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

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

The Boston Red Sox Top 30 Prospects!

Rank Name Position Level Age Projections
1 Roman Anthony CF AAA 21 141.0 wRC+, 0.275/0.379/0.475, 21 HR, 10 SB, 83 Runs, 75 RBI
2 Franklin Arias SS A+ 19 124.8 wRC+, 0.289/0.345/0.456, 18 HR, 14 SB, 71 Runs, 74 RBI
3 Marcelo Mayer SS MLB 22 112.1 wRC+, 0.256/0.324/0.434, 20 HR, 8 SB, 69 Runs, 76 RBI
4 Jhostynxon Garcia CF AAA 22 106.8 wRC+, 0.245/0.311/0.432, 22 HR, 8 SB, 76 Runs, 74 RBI
5 Blaze Jordan 3B AA 22 109.7 wRC+, 0.268/0.321/0.429, 18 HR, 1 SB, 64 Runs, 73 RBI
6 Gerardo Rodriguez C A 19 109.9 wRC+, 0.256/0.337/0.403, 16 HR, 3 SB, 69 Runs, 62 RBI
7 Luis Perales SP AA 21 3.87 ERA, 128 IP, 56 BB, 127 K, 8.9 K/9, 1.19 WHIP
8 Mikey Romero SS AA 21 99.1 wRC+, 0.242/0.295/0.422, 20 HR, 5 SB, 73 Runs, 74 RBI
9 Brainer Bonaci SS AA 21 101.4 wRC+, 0.248/0.322/0.389, 14 HR, 11 SB, 67 Runs, 61 RBI
10 Anderson Fermin CF CPX 18 98.1 wRC+, 0.222/0.339/0.348, 12 HR, 30 SB, 72 Runs, 50 RBI
11 Justin Gonzales 1B A 18 101.1 wRC+, 0.242/0.329/0.377, 14 HR, 10 SB, 67 Runs, 58 RBI
12 Yordanny Monegro SP AA 22 3.98 ERA, 129 IP, 56 BB, 130 K, 9.1 K/9, 1.27 WHIP
13 Johanfran Garcia C A 20 99.7 wRC+, 0.241/0.309/0.403, 19 HR, 0 SB, 66 Runs, 68 RBI
14 Brandon Clarke SP A+ 22 3.82 ERA, 107 IP, 44 BB, 105 K, 8.8 K/9, 1.20 WHIP
15 Yophery Rodriguez CF A+ 19 100.0 wRC+, 0.237/0.323/0.382, 13 HR, 5 SB, 76 Runs, 59 RBI
16 Connelly Early SP AA 23 4.07 ERA, 138 IP, 63 BB, 141 K, 9.2 K/9, 1.29 WHIP
17 Yoeilin Cespedes SS A 19 95.2 wRC+, 0.241/0.287/0.419, 21 HR, 6 SB, 67 Runs, 75 RBI
18 Starlyn Nunez 3B A 19 94.4 wRC+, 0.239/0.290/0.410, 20 HR, 8 SB, 68 Runs, 71 RBI
19 Tavano Baker CF CPX 18 95.5 wRC+, 0.234/0.307/0.387, 17 HR, 11 SB, 69 Runs, 63 RBI
20 Enddy Azocar LF A 18 93.9 wRC+, 0.246/0.303/0.387, 14 HR, 15 SB, 66 Runs, 62 RBI
21 Jorge Rodriguez C CPX 19 88.1 wRC+, 0.232/0.295/0.373, 16 HR, 26 SB, 63 Runs, 61 RBI
22 Freili Encarnacion SS A 20 87.9 wRC+, 0.240/0.276/0.403, 20 HR, 10 SB, 61 Runs, 72 RBI
23 Allan Castro LF AA 22 91.2 wRC+, 0.224/0.310/0.363, 13 HR, 9 SB, 69 Runs, 59 RBI
24 Payton Tolle SP A+ 22 4.16 ERA, 134 IP, 49 BB, 134 K, 8.9 K/9, 1.16 WHIP
25 Miguel Bleis CF A+ 21 84.2 wRC+, 0.226/0.282/0.377, 17 HR, 28 SB, 63 Runs, 65 RBI
26 Nathan Hickey C AAA 25 88.4 wRC+, 0.206/0.302/0.364, 19 HR, 2 SB, 62 Runs, 66 RBI
27 Andruw Musett C A 19 90.9 wRC+, 0.232/0.309/0.363, 15 HR, 2 SB, 60 Runs, 59 RBI
28 Avinson Pinto SS CPX 18 81.9 wRC+, 0.234/0.284/0.364, 13 HR, 38 SB, 64 Runs, 57 RBI
29 Alex Binelas 1B AAA 25 83.0 wRC+, 0.208/0.283/0.371, 20 HR, 9 SB, 65 Runs, 66 RBI
30 Richard Fitts SP MLB 25 4.47 ERA, 163 IP, 50 BB, 127 K, 7.0 K/9, 1.20 WHIP

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 Gerardo Rodriguez Justin Gonzales Marvin Alcantara Franklin Arias Blaze Jordan Enddy Azocar Roman Anthony Zach Ehrhard
Projected Backup Johanfran Garcia Drew Ehrhard Nick Sogard Marcelo Mayer Starlyn Nunez Allan Castro Jhostynxon Garcia Natanael Yuten
Depth Andruw Musett Alex Binelas Fraymi De Leon Brainer Bonaci Franyer Noria Andy Lugo Yophery Rodriguez Narciso Crook

Starting Pitchers

Projected #1 Garrett Crochet
Projected #2 Tanner Houck
Projected #3 Kutter Crawford
Projected #4 Brayan Bello
Projected #5 Luis Perales
Depth Yordanny Monegro
Depth Brandon Clarke
Depth Garrett Whitlock
Depth Connelly Early
Depth Payton Tolle

Relief Pitchers

Projected Closer Aroldis Chapman
Projected Setup #1 Justin Slaten
Projected Setup #2 Justin Wilson
Next Up Greg Weissert
Next Up Brennan Bernardino
Next Up Nick Burdi
Depth Michael Fulmer
Depth Austin Adams
Depth Liam Hendriks
Depth Zack Kelly

Top prospects by tool!

Hit Power Speed
Franklin Arias – 70 Starlyn Nunez – 55 Avinson Pinto – 70
Roman Anthony – 70 Yoeilin Cespedes – 55 Kier Meredith – 70
Blaze Jordan – 60 Mikey Romero – 55 Jorge Rodriguez – 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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