Down on the Farm: The San Diego Padres – May 2025

Down on the Farm: The San Diego Padres – May 2025

The San Diego Padres Top 30 Prospects!

Rank Name Position Level Age Projections
1 Victor Figueroa 1B A 21 124.4 wRC+, 0.264/0.329/0.480, 28 HR, 4 SB, 80 Runs, 83 RBI
2 Leo De Vries SS A+ 18 122.8 wRC+, 0.255/0.337/0.461, 24 HR, 11 SB, 79 Runs, 80 RBI
3 Ethan Salas C AA 19 98.2 wRC+, 0.237/0.313/0.390, 15 HR, 9 SB, 66 Runs, 66 RBI
4 Jack Mathey N/A AA 21 97.2 wRC+, 0.236/0.314/0.384, 17 HR, 11 SB, 68 Runs, 62 RBI
5 Romeo Sanabria 1B AA 23 97.7 wRC+, 0.245/0.315/0.385, 15 HR, 1 SB, 60 Runs, 64 RBI
6 Eguy Rosario 3B MLB 25 90.7 wRC+, 0.228/0.296/0.385, 17 HR, 18 SB, 65 Runs, 67 RBI
7 Cobb Hightower N/A A 20 95.3 wRC+, 0.235/0.321/0.364, 13 HR, 6 SB, 68 Runs, 55 RBI
8 Tirso Ornelas LF N/A 93.3 wRC+, 0.245/0.305/0.381, 14 HR, 4 SB, 60 Runs, 62 RBI
9 Rosman Verdugo 3B A+ 20 86.5 wRC+, 0.215/0.289/0.376, 18 HR, 6 SB, 65 Runs, 67 RBI
10 Yonathan Perlaza LF AAA 26 85.9 wRC+, 0.223/0.290/0.372, 15 HR, 9 SB, 63 Runs, 67 RBI
11 Ryan Jackson 3B A 23 89.6 wRC+, 0.217/0.329/0.325, 10 HR, 9 SB, 65 Runs, 48 RBI
12 Kasen Wells N/A A 21 82.3 wRC+, 0.230/0.299/0.342, 10 HR, 33 SB, 62 Runs, 51 RBI
13 Albert Fabian RF A+ 23 83.4 wRC+, 0.218/0.279/0.379, 20 HR, 4 SB, 58 Runs, 70 RBI
14 Joshua Mears RF AA 24 76.5 wRC+, 0.187/0.260/0.379, 27 HR, 14 SB, 61 Runs, 76 RBI
15 Trenton Brooks N/A MLB 29 86.9 wRC+, 0.224/0.309/0.345, 12 HR, 5 SB, 60 Runs, 56 RBI
16 Tirso Ornelas N/A MLB 25 86.5 wRC+, 0.238/0.301/0.357, 12 HR, 5 SB, 58 Runs, 57 RBI
17 Tyson Neighbors RP A+ 22 3.59 ERA, 40 IP, 17 BB, 46 K, 10.3 K/9, 1.13 WHIP
18 Robert Perez Jr. 1B AA 25 79.6 wRC+, 0.209/0.288/0.348, 17 HR, 7 SB, 59 Runs, 60 RBI
19 Marcos Castanon 3B AA 26 79.9 wRC+, 0.217/0.276/0.368, 18 HR, 1 SB, 54 Runs, 67 RBI
20 Braedon Karpathios RF A+ 22 82.2 wRC+, 0.199/0.312/0.321, 12 HR, 3 SB, 64 Runs, 52 RBI
21 Brandon Valenzuela C AAA 24 82.6 wRC+, 0.222/0.299/0.342, 12 HR, 1 SB, 58 Runs, 55 RBI
22 Bradgley Rodriguez RP AA 21 3.74 ERA, 41 IP, 19 BB, 41 K, 9.1 K/9, 1.23 WHIP
23 Brandon Lockridge LF MLB 28 75.6 wRC+, 0.230/0.293/0.321, 7 HR, 42 SB, 59 Runs, 44 RBI
24 Omar Cruz SP AAA 25 4.03 ERA, 79 IP, 34 BB, 75 K, 8.5 K/9, 1.23 WHIP
25 Eddy Beltre N/A CPX 20 76.7 wRC+, 0.209/0.294/0.324, 12 HR, 21 SB, 58 Runs, 52 RBI
26 Jose Espada SP MLB 28 3.86 ERA, 65 IP, 28 BB, 71 K, 9.9 K/9, 1.15 WHIP
27 Moises Gomez RF AAA 26 74.7 wRC+, 0.205/0.264/0.364, 20 HR, 4 SB, 59 Runs, 67 RBI
28 Kale Fountain N/A CPX 19 75.9 wRC+, 0.215/0.288/0.331, 12 HR, 21 SB, 59 Runs, 53 RBI
29 Jack Costello 1B A+ 24 76.0 wRC+, 0.220/0.273/0.356, 16 HR, 4 SB, 56 Runs, 61 RBI
30 Francisco Acuna SS AAA 25 75.6 wRC+, 0.215/0.288/0.330, 11 HR, 14 SB, 57 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 Ethan Salas Victor Figueroa Nerwilian Cedeno Leo De Vries Eguy Rosario Tirso Ornelas Bryce Johnson Albert Fabian
Projected Backup Brandon Valenzuela Romeo Sanabria Ripken Reyes Francisco Acuna Ryan Jackson Yonathan Perlaza Donte Grant Braedon Karpathios
Depth Oswaldo Linares Robert Perez Jr. Jarryd Dale Maikol Munoz Rosman Verdugo Brandon Lockridge Kai Roberts Joshua Mears

Starting Pitchers

Projected #1 Dylan Cease
Projected #2 Michael King
Projected #3 Joe Musgrove
Projected #4 Nick Pivetta
Projected #5 Yu Darvish
Depth Stephen Kolek
Depth Matt Waldron
Depth Omar Cruz
Depth Jose Espada
Depth Jhony Brito

Relief Pitchers

Projected Closer Jason Adam
Projected Setup #1 Jeremiah Estrada
Projected Setup #2 Robert Suarez
Next Up Adrian Morejon
Next Up Tyson Neighbors
Next Up Bradgley Rodriguez
Depth Wandy Peralta
Depth Yuki Matsui
Depth Reiss Knehr
Depth Francis Pena

Top prospects by tool!

Hit Power Speed
Victor Figueroa – 60 Victor Figueroa – 60 Brandon Lockridge – 70
Leo De Vries – 55 Joshua Mears – 60 Forrest Wall – 70
Jack Mathey – 50 Moises Gomez – 55 Ray-Patrick Didder – 60

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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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