Down on the Farm: The Pittsburgh Pirates – July 2025

Down on the Farm: The Pittsburgh Pirates – October 2025

The Pittsburgh Pirates Top 30 Prospects!

Rank Name Position Level Age Projections
1 Edward Florentino 1B A 18 125.9 wRC+, 0.260/0.342/0.466, 25 HR, 27 SB, 78 Runs, 80 RBI
2 Konnor Griffin SS A+ 19 119.7 wRC+, 0.274/0.333/0.453, 21 HR, 39 SB, 71 Runs, 74 RBI
3 Termarr Johnson 2B AA 21 110.8 wRC+, 0.243/0.346/0.393, 17 HR, 15 SB, 68 Runs, 62 RBI
4 Esmerlyn Valdez 1B AA 21 107.4 wRC+, 0.238/0.311/0.434, 25 HR, 1 SB, 67 Runs, 80 RBI
5 Bubba Chandler SP AAA 22 3.88 ERA, 138 IP, 62 BB, 138 K, 9.0 K/9, 1.24 WHIP
6 Axiel Plaz C A 19 103.3 wRC+, 0.233/0.306/0.424, 24 HR, 2 SB, 64 Runs, 78 RBI
7 Nick Yorke 2B MLB 23 103.2 wRC+, 0.256/0.322/0.398, 15 HR, 15 SB, 68 Runs, 61 RBI
8 Wyatt Sanford SS A 19 92.0 wRC+, 0.228/0.313/0.362, 14 HR, 41 SB, 66 Runs, 56 RBI
9 Johan De Los Santos SS DSL 16 93.5 wRC+, 0.241/0.316/0.364, 11 HR, 34 SB, 67 Runs, 54 RBI
10 Victor Marquez C DSL 17 94.5 wRC+, 0.225/0.320/0.363, 15 HR, 21 SB, 64 Runs, 58 RBI
11 Thomas Harrington SP AAA 22 4.24 ERA, 162 IP, 36 BB, 124 K, 6.9 K/9, 1.08 WHIP
12 Braxton Ashcraft SP MLB 25 3.98 ERA, 114 IP, 38 BB, 103 K, 8.1 K/9, 1.20 WHIP
13 Matt Gorski CF MLB 27 86.4 wRC+, 0.220/0.265/0.413, 25 HR, 17 SB, 65 Runs, 76 RBI
14 Omar Alfonzo C AA 21 95.9 wRC+, 0.229/0.317/0.372, 17 HR, 1 SB, 62 Runs, 62 RBI
15 Keiner Delgado SS A+ 21 90.3 wRC+, 0.230/0.305/0.368, 16 HR, 17 SB, 60 Runs, 61 RBI
16 Duce Gourson 2B AA 22 87.7 wRC+, 0.227/0.307/0.353, 12 HR, 33 SB, 64 Runs, 56 RBI
17 Braxton Ashcraft SP AAA 24 4.14 ERA, 128 IP, 31 BB, 106 K, 7.4 K/9, 1.14 WHIP
18 Hunter Barco SP AAA 24 4.11 ERA, 119 IP, 52 BB, 116 K, 8.7 K/9, 1.25 WHIP
19 Ronny Simon 2B MLB 25 86.5 wRC+, 0.233/0.294/0.368, 13 HR, 22 SB, 65 Runs, 58 RBI
20 Reinold Navarro SP A 18 3.86 ERA, 83 IP, 51 BB, 92 K, 10.0 K/9, 1.34 WHIP
21 Will Taylor CF A+ 22 85.2 wRC+, 0.220/0.297/0.357, 15 HR, 16 SB, 63 Runs, 59 RBI
22 Jack Brannigan SS AA 24 84.4 wRC+, 0.211/0.294/0.359, 18 HR, 11 SB, 64 Runs, 61 RBI
23 Mike Burrows SP MLB 25 4.22 ERA, 126 IP, 48 BB, 120 K, 8.5 K/9, 1.20 WHIP
24 Yordany De Los Santos SS A 20 79.2 wRC+, 0.230/0.276/0.364, 15 HR, 37 SB, 58 Runs, 60 RBI
25 Tsung-Che Cheng SS MLB 23 83.6 wRC+, 0.225/0.304/0.339, 9 HR, 21 SB, 67 Runs, 50 RBI
26 Kervin Pichardo 2B AAA 23 83.6 wRC+, 0.219/0.292/0.359, 16 HR, 4 SB, 62 Runs, 59 RBI
27 Tony Blanco Jr. DH A 20 81.5 wRC+, 0.219/0.278/0.372, 19 HR, 6 SB, 61 Runs, 64 RBI
28 Richard Ramirez C A 19 83.2 wRC+, 0.224/0.286/0.367, 16 HR, 2 SB, 60 Runs, 63 RBI
29 Jhonny Severino 3B A 20 76.1 wRC+, 0.215/0.253/0.389, 22 HR, 11 SB, 62 Runs, 73 RBI
30 Billy Cook RF MLB 26 78.8 wRC+, 0.217/0.279/0.358, 16 HR, 17 SB, 62 Runs, 60 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 Henry Davis Edward Florentino Termarr Johnson Oneil Cruz Jared Triolo Bryan Reynolds Jack Suwinski Tommy Pham
Projected Backup Axiel Plaz Esmerlyn Valdez Nick Yorke Konnor Griffin Ke’Bryan Hayes Alexander Canario Matt Gorski DJ Stewart
Depth Joey Bart Spencer Horwitz Nick Gonzales Johan De Los Santos Kendrick Herrera Nick Solak Will Taylor Billy Cook

Starting Pitchers

Projected #1 Paul Skenes
Projected #2 Jared Jones
Projected #3 Mitch Keller
Projected #4 Bubba Chandler
Projected #5 Johan Oviedo
Depth Thomas Harrington
Depth Braxton Ashcraft
Depth Hunter Barco
Depth Reinold Navarro
Depth Mike Burrows

Relief Pitchers

Projected Closer David Bednar
Projected Setup #1 Ben Heller
Projected Setup #2 Ryan Borucki
Next Up Caleb Ferguson
Next Up Yohan Ramírez
Next Up Colin Holderman
Depth Justin Lawrence
Depth Dennis Santana
Depth Tim Mayza
Depth Kyle Nicolas

Top prospects by tool!

Hit Power Speed
Konnor Griffin – 60 Edward Florentino – 60 Armstrong Muhoozi – 70
Edward Florentino – 60 Esmerlyn Valdez – 60 Fredderick Ovalle – 70
Nick Yorke – 55 Matt Gorski – 60 Darell Morel – 70

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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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