Down on the Farm: The Colorado Rockies – June 2025

Down on the Farm: The Colorado Rockies – June 2025

The Colorado Rockies Top 30 Prospects!

Rank Name Position Level Age Projections
1 Robert Calaz RF A 19 109.0 wRC+, 0.249/0.311/0.441, 24 HR, 7 SB, 74 Runs, 76 RBI
2 Roldy Brito 2B CPX 18 103.4 wRC+, 0.248/0.322/0.399, 16 HR, 25 SB, 73 Runs, 61 RBI
3 Adael Amador 2B MLB 22 101.7 wRC+, 0.241/0.327/0.383, 16 HR, 23 SB, 63 Runs, 62 RBI
4 Carlos Renzullo 2B CPX 18 103.8 wRC+, 0.247/0.337/0.375, 13 HR, 19 SB, 66 Runs, 57 RBI
5 Jared Thomas LF A+ 21 101.0 wRC+, 0.251/0.324/0.385, 15 HR, 20 SB, 65 Runs, 58 RBI
6 Cole Carrigg CF AA 23 93.2 wRC+, 0.236/0.297/0.394, 16 HR, 34 SB, 80 Runs, 59 RBI
7 Ryan Ritter SS MLB 24 97.7 wRC+, 0.229/0.312/0.389, 18 HR, 9 SB, 72 Runs, 64 RBI
8 Jeff Criswell SP MLB 25 3.86 ERA, 114 IP, 42 BB, 109 K, 8.6 K/9, 1.15 WHIP
9 Yanquiel Fernandez RF AAA 22 97.6 wRC+, 0.250/0.294/0.417, 20 HR, 1 SB, 63 Runs, 74 RBI
10 Kyle Karros 3B AA 22 98.4 wRC+, 0.249/0.329/0.364, 10 HR, 4 SB, 64 Runs, 55 RBI
11 Welinton Herrera RP AA 21 3.44 ERA, 39 IP, 18 BB, 43 K, 10.0 K/9, 1.21 WHIP
12 Zac Veen LF MLB 23 89.4 wRC+, 0.228/0.305/0.363, 14 HR, 31 SB, 66 Runs, 58 RBI
13 Wilder Dalis 3B CPX 18 90.5 wRC+, 0.235/0.301/0.375, 15 HR, 17 SB, 68 Runs, 58 RBI
14 Sean Sullivan SP AA 22 4.30 ERA, 158 IP, 43 BB, 127 K, 7.2 K/9, 1.11 WHIP
15 Jaden Hill RP MLB 25 3.69 ERA, 57 IP, 24 BB, 61 K, 9.6 K/9, 1.22 WHIP
16 Carson Palmquist SP AAA 23 4.33 ERA, 145 IP, 62 BB, 134 K, 8.3 K/9, 1.20 WHIP
17 Seth Halvorsen RP MLB 25 3.57 ERA, 33 IP, 15 BB, 34 K, 9.4 K/9, 1.22 WHIP
18 Ashly Andujar SS CPX 17 88.4 wRC+, 0.252/0.295/0.376, 14 HR, 8 SB, 56 Runs, 58 RBI
19 Bryant Betancourt C AA 21 84.6 wRC+, 0.227/0.294/0.360, 15 HR, 6 SB, 57 Runs, 59 RBI
20 Sterlin Thompson LF AAA 24 83.0 wRC+, 0.225/0.292/0.356, 13 HR, 10 SB, 65 Runs, 57 RBI
21 Jace Kaminska SP A 22 4.51 ERA, 160 IP, 36 BB, 119 K, 6.7 K/9, 1.15 WHIP
22 Roynier Hernandez 3B A 20 86.8 wRC+, 0.241/0.314/0.338, 8 HR, 5 SB, 60 Runs, 47 RBI
23 Jesus Freitez C CPX 19 81.6 wRC+, 0.226/0.291/0.352, 12 HR, 13 SB, 64 Runs, 56 RBI
24 Warming Bernabel 3B AAA 23 83.4 wRC+, 0.249/0.287/0.366, 12 HR, 8 SB, 53 Runs, 59 RBI
25 Braxton Fulford C MLB 26 81.1 wRC+, 0.211/0.290/0.350, 15 HR, 6 SB, 63 Runs, 59 RBI
26 Derek Bernard LF A 19 77.5 wRC+, 0.222/0.276/0.357, 14 HR, 16 SB, 61 Runs, 60 RBI
27 Tommy Hopfe LF A 22 79.5 wRC+, 0.218/0.295/0.336, 12 HR, 15 SB, 58 Runs, 54 RBI
28 Drew Romo C MLB 23 79.4 wRC+, 0.238/0.280/0.360, 12 HR, 9 SB, 60 Runs, 57 RBI
29 Benny Montgomery CF AA 22 78.4 wRC+, 0.223/0.285/0.347, 13 HR, 11 SB, 58 Runs, 55 RBI
30 Jeremy Ciriaco N/A CPX 18 78.0 wRC+, 0.225/0.288/0.341, 12 HR, 11 SB, 56 Runs, 55 RBI

Projected organization depth!

Below are the top projected players at peak for each position at the MLB level.

C 1B 2B SS 3B LF CF RF
Projected Starter Bryant Betancourt Michael Toglia Carlos Renzullo Ezequiel Tovar Ryan McMahon Jared Thomas Tyler Freeman Robert Calaz
Projected Backup Jesus Freitez Aidan Longwell Roldy Brito Ryan Ritter Kyle Karros Jordan Beck Mickey Moniak Hunter Goodman
Depth Braxton Fulford Owen Miller Adael Amador Ashly Andujar Wilder Dalis Sam Hilliard Cole Carrigg Yanquiel Fernandez

Starting Pitchers

Projected #1 Tyler Dollander
Projected #2 Jeff Criswell
Projected #3 Sean Sullivan
Projected #4 Ryan Feltner
Projected #5 Carson Palmquist
Depth Jace Kaminska
Depth Kyle Freeland
Depth German Marquez
Depth McCade Brown
Depth Peter Lambert

Relief Pitchers

Projected Closer Jake Bird
Projected Setup #1 Welinton Herrera
Projected Setup #2 Jaden Hill
Next Up Seth Halvorsen
Next Up Victor Vodnik
Next Up Riley Pint
Depth Juan Mejia
Depth Angel Chivilli
Depth Matt Carasiti
Depth Jefry Yan

Top prospects by tool!

Hit Power Speed
Jared Thomas – 50 Robert Calaz – 55 Braiden Ward – 70
Carlos Renzullo – 50 Jared Thomas – 50 Caleb Hobson – 60
Roldy Brito – 50 Roldy Brito – 50 Cole Carrigg – 60

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What are Scout the Statline Peak Projections?
Scout the Statline Peak Projections are based entirely on data analysis. Combining performance data with advanced statistics, translating the results to an equalized playing field (the MLB level), and scaling the results up to a player’s peak ages, allows us to instantly compare thousands of players across different ages, environments, and organizations! While the results can often be quite different than you might find from other scout-based analysis, peak projections provide a bias-free look at players with all the best data available, based on sound data science practices!

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