Disclaimer: This is just for fun. I am, by no means, claiming that the predicted average draft positions (ADPs) described below will happen. Obviously! I’m no prophet. Also, I am not claiming these predictions are merely educated guesses. In fact, these aren’t even my predictions — they’re yours. Or, well, they’re not your predictions — they’re my computer’s predictions, but fitting your behavior to observed events.

That’s a complicated way of saying: by using historical ADP data and end-of-season (EOS) values, we can model future ADP values. (xADP, if you will.) Namely, with 2018 EOS, 2018 ADP, and 2017 EOS, we can predict 2019 ADP — and explain almost 60 percent of its variance (adjusted r2 = 0.59).

Over the years, I’ve compiled seven years’ worth of ADP data from the National Fantasy Baseball Championship (NFBC) and EOS values courtesy of Razzball — almost 5,500 player-seasons, although for these purposes I’ve narrowed my n to 2,315.

The problem with ADP (and EOS) ranks is they’re perfectly linear, whereas the values they represent are not. For example, the difference in value between the 1st and 2nd picks in a draft is not the same as the difference in value between the 399th and 400th picks. To resolve this issue, I converted the linear values (1, 2, 3 … 99, 100, 101 … 398, 399, 400) into logarithmic dollar equivalents (\$58, \$52, \$48 … \$13.70, \$13.60, \$13.50 … \$0.17, \$0.15, \$0.12). In order to do this, though, I needed to construct a hypothetical league in which these values would be applied. Somewhat arbitrarily, I chose a 15-team league with 27-player rosters, such that the draft pool would be 405 players deep. I made this decision partly due to limitations with my older data. However, I’m not convinced that changing the league size — not dramatically, at least — would make much difference anyway.

(Here’s some messy math. Feel free to skip to the next paragraph if it’s not your jam.)

Because the data effectively operates as a panel — hundreds of players whose actual and perceived values are observed over time — and because we cannot dissociate ourselves from our knowledge, perceptions, and biases of these players, there exists serial correlation among the values. This correlation — the influence of 2017 EOS on 2018 ADP, and so on — artificially inflates the fit of the model. A standard linear regression of this same data produces an adjusted r2 of 0.85, which is incredible but misleading. To correct for this, I specified a first-differences regression, which subtracts the previous period’s value from the current period (for example, 2018 ADP minus 2017 EOS).

(OK, stop skipping.)

Here’s the final model:

(…maybe you could’ve skipped that part, too.)

I can tell you, without even really looking at the numbers, that the model will probably struggle in some areas. Obviously, it won’t know if a player has retired. It’s unaware of seasons truncated by injury or midseason debut. It has no concept of prospect hype and will absolutely whiff on Vladimir Guerrero Jr., who has yet to debut but will be the prospect gem with tons of helium in 2019 fantasy drafts. It is blissfully unaware of the out-of-control Adalberto Mondesi hype train. You can yell at me all you want about how stupid that is, but you’d be yelling at a computer that can’t think for itself.

It’ll be months before we see this work bear fruit, but we can at least compare the results of the Too Early Mock Drafts that ran in September, the data for which were compiled by the enigmatic Smada.

