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Top Farm Systems (2028) - Printable Version

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Top Farm Systems (2028) - mattynokes - 04-17-2012

BASEBALL AMERICA 2028 TOP 100 PROSPECTS

For Reference:
Top Farm Systems (2027)

99-90 Elite:
- This player will be one of the best players at his position, top tier starter, or frontline closer

90-87 Well Above:
- This player will be a perennial All-Star, #1 starter (#2 starter on championship teams), or quality closer

87-84 Above Average:
- This player is the type that fields the majority of starting jobs in the majors, quality #2/3 starter, or second-tier closer

84-81 Average:
- This player is a solid to average everyday player on non-championship teams, most #4/5 starters, or set-up man

81-78 Below Average:
- This player is a fringe everyday player and is where you'll find most of your backups, some #5 starters, and most middle relievers

78-75 Well Below Average:
- This player is an up-and-down roster filler, situational relievers, and 25th players




RankTeamPlayer NamePosAgeOvrPeakScore
100PITBarnett, BradySP22788982.66
99BOSToll, NateLF22769082.69
98BALErvin, MatthewRP18689382.70
97SDPNorris, MichaelSP24828882.74
96ATLVargas, José3B22739382.79
95SEAWest, KentSP22759182.79
94DETBonaporte, JoséRF22788682.79
93CHWEnriquez, RicardoSP21689382.82
92ATLLenny, TaylorCF22739082.86
91ATLEpner, TimSP23828982.86
90LAAChasse, JasonSP22739382.92
89CLEDionn, ShawnSS19649482.93
88MILTocornal, CesarC20728783.06
87NYMMcCliverty, TravisRP23858583.13
86CHCRabelo, Ephraim2B23779383.16
85NYMPavilaitis, CameronSP20698883.34
84KCRScudder, KirkSP22758883.37
83SEAWadley, BorisRP21769283.39
82KCRDaley, BenoitRF19748483.43
81LADBawden, Martin1B22739083.53
80STLDoris, LarryRP22789083.55
79SEADuprey, TimSS24868683.59
78TEXPlakke, TomSS17618683.66
77PHIChaussé, Steve1B22719783.70
76TBRWilliams, EdgarSS17639383.70
75FLAKivlehan, Carmelo3B21718983.71
74CHWMárquez, Emmanuel3B21718783.71
73TORBarrundia, AlbertSP21769583.72
72TBRCheriton, BobbyCF23799083.75
71TEXMorales, ImbertCF19699183.81
70FLAWilson, CarmeloSP22779583.90
69BOSWest, PeterC22779383.92
68BALHelm, PeterRF20758883.92
67BALPollak, DanSS22759383.95
66SDPRay, PhilLF24818783.98
65PITLuck, BrianRP21759584.03
64NYYClément, EdwardSS22779084.05
63TORSipes, TerranceSP23828884.16
62PITBothwell, TomSP18719084.20
61CHWWadley, LukeSP22779384.20
60ARIRizzo, SimonSP24848884.20
59SEADaniels, TomSP20699584.22
58LADWilkinson, T.V.SP21788884.29
57LAACandelalia, AntonioLF23799084.31
56SDPDrouin, DarbyRF19669284.34
55SEAMetrock, TomSP20759284.39
54CINGowlett, Kelvin2B18659284.48
53LAABlank, TimSS23898984.50
52STLAvila, OscarCF21739284.62
51LAACases, MarcusLF22868684.64
50NYMBinford, JosephLF23838784.67
49DETO'Malley, James2B24849184.71
48OAKRhoades, ScottSP21778884.74
47STLSoutsos, MaxSP22778884.77
46HOURamming, MarcC21738784.78
45BOSWhite, SeanLF24829784.88
44NYMSampson, DaveSP25868884.91
43CHWMcLaughlin, MasonRP20788984.93
42ATLBickerstaff, Jeff3B18669484.98
41OAKWright, JoeRF23828585.04
40ATLSapagosa, JavierSP18699385.13
39LAAAquino, MarioSP20739585.15
38COLArmstrong, C.C.CF23848985.21
37BOSVerganor, AlbertoSP23829385.23
36NYMHenry, ToddCF23809585.23
35TORWolfson, NathanielSP23838885.38
34DETYoung, Jerry3B24798985.43
33PHIArikawa, RichSP23819385.71
32ATLAshe, GlennSP24888885.71
31LAAPena, JavySP20779085.74
30CHCHuebe, EnriqueLF18639785.85
29ATLBenavides, EdSS21779885.90
28PHIChaplin, NealC23809385.96
27LAACostello, RaySS18659486.10
26PITFowler, JoeySS23879286.20
25DETGravely, Lane3B24849286.20
24SDPMcKerlich, Travis3B21769386.27
23PITNicks, Mike1B18639586.53
22LAACarson, PeterCF23809786.58
21BOSTaylor, Will1B21729886.61
20MILCrum, BillySP21809486.64
19DETGillon, EarlSP23848786.67
18LADWrathall, Peter1B18699786.78
17TBRWilkie, DevinSP20838786.85
16NYMViloca, Etienne2B19759387.03
15STLMcComish, AdamSP23849087.12
14CHWLinn, JamesSP19759587.26
13OAKRodriguez, JamieSP20789487.71
12DETScifo, Glen1B22809787.75
11MINWakisaka, FujifusaSP24889387.77
10TEXMestas, NelsonLF22779787.85
9NYYMaes, VladimirSP22859387.85
8FLAWinegar, ScottSP22849488.04
7COLZlotnick, SeanSP22829488.15
6BALKingery, BrianSP20809888.20
5KCRIwahashi, UchimaroSP23849488.33
4KCRRaines, JimSP20819689.13
3TEXEtalis, RayRF20779589.40
2LAAMantle, JaySP20819790.24
1NYMBelovsky, MathewSP19829591.06



