Down on the Farm: The Boston Red Sox – July 2025

Down on the Farm: The Boston Red Sox – July 2025

The Boston Red Sox Top 30 Prospects!

Rank Name Position Level Age Projections
1 Roman Anthony CF MLB 21 136.7 wRC+, 0.268/0.376/0.461, 21 HR, 10 SB, 82 Runs, 74 RBI
2 Franklin Arias SS A+ 19 120.5 wRC+, 0.283/0.338/0.448, 18 HR, 13 SB, 69 Runs, 74 RBI
3 Marcelo Mayer SS MLB 22 116.3 wRC+, 0.258/0.326/0.450, 22 HR, 8 SB, 71 Runs, 79 RBI
4 Jhostynxon Garcia CF AAA 22 108.1 wRC+, 0.244/0.312/0.435, 23 HR, 6 SB, 77 Runs, 74 RBI
5 Blaze Jordan 3B AAA 22 111.2 wRC+, 0.270/0.322/0.433, 17 HR, 1 SB, 65 Runs, 74 RBI
6 Payton Tolle SP AA 22 3.86 ERA, 145 IP, 54 BB, 155 K, 9.6 K/9, 1.13 WHIP
7 Connelly Early SP AA 23 4.00 ERA, 143 IP, 64 BB, 144 K, 9.1 K/9, 1.29 WHIP
8 Mikey Romero SS AA 21 101.4 wRC+, 0.246/0.297/0.429, 21 HR, 5 SB, 73 Runs, 75 RBI
9 Luis Perales SP AA 21 3.87 ERA, 128 IP, 56 BB, 127 K, 8.9 K/9, 1.19 WHIP
10 Justin Gonzales 1B A 18 103.9 wRC+, 0.251/0.327/0.393, 15 HR, 10 SB, 68 Runs, 62 RBI
11 Jorge Rodriguez C CPX 19 95.1 wRC+, 0.243/0.299/0.399, 20 HR, 22 SB, 63 Runs, 67 RBI
12 Yophery Rodriguez CF A+ 19 97.9 wRC+, 0.235/0.320/0.376, 13 HR, 5 SB, 74 Runs, 59 RBI
13 Yoeilin Cespedes SS A 19 92.9 wRC+, 0.238/0.281/0.417, 21 HR, 5 SB, 68 Runs, 75 RBI
14 Enddy Azocar LF A 18 93.7 wRC+, 0.243/0.296/0.397, 17 HR, 15 SB, 65 Runs, 67 RBI
15 Brandon Clarke SP A+ 22 3.85 ERA, 101 IP, 44 BB, 101 K, 8.9 K/9, 1.22 WHIP
16 Avinson Pinto SS CPX 18 88.6 wRC+, 0.235/0.294/0.377, 15 HR, 36 SB, 71 Runs, 59 RBI
17 Allan Castro LF AA 22 94.6 wRC+, 0.229/0.313/0.373, 15 HR, 10 SB, 69 Runs, 61 RBI
18 Starlyn Nunez 3B A 19 91.1 wRC+, 0.238/0.286/0.401, 19 HR, 12 SB, 65 Runs, 70 RBI
19 Johanfran Garcia C A+ 20 93.5 wRC+, 0.234/0.297/0.394, 19 HR, 3 SB, 63 Runs, 68 RBI
20 Yordanny Monegro SP AA 22 4.08 ERA, 127 IP, 55 BB, 123 K, 8.7 K/9, 1.28 WHIP
21 Anderson Fermin CF CPX 18 92.7 wRC+, 0.222/0.327/0.342, 11 HR, 24 SB, 71 Runs, 50 RBI
22 Miguel Bleis CF A+ 21 87.1 wRC+, 0.227/0.285/0.386, 19 HR, 26 SB, 64 Runs, 68 RBI
23 Zach Ehrhard RF AA 22 91.4 wRC+, 0.232/0.317/0.353, 12 HR, 20 SB, 62 Runs, 56 RBI
24 James Tibbs III RF AA 22 91.0 wRC+, 0.225/0.307/0.367, 16 HR, 5 SB, 65 Runs, 60 RBI
25 Ilan Fernandez SS CPX 18 88.1 wRC+, 0.227/0.303/0.361, 15 HR, 20 SB, 62 Runs, 59 RBI
26 Freili Encarnacion SS A+ 20 86.2 wRC+, 0.236/0.274/0.399, 20 HR, 9 SB, 62 Runs, 71 RBI
27 Andruw Musett C A 19 91.8 wRC+, 0.237/0.311/0.365, 14 HR, 2 SB, 59 Runs, 59 RBI
28 Alex Binelas 1B AAA 25 85.6 wRC+, 0.212/0.286/0.377, 20 HR, 7 SB, 66 Runs, 67 RBI
29 Nathan Hickey C AAA 25 86.7 wRC+, 0.206/0.299/0.361, 18 HR, 1 SB, 63 Runs, 65 RBI
30 Tavano Baker CF CPX 18 83.2 wRC+, 0.224/0.290/0.360, 15 HR, 21 SB, 63 Runs, 59 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 Jorge Rodriguez Triston Casas Kristian Campbell Franklin Arias Alex Bregman Rob Refsnyder Roman Anthony Wilyer Abreu
Projected Backup Johanfran Garcia Justin Gonzales Romy Gonzalez Marcelo Mayer Blaze Jordan Allan Castro Jarren Duran Zach Ehrhard
Depth Connor Wong Alex Binelas Vaughn Grissom Mikey Romero Abraham Toro Enddy Azocar Jhostynxon Garcia James Tibbs III

Starting Pitchers

Projected #1 Garrett Crochet
Projected #2 Tanner Houck
Projected #3 Brayan Bello
Projected #4 Kyle Harrison
Projected #5 Payton Tolle
Depth Kutter Crawford
Depth Connelly Early
Depth Luis Perales
Depth Jordan Hicks
Depth Garrett Whitlock

Relief Pitchers

Projected Closer Aroldis Chapman
Projected Setup #1 Justin Slaten
Projected Setup #2 Justin Wilson
Next Up Nick Burdi
Next Up Greg Weissert
Next Up Jorge Alcala
Depth Zack Kelly
Depth Brennan Bernardino
Depth Liam Hendriks
Depth Lucas Luetge

Top prospects by tool!

Hit Power Speed
Franklin Arias – 60 Yoeilin Cespedes – 55 Avinson Pinto – 60
Blaze Jordan – 60 Mikey Romero – 55 Jhoan Peguero – 60
Roman Anthony – 60 Jhostynxon Garcia – 55 Raimundo De Los Santos – 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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