1 1.83 Mike Trout
2 2.47 Mookie Betts
3 5.02 Trea Turner
5 9.51 Christian Yelich
6 9.65 J.D. Martinez
7 10.15 Jose Altuve
8 10.54 Jose Ramirez
10 10.69 Francisco Lindor
11 12.30 Max Scherzer
12 12.94 Bryce Harper
13 14.99 Paul Goldschmidt
14 18.09 Giancarlo Stanton
15 20.80 Clayton Kershaw
16 20.82 Freddie Freeman
17 21.45 Alex Bregman
18 21.48 Charlie Blackmon
19 22.18 Corey Kluber
20 22.31 Chris Sale
21 23.17 Justin Verlander
22 25.82 Jacob deGrom
23 26.10 Trevor Story
24 27.95 Starling Marte
25 28.95 Javier Baez
26 33.06 Andrew Benintendi
27 34.21 Rhys Hoskins
28 37.56 Anthony Rizzo
29 38.80 Khris Davis
30 38.83 Noah Syndergaard
31 39.00 Aaron Nola
32 39.02 Edwin Diaz
33 39.41 Luis Severino
34 39.57 Blake Treinen
35 42.96 Craig Kimbrel
36 43.46 Cody Bellinger
37 44.78 Carlos Carrasco
38 45.27 Whit Merrifield
39 45.80 Gerrit Cole
40 48.75 George Springer
41 49.46 Ronald Acuna
42 50.56 Ozzie Albies
43 50.73 Anthony Rendon
44 51.89 Carlos Correa
45 56.25 Blake Snell
46 56.97 Xander Bogaerts
47 60.88 Aaron Judge
48 61.35 Kris Bryant
49 62.17 Jean Segura
50 64.74 Tommy Pham
51 64.89 Stephen Strasburg
52 64.90 Zack Greinke
53 65.44 Edwin Encarnacion
54 65.49 Kenley Jansen
55 68.36 Gary Sanchez
56 69.21 Nicholas Castellanos
57 70.07 Joey Votto
58 71.81 Aroldis Chapman
59 72.60 Ian Desmond
60 72.83 Lorenzo Cain
61 74.48 Justin Upton
62 76.13 Shohei Ohtani
63 76.84 Nelson Cruz
64 79.69 Didi Gregorius
65 82.13 Matt Carpenter
66 83.22 David Price
67 83.96 Mitch Haniger
68 85.04 J.T. Realmuto
69 86.11 Marcell Ozuna
70 86.72 Dee Gordon
71 86.90 Jose Abreu
72 87.17 Brian Dozier
74 88.14 Matt Olson
75 88.15 Gregory Polanco
76 89.51 Trevor Bauer
77 89.79 A.J. Pollock
78 91.67 James Paxton
79 92.08 Eugenio Suarez
80 93.07 Joey Gallo
81 97.34 Travis Shaw
82 97.93 Eddie Rosario
83 100.34 Michael Brantley
84 104.58 Miles Mikolas
85 104.77 Willson Contreras
87 107.10 Jose Quintana
88 109.66 Carlos Martinez
91 110.95 Kyle Hendricks
92 111.95 Jose Peraza
93 112.32 Scooter Gennett
94 112.89 Jose Berrios
95 112.95 Andrew McCutchen
96 113.38 Masahiro Tanaka
97 113.84 Raisel Iglesias
98 115.69 Ender Inciarte
100 116.68 Luis Castillo
101 116.87 Robbie Ray
102 117.08 Miguel Andujar
103 118.90 Rougned Odor
104 119.28 Jon Lester
105 120.97 Aaron Hicks
106 122.75 Rafael Devers
107 122.80 Sean Doolittle
108 124.67 Dallas Keuchel
109 125.27 Chris Taylor
110 125.47 Chris Archer
111 125.92 Evan Gattis
112 126.00 Wilson Ramos
113 126.47 Yasiel Puig
114 127.05 Jameson Taillon
115 127.82 Corey Knebel
116 128.51 David Peralta
117 128.51 Charlie Morton
118 128.91 Stephen Piscotty
119 129.05 Buster Posey
120 129.18 Billy Hamilton
121 129.60 Josh Donaldson
122 130.22 Mike Moustakas
123 131.64 Matt Chapman
124 132.07 Ryan Braun
125 133.54 Jonathan Villar
126 134.13 Jeurys Familia
127 134.76 Tim Anderson
128 136.08 Patrick Corbin
129 140.05 Mike Clevinger
130 141.56 Cody Allen
131 141.96 Eric Hosmer
132 142.80 DJ LeMahieu
133 143.80 Lance McCullers
134 144.73 Marcus Semien
135 146.18 Yu Darvish
138 149.66 J.A. Happ
139 150.98 Mallex Smith
140 154.71 Amed Rosario
141 155.27 Rich Hill
142 156.04 Michael Conforto
143 156.31 Yasmani Grandal
144 156.80 Roberto Osuna
145 161.68 Mike Foltynewicz
146 161.69 Jonathan Schoop
147 163.71 Wil Myers
148 166.49 Jake Arrieta
149 167.80 Justin Turner
150 168.17 Kyle Schwarber
151 168.60 Rick Porcello
152 170.27 Walker Buehler
153 171.21 Zack Godley
154 171.47 Nomar Mazara
155 172.67 Jose Martinez
156 173.45 Carlos Santana
157 175.38 Cesar Hernandez
158 175.96 Gleyber Torres
160 180.66 Alex Colome
161 182.91 Paul DeJong
162 183.34 Corey Seager
164 185.27 Ken Giles
165 186.47 Jason Kipnis
166 186.89 Robinson Cano
167 188.38 Alex Wood
168 188.41 Odubel Herrera
169 192.32 Felipe Vazquez
170 193.92 Luke Weaver
