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Equivalent Fantasy Average: Learning as we go

Someone pointed out a bit of an issue with the math in my new metric. So I calculated again! I'm nothing if not open to change.

Otto Greule Jr

My nephew loves board games. (I do, too, which is handy.) He does, however, have a bit of a problem with strategy.

See, the first time we played Monopoly, he noticed that the person who ended up with Boardwalk and Park Place won. After that, that was Grant's only strategy. He set his sights on those properties every time. That's all well and good - they're the best properties, after all - but Grant would do anything to get them. He would have two full monopolies on a corner of the board - say, the yellow and green bunches - and trade the lot of them for those two. "They are the way to win," he would say.

It had worked once, it was the way to play, and there was no questioning it. He's done it with other games - Carcassone, Settles of Catan, even Life. If something made him happy the first time, then that was his strategy forever. It took Grant several losses to realize he had other options.

Now, I'm a big fan of Eric Hosmer. If you've hung around this site for more than a few days, you know that.

So when I started fiddling around with a new sorting metric that I have since taken to calling Equivalent Fantasy Average, using math that made sense, and it gave relatively believable results that were all "Yay Hosmer," I was pretty daggone pleased with myself.

As I messed around with EFA, Hosmer did well. Jonathan Lucroy - another personal favorite - scored highly. People reading about it here responded favorably. I had Boardwalk and Park Place, and I was winning.

Of course, I'm good at math - but I'm not perfect.

If you read the comments section of the first-base EFA breakdown a couple weeks ago, you might have seen a small exchange about my approach. After I explained it, a commenter - very helpfully named "Mathete" - pointed out a flaw in my methodology. I separated players by position, then calculated the position's mean and standard deviation, using those numbers to formulate the final EFA.

Unfortunately, as Mathete pointed out, doing it that way meant that I was just weighting contributions like Hosmer's - a handful of stolen bases at a non-steal position - unnecessarily highly. It's good that Hosmer steals bases. It doesn't make him better than Joey Votto.

No, what I needed to do - and, if you look below, what I have done - is find the standard deviations across all the statistics, then use those with the positional means. That still gives extra credit to guys who do things others at their position don't - Hosmer, Paul Goldschmidt, Lucroy with the steals; Ian Desmond and Troy Tulowitzki with power - without making them into statistical demigods.

Blah blah blah, lots of explanation. Whatever, I made EFA better.

Starting with the shortstop piece from yesterday, our positional rankings going forward will include the update EFA projections. Below, I'm listing the revised EFA projections for catcher, first base, and second base. All the numbers are based on the 2014 statistical projections from Rotobanter. And Mathete - or any wannabe Mathetes out there - feel free to chime in if I'm still not quite there with my math.

After all, Grant's gotten better at Monopoly, but he still hasn't figured out the real key to the game: Hotels on the orange properties. (People go to jail. They roll to get out of jail. The most common rolls are those in the range of seven. Seven plus/minus spaces out from jail is the orange properties - St. James, Tennessee, New York. You build on those, you're golden.) So I'm all ears.


Rank Team Projected 2014 EFA
1 Buster Posey SFG .282
2 Wilin Rosario COL .279
3 Jonathan Lucroy MIL .275
Joe Mauer MIN .275
5 Yadier Molina SLC .274
6 Salvador Perez KCR .273
Carlos Santana CLE .273
8 Brian McCann NYY .272
9 Wilson Ramos WAS .269
Matt Wieters BAL .269
11 Jason Castro HOU .264
Miguel Montero ARI .264
13 Yan Gomes CLE .261
14 Evan Gattis ATL .258
A.J. Pierzynski BOS .258
16 Dioner Navarro TBJ .257
17 Travis d'Arnaud NYM .256
18 Welington Castillo CHC .255
Mike Zunino SEA .255
20 Alex Avila DET .253
Russell Martin PIT .253
Hank Conger LAA .253
23 Devin Mesoraco CIN .251
Josh Phegley CWS .251
Carlos Ruiz PHI .251
Jarrod Saltalamacchia MIA .251
27 Geovany Soto TEX .250
28 A.J. Ellis LAD .249
29 Ryan Lavarnway BOS .248
Josmil Pinto MIN .248
31 John Jaso OAK .243

First Base

Rank Team Projected 2014 EFA
1 Miguel Cabrera DET .304
2 Paul Goldschmidt ARI .296
3 Chris Davis BA; .288
4 Edwin Encarnacion TBJ .287
5 Freddie Freeman ATL .286
6 Prince Fielder TEX .283
7 Joey Votto CIN .282
8 Eric Hosmer KCR .281
9 David Ortiz BOS .277
10 Adrian Gonzalez LAD .276
11 Allen Craig SLC .275
Buster Posey SFG .275
Anthony Rizzo CHC .275
14 Billy Butler KCR .274
15 Albert Pujols LAA .273
Mark Trumbo ARI .273
17 Brandon Belt SFG .268
Kendrys Morales FA .268
19 Joe Mauer MIN .267
Brandon Moss OAK .267
21 Victor Martinez DET .266
22 Carlos Santana CLE .265
23 Chris Carter HOU .264
Mark Teixeira NYY .264
25 Corey Hart SEA .263
Justin Morneau COL .263
Mike Napoli BOS .263
28 Matt Adams SLC .262
29 Nick Swisher CLE .260
30 Mitch Moreland TEX .259
31 Yonder Alonso SDP .258
Justin Smoak SEA .258
33 Adam LaRoche WAS .257
Adam Lind TBJ .257
35 James Loney TBR .255
36 Ryan Howard PHI .253
Logan Morrison SEA .253
38 Adam Dunn CWS .251
39 Lucas Duda NYM .249
40 Ike Davis NYM .248
Garrett Jones PIT .248
Mark Reynolds MIL .248
43 Juan Francisco MIL, .247
Darin Ruf PHI .247
45 Kyle Blanks SDP .242
46 Paul Konerko CWS .241

Second Base

Rank Team Projected 2014 EFA
1 Robinson Cano SEA .286
Jason Kipnis CLE .286
3 Dustin Pedroia BOS .283
4 Matt Carpenter SLC .282
5 Jedd Gyorko SDP .280
6 Jose Altuve HOU .277
7 Ben Zobrist TBR .276
8 Aaron Hill ARI .275
Brandon Phillips CIN .275
10 Daniel Murphy NYM .274
Martin Prado ARI .274
12 Ian Kinsler DET .273
13 Howie Kendrick LAA .272
Jed Lowrie OAK .272
15 Brian Dozier MIN .271
16 Neil Walker PIT .268
17 Omar Infante KCR .267
Jurickson Profar TEX .267
19 Anthony Rendon WAS .266
Chase Utley PHI .266
21 DJ LeMahieu COL .263
22 Kolten Wong SLC .262
23 Kelly Johnson NYY .258
24 Alberto Callaspo OAK .256
25 Gordon Beckham CWS .255
Scooter Gennett MIL .255
27 Dustin Ackley SEA .253
28 Dan Uggla ATL .251