PositionTop 100Prospects
C412
1B622
2B422
3B713
SS1014
LF816
CF716
RF613
SP4261
RP617
Total100206

RankTeamTop 100ProspectsScore
30:SFG:012
29:WAS:0136
28:CIN:12187
27:MIN:11196
26:ARI:13212
25:CLE:14275
24:NYY:22341
23:MIL:23382
22:HOU:15457
21:COL:23463
20:FLA:33468
19:CHC:26476
18:OAK:35603
17:TOR:36637
16:TBR:36641
15:PHI:38743
14:KCR:46749
13:SDP:49793
12:LAD:38840
11:BAL:49898
10:SEA:510920
9:STL:411970
8:TEX:4101011
7:PIT:581028
6:CHW:5141035
5:ATL:7101060
4:BOS:5131260
3:NYM:7111392
2:LAA:9111608
1:DET:6171638



RE: Top Farm Systems (2028) - dlee2499 - 04-17-2012

awesome stuff matty


RE: Top Farm Systems (2028) - Peter - 04-18-2012

wow how did fowler fall so low


RE: Top Farm Systems (2028) - AndyP - 04-18-2012

I traded two of the top 20 in just the last week....


RE: Top Farm Systems (2028) - mattynokes - 04-18-2012

(04-18-2012, 11:35 AM)Peter Wrote: wow how did fowler fall so low

Two big things occurred after I did my list last year, winterball and spring training. With the potential for a +Predicted in WB and hitting their projected debut in ST, players have a stronger score this season.

I'd also be led to believe that his subpar arm and range hurt his score.


RE: Top Farm Systems (2028) - jhc54 - 04-20-2012

Hey I am just noticing this now, but the scale is very compact, there is nothing wrong with that. But it might be good to force some more variation between the players. It seems like a lot of them are clumped, not sure what the best way of doing that is.


RE: Top Farm Systems (2028) - mattynokes - 04-20-2012

(04-20-2012, 06:00 AM)jhc54 Wrote: Hey I am just noticing this now, but the scale is very compact, there is nothing wrong with that. But it might be good to force some more variation between the players. It seems like a lot of them are clumped, not sure what the best way of doing that is.

I'm really not sure what you're getting at. Is it the individual player scoring (i.e. the 85.??, 84.??, etc...) or the top teams scoring? or what?

I'll just speculate and see if I can get your concern nailed down. I would guess it's to do with the individual player scoring being so close. This really not a problem and maybe something I shouldn't list so people don't get so caught up in it. Consider that we're only looking at a top 100 of about 850 players that qualify.

My formula compares player vitals to what the MLB league average is per position in our league. Then it looks at the overall/peak rating and assigns a value to that. That gives me two values; one for vitals and one for rating. It averages the two and factors in age. Lastly it factors in whether or not the player has peaked. While peaked players can make the list, it's in my opinion that since this is a prospect list there should be some penalty for peaked players.

So in the end what you get is basically a true rating for each player. Like this year the #1 guy is a 91 while the #100 guy is an 82.6. For trade value that's significantly different. And if we look at KCR's two guys in the top 10. One has an 89.1 rating while the other is 88.3. There's not much variation and I don't see much difference in the players. Both are good and I would expect the younger, slightly higher peak guy to have a little more value.