171 196.01 Andrelton Simmons
172 196.34 Kyle Seager
173 199.51 Yuli Gurriel
174 200.15 Byron Buxton
175 201.04 Ian Happ
176 202.28 Matt Kemp
177 202.62 Trey Mancini
178 205.54 Justin Smoak
179 206.06 Garrett Richards
180 206.24 Sean Manaea
181 206.46 Manuel Margot
183 208.60 German Marquez
184 210.29 Yoenis Cespedes
185 210.93 Jack Flaherty
186 211.13 Marwin Gonzalez
187 211.19 Jon Gray
188 215.33 Brett Gardner
189 215.38 Julio Teheran
190 215.46 Shane Greene
191 216.15 Ian Kinsler
192 217.68 Carlos Gonzalez
193 218.16 Daniel Murphy
194 218.98 C.J. Cron
195 220.52 Robinson Chirinos
196 220.87 Kevin Gausman
198 221.77 Jesus Aguilar
199 223.47 Chase Anderson
200 223.96 Kenta Maeda
201 224.63 Cole Hamels
202 225.40 Zack Wheeler
204 227.74 Corey Dickerson
205 229.23 Nick Markakis
206 229.35 Sonny Gray
207 230.68 Arodys Vizcaino
208 230.80 Jed Lowrie
209 230.86 Miguel Cabrera
210 232.67 Yonder Alonso
211 233.54 Brandon Morrow
212 234.31 Eduardo Nunez
213 234.36 Johnny Cueto
214 235.49 Josh Bell
215 235.77 Elvis Andrus
216 236.73 Maikel Franco
217 237.06 Shin-Soo Choo
218 239.24 Jorge Alfaro
219 239.88 Asdrubal Cabrera
220 240.89 Sean Newcomb
221 243.14 Randal Grichuk
222 243.83 Ketel Marte
223 246.91 Eduardo Rodriguez
224 249.00 Mike Zunino
225 249.13 Jhoulys Chacin
226 250.79 Jeremy Jeffress
227 254.04 Starlin Castro
228 254.16 Eduardo Escobar
229 256.53 Johan Camargo
230 260.38 David Dahl
232 264.28 Jonathan Lucroy
233 265.33 Kevin Pillar
234 265.41 Kelvin Herrera
235 265.91 Teoscar Hernandez
236 266.77 Hunter Renfroe
237 267.14 Hyun-Jin Ryu
238 268.35 Jeimer Candelario
239 270.13 Michael Wacha
240 270.98 Ryon Healy
241 273.10 Fernando Rodney
242 275.47 Mike Minor
243 278.20 Andrew Heaney
244 278.49 Trevor Williams
245 279.00 Joc Pederson
246 279.00 Keone Kela
247 279.03 Gio Gonzalez
249 279.55 Jacob Faria
250 280.78 Steven Matz
251 282.74 Dellin Betances
252 284.61 Max Kepler
253 284.86 Miguel Sano
254 285.39 Aaron Sanchez
255 286.06 Hector Neris
256 286.68 Justin Bour
257 288.69 Tanner Roark
258 292.65 Greg Bird
260 293.64 Scott Kingery
261 296.27 Collin McHugh
262 300.24 Delino DeShields
263 300.34 Kevin Kiermaier
264 300.59 Evan Longoria
265 302.91 Yan Gomes
266 305.09 Joakim Soria
267 306.06 Dylan Bundy
268 307.50 Danny Duffy
269 308.69 Austin Hedges
270 311.96 Vince Velasquez
271 313.07 Kole Calhoun
272 313.37 Matt Harvey
273 314.11 Jake Odorizzi
274 314.40 Matt Duffy
275 314.46 Kyle Gibson
276 316.98 Blake Parker
277 318.56 Tucker Barnhart
278 319.18 Lance Lynn
279 320.74 Michael Fulmer
280 321.95 Francisco Cervelli
281 324.76 David Robertson
282 325.38 Colin Moran
283 326.27 Michael A. Taylor
284 326.41 Scott Schebler
285 327.05 Reynaldo Lopez
286 327.52 Todd Frazier
287 327.94 A.J. Minter
288 333.10 Jake Junis
289 334.67 Nick Williams
290 334.73 Jurickson Profar
291 335.74 Yoshihisa Hirano
292 335.75 Mark Melancon
293 335.98 Avisail Garcia
294 337.19 Dansby Swanson
295 337.78 Marcus Stroman
296 338.97 Joe Musgrove
297 339.65 Brandon Belt
298 339.69 Tyler Skaggs
299 341.90 CC Sabathia
300 343.21 Tyler Glasnow
301 343.78 Chris Iannetta
302 344.33 Kurt Suzuki
303 345.16 Anthony DeSclafani
305 345.85 Welington Castillo
307 350.76 Jeff Samardzija
308 351.18 Jesse Winker
309 351.63 Josh Reddick
310 352.94 Freddy Galvis
311 353.89 Domingo Santana
312 354.24 Brandon Crawford
313 354.92 Lucas Giolito
314 355.67 Austin Barnes
315 360.30 Albert Pujols
316 361.41 Juan Soto
317 361.90 Clay Buchholz
318 362.91 Eric Thames
319 364.55 Yangervis Solarte
320 368.25 Lewis Brinson
321 369.51 Joey Wendle
322 370.71 Ryan Zimmerman
323 370.87 Orlando Arcia
324 370.94 Kendrys Morales
326 373.89 Gerardo Parra
327 377.19 Felix Hernandez
328 378.20 Mike Leake
329 378.63 Jordan Montgomery
331 380.29 Leonys Martin
332 380.31 Ivan Nova
