Dynasty BaseballScouting the Statline

Scouting the Statline – Top 100 Prospects for Dynasty

For those new to this series, Scouting the Statline focuses on statistical analysis using using curves and major league equivalencies to generate peak projections. Peak projections put all minor and major leaguers on equal statistical footing for comparative purposes.

We are constantly looking to fine-tune our data models to deliver improved results, most recently adopting a new approach to the way we order our rankings. Please follow this link to view the full list of over 1,600 eligible minor leaguers! Once the regular season starts, this list is updated on a weekly basis, while our 2022 prospect leaderboard will be updated daily! Watch these lists evolve and much more at scoutthestatline.com.

What’s New

The order of our rankings is now based on z-score!

What is Z-Score?

Z-score helps determine a player’s value compared to the rest of the league. By totaling the z-scores across multiple stats we believe help indicate a player’s future fantasy value, we have created a new ranking methodology!

Why the Change?

This is really two-fold.

  1. Our rankings were previously based on peak projected wRC+.  We believe wRC+ is a useful real world “player value” data point, but fantasy players almost universally rely more heavily on stolen bases, which are not a part of the wRC+ calculation. We believe using z-scores helps give more credit to the speed demons out there.  We have to strike a careful balance, however, because there are some ridiculously fast players in the low minors that will never advance due to limited bats and we don’t want them to benefit too much from the change!
  2. Eventually, we will roll out pitching translations. In order to integrate them into our rankings, we cannot use wRC+ since it is a hitting stat.  However, since z-score is a standard comparative metric, it can be used for any set of data. Voila! While pitching translations are not yet ready, we have tested it with sample datasets and it passes the eye test.

At Scouting the Statline, we always believe the numbers are more important than the rank, but our new approach better aligns with traditional views of prospect rankings for fantasy..

