Tuesday, September 30, 2014

MLB 2014: Regular Season Review

First or two analyses on the 2014 MLB season review let's examine the Pythagorean Theorem we have posted about over summer:



Here is what the standings & playoff seeding would look like for each division, starting first with the American League:






P WINS
P LOSSES
+ / -

BAL
92
70
4

TBR
87
75
(10)

TOR
85
77
(2)

NYY
78
84
6

BOS
71
91
(0)






DET
90
72
0

CLE
84
78
1

KCR
83
79
6

CHW
75
87
(2)

MIN
71
91
(1)






LAA
100
62
(2)

OAK
96
66
(8)

SEA
88
74
(1)

HOU
75
87
(5)

TEX
65
97
2










PLAYOFF PROJECTIONS
#1 SEED
LAA


#2 SEED
BAL


#3 SEED
DET


WC #1
OAK


WC #2
SEA



These projections were right on target with the top 3 seeds identical to the final regular season standings, while one of the two Wild Card teams were correct – missing Seattle.  The Royals were able to land a Wild Card spot winning 6 games more than their runs difference would suggest – keep an eye on that come the opener vs. Oakland & if they were to advance to face the Angels.
Next up here is the National League:






P WINS
P LOSSES
+ / -

WSN
97
65
(1)

ATL
78
84
1

MIA
77
85
(0)

NYM
76
86
3

PHI
73
89
(0)






PIT
94
68
(6)

STL
86
76
4

MIL
83
79
(1)

CHC
79
83
(6)

CIN
75
87
1






LAD
97
65
(3)

SFG
89
73
(1)

COL
80
82
(14)

SDP
73
89
4

ARI
69
93
(5)


CURRENT PLAYOFF PROJECTIONS
#1 SEED
WSN


#2 SEED
LAD


#3 SEED
PIT


WC #1
SF


WC #2
STL



My Pythagorean Theorem for the NL was right on the target as far as the five teams that made the playoffs, and which teams earned the top 2 seeds.  The Cardinals won four more games than the model suggested which tied the Padres for most in the NL – that is a bearish sentiment towards their chances against the Dodgers who were 11 games better during the regular season according to my model.

Next up let's examine the Top 99 players in my Runs Created model:


Rank
Player
Team
League
RC/GM
1
Victor Martinez
DET
AL
0.866
2
Jose Abreu
CHW
AL
0.858
3
Andrew McCutchen
PIT
NL
0.843
4
Mike Trout
LAA
AL
0.824
5
Giancarlo Stanton
MIA
NL
0.817
6
Paul Goldschmidt
ARI
NL
0.804
7
Michael Brantley
CLE
AL
0.768
8
Anthony Rizzo
CHC
NL
0.767
9
Jose Bautista
TOR
AL
0.761
10
Miguel Cabrera
DET
AL
0.758
11
Edwin Encarnacion
TOR
AL
0.724
12
J.D. Martinez
DET
AL
0.720
13
Jose Altuve
HOU
AL
0.718
14
Adrian Beltre
TEX
AL
0.713
15
Yasiel Puig
LAD
NL
0.694
16
Corey Dickerson
COL
NL
0.692
17
Steve Pearce
BAL
AL
0.690
18
Justin Morneau
COL
NL
0.681
19
Nelson Cruz
BAL
AL
0.680
20
David Ortiz
BOS
AL
0.678
21
Buster Posey
SFG
NL
0.672
22
Anthony Rendon
WSN
NL
0.670
23
Freddie Freeman
ATL
NL
0.669
24
Danny Santana
MIN
AL
0.669
25
Jonathan Lucroy
MIL
NL
0.664
26
Carlos Gomez
MIL
NL
0.662
27
Melky Cabrera
TOR
AL
0.661
28
Robinson Cano
SEA
AL
0.660
29
Jayson Werth
WSN
NL
0.655
30
Devin Mesoraco
CIN
NL
0.650
31
Nolan Arenado
COL
NL
0.646
32
Matt Kemp
LAD
NL
0.638
33
Justin Upton
ATL
NL
0.626
34
Josh Harrison
PIT
NL
0.621
35
Denard Span
WSN
NL
0.616
36
Adrian Gonzalez
LAD
NL
0.610
37
Albert Pujols
LAA
AL
0.609
38
Josh Donaldson
OAK
AL
0.604
39
Matt Holliday
STL
NL
0.602
40
Neil Walker
PIT
NL
0.599
41
Adam Jones
BAL
AL
0.597
42
Russell Martin
PIT
NL
0.596
43
Hunter Pence
SFG
NL
0.595
44
Starling Marte
PIT
NL
0.591
45
Todd Frazier
CIN
NL
0.591
46
Christian Yelich
MIA
NL
0.590
47
Adam LaRoche
WSN
NL
0.589
48
Starlin Castro
CHC
NL
0.587
49
Hanley Ramirez
LAD
NL
0.581
50
Ryan Braun
MIL
NL
0.579
51
Adam Eaton
CHW
AL
0.576
52
Charlie Blackmon
COL
NL
0.572
53
Kole Calhoun
LAA
AL
0.571
54
Lucas Duda
NYM
NL
0.567
55
Kyle Seager
SEA
AL
0.565
56
Daniel Murphy
NYM
NL
0.561
57
Dexter Fowler
HOU
AL
0.560
58
Jose Reyes
TOR
AL
0.560
59
Juan Uribe
LAD
NL
0.558
60
Carlos Santana
CLE
AL
0.557
61
Brian Dozier
MIN
AL
0.557
62
Torii Hunter
DET
AL
0.557
63
Matt Adams
STL
NL
0.553
64
Ian Kinsler
DET
AL
0.551
65
Ben Zobrist
TBR
AL
0.551
66
Alex Gordon
KCR
AL
0.551
67
Nick Markakis
BAL
AL
0.549
68
Mike Napoli
BOS
AL
0.544
69
Howie Kendrick
LAA
AL
0.543
70
Yoenis Cespedes
BOS
AL
0.540
71
Mike Morse
SFG
NL
0.538
72
Marcell Ozuna
MIA
NL
0.537
73
Yan Gomes
CLE
AL
0.537
74
Brock Holt
BOS
AL
0.537
75
Jacoby Ellsbury
NYY
AL
0.537
76
Evan Gattis
ATL
NL
0.536
77
Marlon Byrd
PHI
NL
0.536
78
Matt Carpenter
STL
NL
0.536
79
Trevor Plouffe
MIN
AL
0.535
80
Jhonny Peralta
STL
NL
0.534
81
Chris Carter
HOU
AL
0.532
82
Chase Utley
PHI
NL
0.532
83
Seth Smith
SDP
NL
0.531
84
Justin Turner
LAD
NL
0.529
85
Aramis Ramirez
MIL
NL
0.526
86
Brett Gardner
NYY
AL
0.523
87
Dustin Pedroia
BOS
AL
0.521
88
Ian Desmond
WSN
NL
0.521
89
Jason Heyward
ATL
NL
0.521
90
Bryce Harper
WSN
NL
0.514
91
Joe Mauer
MIN
AL
0.510
92
Pablo Sandoval
SFG
NL
0.510
93
Dee Gordon
LAD
NL
0.509
94
Adam Dunn
CHW
AL
0.509
95
Evan Longoria
TBR
AL
0.505
96
Conor Gillaspie
CHW
AL
0.502
97
Brandon Moss
OAK
AL
0.501
98
Martin Prado
NYY
AL
0.500
99
James Loney
TBR
AL
0.499

For purposes of this analysis I used a cut-off of 100 games played.

Here are how many each team has out of the 99 players listed above:

BOS
5
NYM
2
NYY
3
PHI
2
TOR
4
MIA
3
TB
3
ATL
4
BAL
4
WSN
6
CLE
3
CIN
2
KC
1
STL
4
CHW
4
CHC
2
DET
5
PIT
5
MIN
4
MIL
4
OAK
2
SD
1
LAA
4
SF
4
SEA
2
LAD
7
TEX
1
COL
4
HOU
3
ARZ
1
 



Thanks for reading our FINAL MLB 2014 installment.



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