333 382.86 Daniel Mengden
334 383.51 Nick Pivetta
335 384.61 Mark Trumbo
336 387.10 Jorge Polanco
337 387.60 Denard Span
338 392.61 Jose Urena
339 394.09 Tyler Anderson
340 396.91 Carlos Rodon
341 399.65 Brandon Nimmo
342 399.74 Jason Heyward
343 401.54 Jake Lamb
344 401.75 Matt Davidson
345 403.64 Luiz Gohara
346 407.33 Devon Travis
347 407.34 Tyler Flowers
349 407.86 Brian McCann
350 411.55 Andrew Miller
351 412.27 Kyle Freeland
352 412.56 Manny Pina
353 413.94 Marco Gonzales
354 414.63 Brian Anderson
355 414.92 Albert Almora
357 416.95 Tyler Chatwood
358 417.20 Alex Cobb
359 418.19 Brandon Woodruff
360 419.54 James McCann
361 419.57 Yolmer Sanchez
362 420.16 Drew Steckenrider
363 422.20 Mitch Moreland
364 422.42 Wilmer Flores
365 423.38 Jay Bruce
366 425.07 Josh Harrison
367 425.89 Willie Calhoun
368 425.91 Anibal Sanchez
369 429.65 Dan Straily
371 430.99 Chris Davis
372 431.77 Cam Bedrosian
373 432.22 Jorge Soler
374 432.31 Matt Wieters
375 433.70 Ryan McMahon
376 433.99 Chris Owings
377 434.94 Zach Britton
378 436.36 Russell Martin
379 436.82 Matt Shoemaker
380 438.04 Jose Pirela
382 442.01 Tyler Mahle
383 442.09 Jedd Gyorko
385 443.93 Ben Zobrist
386 447.02 Kolten Wong
387 447.40 John Gant
388 447.86 Nate Jones
389 448.30 Tim Beckham
390 448.68 Wilmer Difo
391 449.88 Alex Reyes
392 451.04 Carlos Gomez
393 451.29 Chris Stratton
394 451.30 Joe Mauer
395 454.43 Victor Robles
396 455.38 Greg Holland
397 461.26 Jesse Chavez
398 461.28 Dexter Fowler
399 462.29 Zach Eflin
401 472.93 Zach Davies
402 473.51 Chance Sisco
403 476.19 Dustin Fowler
404 477.94 Danny Salazar
405 479.37 Lucas Duda
406 479.41 Brandon McCarthy
407 481.30 Christian Vazquez
408 484.67 Taijuan Walker
409 486.00 Mark Canha
410 486.10 Dinelson Lamet
411 488.67 Nathan Eovaldi
412 488.75 Kyle Barraclough
414 489.08 Carl Edwards Jr.
415 490.58 Roenis Elias
416 490.63 Neil Walker
417 494.35 Francisco Mejia
418 496.26 Derek Dietrich
419 496.35 Aledmys Diaz
420 497.59 Matthew Boyd
421 497.98 Ian Kennedy
422 502.20 Hanley Ramirez
423 503.18 Hernan Perez
424 503.96 Mike Fiers
425 504.40 Steven Souza Jr.
426 506.73 Michael Kopech
427 511.32 Derek Holland
428 511.89 Mike Montgomery
429 513.77 Aaron Altherr
430 515.18 Chris Devenski
431 515.52 Zack Cozart
432 517.68 Cameron Maybin
433 521.12 John Axford
434 523.39 Curtis Granderson
436 524.98 Kike Hernandez
437 527.56 Logan Morrison
438 529.58 Nick Senzel
439 529.94 Gorkys Hernandez
440 531.24 J.P. Crawford
442 534.18 Alex Claudio
443 538.09 Tyler Clippard
444 541.53 Jose Bautista
445 542.60 Mikie Mahtook
446 543.11 Luke Gregerson
448 544.51 Austin Hays
449 545.22 Mychal Givens
450 546.51 Curt Casali
451 547.29 Ryan Pressly
452 547.60 Derek Fisher
453 549.05 Brent Honeywell
454 551.24 Juan Minaya
455 551.26 Logan Forsythe
456 551.64 Drew Pomeranz
457 553.53 Alex Avila
458 562.66 Nick Ahmed
460 574.20 Ervin Santana
461 575.47 Nick Kingham
462 576.75 Alex Gordon
464 580.24 Tyson Ross
465 581.39 Drew Hutchison
466 581.65 Travis d’Arnaud
467 582.79 Ross Stripling
468 584.20 Eloy Jimenez
469 584.20 Joe Panik
470 586.56 David Bote
471 587.77 Bud Norris
472 588.36 Jason Vargas
473 590.22 Trevor May
474 591.18 Yasmany Tomas
475 594.65 Dominic Leone
476 595.31 Zach Duke
477 598.21 Tony Kemp
478 599.32 Jarrod Dyson
479 599.58 Elias Diaz
480 600.01 Wily Peralta
481 603.18 Cory Spangenberg
482 603.95 Franklin Barreto
483 604.12 Seung Hwan Oh
484 608.13 Raimel Tapia
485 610.79 Troy Tulowitzki
486 611.94 A.J. Puk
487 618.16 Jose Lobaton
488 619.19 Brandon Drury
490 623.12 Shawn Kelley
491 624.45 Pedro Strop
492 625.72 Mitch Garver
493 625.79 Lonnie Chisenhall
494 626.41 Ronald Guzman
495 636.71 Nicky Delmonico
496 637.49 Andre Ethier
497 638.13 Sam Dyson
498 638.43 Blake Swihart
499 638.72 Luis Avilan
500 639.15 Jacob May

