winning are from every situation, so
all we have to do is look at the value of the situation when he came to
bat, look at the new value after he is through, and award the points.
If he increased his team's chance of winning (usually by getting on
base) he will receive Win Points. If he decreased his team's chance of
winning (usually by making an out) he will receive Loss Points. The
opposing responsible player (usually the pitcher) receives just the
opposite, so that on every play a player on one team receives Win
Points, and a player on the other receives exactly the same number of
Loss Points.
And so on down through the game: The more clutch the situation, the
larger the value of pcoints, both Win and Loss. Average situations will
generally have a value of between 25 and 75 points. Big clutch plays get
up as high as 1800 points (going from probable defeat to certain
victory), and small clutch plays drop to 5 to 10 points (hitting a home
run in the ninth while leading by six runs) . Bobby Thomson's home run?
Worth 1472 Win Points. Pitcher Ralph Branca? 1472 Loss Points. Who's
Branca? He threw the pitch that Thomson hit.
So, over any period of time-weeks, months, a season- we continually
award Win and Loss Points to each individual player. We award the points
to a member of each team simultaneously on each play, based on just how
much each player increases or decreases his team's chance of winning.
This is comparable to awarding number of hits and times at bat to a
player. At any period of time we can stop and figure his batting
average. It's the same with our scoring system. At any period of time we
can stop and figure a Player Win Average. Everybody knows how to figure
a batting average (divide number of times at bat into number of hits),
but once again, here's how we figure a Player Win Average.
Add up the total of a player's Win and Loss Points. Then divide that
total into the Win Points only. The resultant percentage is a win
average. Example-if a player has 13,000 Win Points and 12,000 Loss
Points, we divide 13,000 plus 12,000 (25,000) into 13,000. That turns
out to be a .520 win average. Since it belongs to an individual player
we call it a Player Win Average.
Here's something to keep in mind, and it also explains why we think this measurement system is equitable for the players.
The players are not measured against any arbitrary standard. They are
measured against their own teammates and opponents on how they performed
this year. Over the year, using our new scorecard, we tabulate every
play of every game. We know what actually happened-how many times each
situation moved to each next situation. This gives us an average of what
will happen on each next play, as actually performed by the players.
So when we score each player against that average, we are really scoring
him against his fellow players and opponents. The player who conforms
to the average will have exactly the same number of Win and Loss Points,
for a .500 Player Win Average. Those who are better than average will
be above .500, and those who are less than average will be below .500,
no matter what their batting average or earned run average may be.
To illustrate, if it were a common, every-day occurrence for a player to
hit a game-winning home run in the ninth, then those who did not would
be below average. Since this is not the case, those who do not are not
necessarily below average. Also, in a year when hitters are big, and ten
runs a game are commonplace, a player had better be up there getting
his share, or he'll be below average. On the other hand, in a year like
1968, an average hitter needn't have done so much, since low scoring
games were the rule.
In other words, we do not measure players from one era against players
from another. We measure them against their own teammates and opponents.
But the statistic itself-Player Win Average-can be used to compare
players of any era. That's because, in any era, whether the ball be
dead or rabbit-like, a .500 ball player will be average, and a .570
player will be much better than average.
Nov 21 '17
It's something called Player Win Averages, which may have inspired Project Scoresheet.
Nov 21 '17
Is that referring to Project Scoresheet?
Nov 20 '17
The strangest statement in a very long and strange ramble: "Because Dickey and Howard created runs in the same park, the park adjustments that apply to them are the same for both players."
The Handbook shows how different the park adjustments are for right and lefthanded batters. In any ballpark.
In the old Yankee Stadium, it was extreme. Balls went to die in left center, even after they put the fence in front of the monuments.
Another odd statement (partial statement): "If Howard had been a left-handed hitter and Dickey a right-handed pull hitter like Howard..."
My memory is that Howard was distinctly not a pull hitter. He lost a lot of homers, certainly, that would have cleared the left field fence in other ballparks, but (perhaps in response to that) he hit with authority to right center.
In any event, if you click on the link that Tom Tango provides at the end of the piece, this is what you'll find:
Where could we get this kind of information? Of all the statistics on
baseball today, nobody we could find kept track of a game in this
manner. So we had to do it ourselves. The end result was a scorecard
that not only simultaneously told us "what" and "when" a player did
something, but could be preserved, in such a way that the information
could be transposed to computer cards-and then to a computer.
This scorecard fitted our purposes exactly. Now we could gather a
history of the progress of every game in both leagues for the entire
season (and all seasons to come) as) it actually happened. Now we could
tell, for instance, just what percent of the time any situation would
follow any other situation. As an example, we know (and we don't know
anybody else who does) what percent of the time a double play will occur
with a runner on first, and less than two outs. We also know not only
what percent of the time a home run will be hit with men on second and
third and one out (Bobby Thomson's situation), but also what percent of
the time a home run will be hit from every combination of men on base
and outs.
I'd love to see their scorecards.
Nov 20 '17
Fascinating ramble along with Bill. Particularly the Bill Dickey/Elston Howard comparison and the discounting for Charlie Blackmon in Coors.
A few oddities: Why does he say Yankee Stadium was "turabull" for Elston Howard? Why does he call the Charlie Blackmon who is maybe growing pot in Colorado Johnny Blackmon? Why does he think anyone remembers or cares about the Steve Garvey rule?
FInally, his insistence that you can't start with everyone average and adjust them up and down as you get data, rather you have to start them at the bottom and build them up, doesn't make sense to me. Especially in light of his discussion about the value of average ballplayers, which reminded me of how much I used to like reading him.
Nov 20 '17
Bill James decided to write a longer, more rambling, column on his site. It includes a full take down of WPA.
Nov 20 '17