The New Top 100

RankNameLast TeamAgeCareer PAPeak
wRC+
Peak
wOBA
Peak
BA
Peak
OBP
Peak
SLG
Peak
HR/600
Peak
SB/600
CSPeak
BB%
Peak
K%
Peak
BABIP
1Julio RodriguezSEA20962151.20.3870.2970.3770.507251209.8%16.9%0.327
2Anthony VolpeNYY20663136.20.3640.2340.3550.4782617012.9%19.4%0.252
3Jordan WalkerSTL19366138.20.3670.2870.3530.490221208.2%20.3%0.333
4CJ AbramsSDP20348124.30.3450.2850.3470.437112507.6%14.1%0.320
5Riley GreeneDET20809135.80.3630.2710.3580.4702411011.1%23.9%0.329
6Francisco AlvarezNYM19582137.70.3660.2460.3560.483327112.8%18.4%0.246
7Anthony GarciaNYY20394130.30.3550.2170.3260.4934115013.6%35.2%0.271
8Oneil CruzPIT221475128.60.3520.2700.3300.480251608.1%22.0%0.314
9Gabriel MorenoTOR21802137.60.3660.2890.3450.49925506.6%11.8%0.293
10Josh H. SmithTEX23492124.80.3460.2540.3670.4091519011.4%19.2%0.301
11Bobby Witt Jr.KCR21744121.20.3410.2490.3170.470281908.3%22.0%0.277
12Nick YorkeBOS19442130.70.3550.2790.3640.441198310.8%13.6%0.300
13Spencer TorkelsonDET21530134.00.3600.2340.3500.477304013.8%20.4%0.242
14Andy PagesLAD201029133.10.3590.2260.3440.483345012.0%23.1%0.241
15Khalil LeeNYM231885121.00.3400.2410.3710.3901518013.6%28.0%0.341
16Alek ThomasARI211273127.00.3500.2670.3470.447191009.8%18.2%0.306
17Brennen DavisCHC21692128.50.3520.2440.3480.456268011.0%23.9%0.288
18George ValeraCLE20599126.40.3490.2170.3550.4363010016.4%22.9%0.230
19Vidal BrujanTBR231720102.30.3110.2490.3250.376113509.6%14.9%0.279
20Zac VeenCOL19479114.70.3310.2400.3440.4041919912.8%23.6%0.293
21Josh LoweTBR231951113.30.3280.2410.3290.4182020011.2%25.4%0.301
22Jhonkensy NoelCLE19759125.60.3470.2640.3270.48432606.9%18.9%0.276
23Edouard JulienMIN22514116.60.3340.2190.3660.3811716016.8%29.0%0.310
24Everson PereiraNYY20478120.30.3390.2300.3120.4763511010.0%27.8%0.257
25Jarren DuranBOS241163108.10.3210.2580.3270.397152407.7%23.1%0.319
26Richie PalaciosCLE24618115.00.3310.2600.3560.385716011.6%18.8%0.321
27Triston CasasBOS21871122.80.3430.2380.3430.439255013.0%19.5%0.259
28Joey WiemerMIL22472114.70.3310.2340.3290.4282714010.6%24.5%0.275
29Robert Hassell IIISDP19516111.60.3260.2490.3440.3891417012.3%16.8%0.281
30Greg JonesTBR2353598.80.3060.2340.3210.366153109.3%30.8%0.330
31Miguel VargasLAD211330120.30.3390.2750.3420.42817708.5%14.6%0.299
32Ji-hwan BaePIT21904106.50.3180.2630.3420.36982109.8%18.9%0.320
33Orelvis MartinezTOR19614121.00.3400.2280.3040.49636408.3%20.7%0.230
34Dustin HarrisTEX21704113.60.3290.2670.3400.403171208.9%17.0%0.301
35Jairo PomaresSFG20557121.50.3410.2710.3150.47927304.9%23.1%0.314
36Josh JungTEX23540122.00.3420.2680.3370.44420207.8%22.7%0.326
37Chris GittensNYY271189123.30.3440.2350.3460.436280013.7%31.4%0.315
38Samad TaylorTOR221516100.80.3090.2240.3160.3851824010.5%24.7%0.279
39Felix ValerioMIL20992108.80.3220.2480.3400.3831115010.7%12.5%0.271
40Curtis MeadTBR20639116.00.3330.2660.3260.43617707.1%14.3%0.287
41Xavier EdwardsTBR211093104.20.3150.2810.3530.34032009.9%9.8%0.310
42Nick GonzalesPIT22369116.90.3340.2470.3290.43520529.8%27.6%0.322
43Drew WatersATL221754104.90.3160.2520.3200.393121808.1%26.6%0.335
44Tyler FreemanCLE221172111.90.3260.2820.3360.39771004.2%9.9%0.305
45Leo JimenezTOR20663117.30.3350.2630.3900.35274012.5%14.4%0.310
46Luis MatosSFG19781109.90.3230.2680.3190.423171205.7%11.0%0.278
47Nolan JonesCLE231726115.20.3310.2310.3500.397196014.5%28.2%0.308
48Kevin AlcantaraCHC18312112.40.3270.2530.3170.43022908.0%20.7%0.294
49Juan YepezSTL231537117.50.3350.2460.3230.44524218.9%20.1%0.272
50Vaughn GrissomATL20564110.90.3250.2600.3490.378129010.0%14.3%0.289
51Oswald PerazaNYY21122197.30.3040.2510.3140.372152407.2%18.8%0.291
52Otto LopezTOR221443105.00.3160.2800.3390.36751507.3%15.3%0.329
53Heriberto HernandezTBR21793113.80.3290.2160.3300.414235012.6%27.3%0.269
54Kevin SmithTOR241736106.60.3180.2330.2970.437251307.5%26.6%0.279
55Eddys LeonardLAD20901112.80.3280.2350.3290.418236010.2%22.9%0.277
56Cooper HummelARI261428115.30.3320.2320.3550.390163013.8%23.6%0.291
57Terrin VavraBAL24866108.90.3220.2400.3440.3781310012.4%20.9%0.292
58Nick PrattoKCR221784109.40.3220.2150.3110.429259011.3%29.1%0.267
59Diego CartayaLAD19344115.60.3320.2330.3220.443282010.1%21.9%0.254
60Seth BeerARI241265117.40.3350.2410.3430.41521017.8%20.7%0.279
61Vinnie PasquantinoKCR23761115.50.3320.2390.3230.442222010.0%16.5%0.251
62Adley RutschmanBAL23698114.90.3310.2380.3470.400192113.2%18.5%0.266
63Brayan RocchioCLE201055103.30.3130.2460.3120.399181506.9%16.4%0.271
64Bryson StottPHI23680110.40.3240.2490.3420.388157012.1%23.7%0.313
65Austin MartinTOR22418105.80.3170.2350.3750.320612013.3%20.2%0.301
66Brett AuerbachSFG22368100.30.3090.2250.3090.397221809.2%25.4%0.270
67Bryan LavastidaCLE22731107.50.3200.2540.3430.3721010010.9%18.6%0.301
68Steven KwanCLE23947110.70.3240.2690.3440.38310609.4%10.5%0.289
69Luis CampusanoSDP221248114.90.3310.2620.3340.41818108.7%15.8%0.286
70MJ MelendezKCR221620112.30.3270.2140.3030.454313211.0%26.8%0.238
71Austin ShentonSEA23598114.90.3310.2380.3270.42918009.6%24.3%0.295
72Jacob RobsonDET26192198.90.3060.2470.3400.342517011.5%32.6%0.394
73Shay WhitcombHOU2244498.80.3060.2350.2990.404231707.3%31.1%0.315
74Marco LucianoSFG19669107.60.3200.2190.3150.417267011.4%22.5%0.243
75Canaan Smith-NjigbaPIT221225104.00.3140.2410.3420.3591211012.9%23.5%0.307
76Luke BerryhillHOU23330111.70.3260.2250.3310.409212110.1%31.7%0.323
77Nolan GormanSTL211309109.90.3230.2440.3070.43726407.9%23.0%0.278
78Jonathan ArandaTBR231054111.40.3260.2600.3410.39212209.1%19.0%0.311
79Esteban QuirozTBR29779111.30.3250.2150.3310.406202012.3%27.1%0.277
80Jordan GroshansTOR21619111.80.3260.2620.3390.397131110.2%18.2%0.306
81Geraldo PerdomoARI211392100.70.3090.2280.3450.3411213013.1%17.1%0.263
82Jorge CaballeroMIA21493110.50.3240.2560.3570.365122212.5%27.6%0.362
83Aldenis SanchezTBR2273688.00.2890.2440.3270.31142709.4%19.1%0.306
84Michael Harris IIATL2063295.90.3020.2490.3200.35581808.4%16.6%0.291
85Keibert RuizLAD221492110.80.3250.2510.3200.42023108.4%7.3%0.237
86Mark VientosNYM211276110.80.3250.2380.3050.44629128.2%23.4%0.267
87Jeremy PenaHOU23790101.70.3110.2440.3180.383161107.5%21.9%0.295
88Jordan WestburgBAL22506103.30.3130.2340.3340.368129010.8%25.8%0.313
89Curtis TerryTEX241475110.20.3240.2360.3090.43826116.6%25.4%0.280
90Brett BatyNYM21613107.50.3200.2330.3360.386164012.3%25.8%0.297
91Jayce EasleyTEX2158777.10.2730.2010.3370.255538015.4%22.2%0.269
92Jose BarreroCIN231349101.20.3100.2490.3080.397161106.1%21.1%0.295
93Skye BoltOAK271566102.90.3120.2400.3270.379139010.5%28.5%0.332
94Jake McCarthyARI2383587.60.2890.2140.2880.369142608.5%25.4%0.270
95Fidel CastroCIN22677102.80.3120.2130.3060.409239010.0%35.0%0.312
96Jose MirandaMIN231873110.00.3230.2690.3190.41919115.4%12.9%0.284
97Peyton BurdickMIA24804106.40.3180.2060.3250.396235112.6%29.7%0.267
98Jorbit VivasLAD20928104.50.3150.2460.3290.38214708.0%12.6%0.262
99Rangel RaveloLAD291238110.50.3240.2680.3470.38410008.8%18.2%0.320
100Austin WellsNYY21469102.20.3110.2160.3250.378179011.8%24.9%0.273