If there are any glaring omissions, it’s probably because the player made an impact in 2018 despite being drafted outside the top-405 players. Let me know who’s missing and I can give you the ADP value!

I’m also curious to hear your thoughts — on the first round, on perceived accuracy or inaccuracy, everything. My computer wants your feedback. At the end of the day, though, this isn’t anything more than a stupid data trick. It’ll be fun (for me, at least) to see how close this gets.

We hoped you liked reading Predicted 2019 NFBC ADP by Alex Chamberlain!

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Currently investigating the relationship between pitcher effectiveness and beard density. Biased toward a nicely rolled baseball pant. Three-time FSWA award finalist, one-time award-winner. Featured in Lindy's Sports' Fantasy Baseball magazine (2018, 2019).

Member
Colby

Only glaring omission seems to be Juan Soto, who I imagine wasn’t drafted all that much. Interested in where he places, I imagine not too far from Acuna, in the low 50s.

I also could guess you will see some differences in how Kris Bryant is treated in real drafts vs this model, but injuries played a big role for him this year.

Member
wubbie075

I think both Soto and Acuna are likely to slot a bit higher in real drafts than where Acuna actually landed on the list above. Bryant will definitely end up much higher.

This is kinda fun, but considering the limitations of the model acknowledged by the author it’s probably not gonna end up being useful in most practical cases. Better to use actual ADP data adjusting for league context and the latest news reports as you approach your drafts next pre-season.

Member
Anonymous

As a first step, this research is amazing for those of us in Dynasty and Keeper leagues. Even if the projections start flawed, they might get better every year to the point where they can be real asset in an owner’s portfolio.