Observations

  • The highest-end players remain mostly unchanged, a testament to the strong resume supporting their cases. After updating to the most current conditions, the top five prospects are Julio Rodriguez, Anthony Volpe, Jordan Walker, C.J. Abrams, and Riley Greene.
  • Felix Valerio, Vaughn Grissom, Bobby Witt, and Xavier Edwards all benefit under the new rankings thanks to their stolen base prowess.
  • Despite efforts to limit it, there are instances of low-level minor league speedsters that creep up in the ranks – beware of players that climb the rankings with wRC+ projections near 100 or lower. 100 is major league replacement level, meaning these players carry higher playing time risks!

 


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We are always open to feedback!

The Dynasty Guru: @DynastyGuru

Ross Jensen: @rossjensen12

Jordan Rosenblum: @rosenjordanblum

Scouting the Statlinestatlinescouting.com

The Author

Ross Jensen

Ross Jensen

Ross has been a passionate fantasy baseball player and League Manager for over a decade. Ross's approach is to build league powers through hunting down talented minor leaguers and targeting players on the verge of breakout based on a variety of metrics, statistical analysis, and assumptions.

5 Comments

  1. Todd Hedberg
    March 21, 2022 at 2:46 pm

    Whao, either this math is revolutionary or really flawed. Haven’t heard of many of these players…

    • March 21, 2022 at 2:52 pm

      Revolutionary, for sure :p

      Though honestly, while we want our rankings to make sense, we also don’t want to follow the general consensus to create something safe/vanilla. We hope that our data models can help reveal the players that are over-looked by conventional wisdom!

  2. Logan
    March 22, 2022 at 9:56 am

    Ross, this is a very interesting list. Definitely has given me some names I haven’t heard of that I need to keep an eye on. I’d be interested to know how you are using this list for yourself in leagues? Are you averaging your findings with that of the “general consensus” during drafts? Or are you taking this as your only guide when making picks?
    i.e., are you taking Nick Yorke over Bobby Witt Jr. if you have the opportunity to grab one of them?

    • March 23, 2022 at 3:54 pm

      The name of the game is to trade for the best prospects before they become “general consensus” best prospects (ie Anthony Volpe, who I received for Christhian Vaquero early last season), and trade the prospects that are failing to measure up before they fall out of “general consensus” favor (ie Royce Lewis, who I traded for CJ Abrams two seasons ago). The best way to do this is to follow our daily leaderboard and weekly updates during the season (at statlinescouting.com) to see who is rising and who is falling. In my experience, general consensus always lags a little, so it’s important to be ahead.

      Regarding Witt, he was a pretty big name right out of the gate, so he would have been a tough one to get. Yorke is a different story – I traded for him everywhere I could, generally for good discounts to his current general consensus ranking (which is still too low, imo). If I had the opportunity to pick either, right now I would still grab Witt because his perceived value is higher, which means you can get more in exchange for him. However, I think the two are a lot closer than most think, people haven’t fully caught on to Yorke’s true value yet!

      • March 23, 2022 at 4:39 pm

        In that scenario, you could snag Witt, trade him, then add Yorke. Or trade Witt for Yorke-plus.

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