Down on the Farm: The Atlanta Braves – June 2025

Down on the Farm: The Atlanta Braves – June 2025

The Atlanta Braves Top 30 Prospects!

Rank Name Position Level Age Projections
1 Nacho Alvarez Jr. 3B MLB 22 109.6 wRC+, 0.259/0.355/0.372, 10 HR, 14 SB, 68 Runs, 53 RBI
2 Owen Carey CF A 18 102.1 wRC+, 0.261/0.316/0.402, 14 HR, 11 SB, 63 Runs, 66 RBI
3 Owen Murphy SP A+ 20 4.11 ERA, 152 IP, 48 BB, 142 K, 8.4 K/9, 1.09 WHIP
4 Cam Caminiti SP A 18 3.91 ERA, 115 IP, 40 BB, 98 K, 7.7 K/9, 1.21 WHIP
5 John Gil SS A 19 91.7 wRC+, 0.243/0.313/0.360, 11 HR, 44 SB, 58 Runs, 57 RBI
6 Elian Cortorreal SS CPX 19 94.1 wRC+, 0.222/0.325/0.353, 14 HR, 8 SB, 66 Runs, 55 RBI
7 Manuel Dos Passos C CPX 18 89.9 wRC+, 0.229/0.302/0.372, 15 HR, 9 SB, 63 Runs, 62 RBI
8 Geraldo Quintero LF AA 23 86.3 wRC+, 0.227/0.305/0.351, 11 HR, 31 SB, 71 Runs, 51 RBI
9 Jesse Franklin V LF AA 25 83.3 wRC+, 0.213/0.274/0.386, 22 HR, 19 SB, 62 Runs, 71 RBI
10 Ethan Workinger LF AA 23 88.6 wRC+, 0.231/0.287/0.389, 18 HR, 3 SB, 65 Runs, 67 RBI
11 Eric Hartman CF A 19 84.5 wRC+, 0.218/0.300/0.350, 13 HR, 31 SB, 68 Runs, 56 RBI
12 Will King C CPX 21 88.2 wRC+, 0.226/0.312/0.347, 13 HR, 9 SB, 62 Runs, 53 RBI
13 Austin Machado C A+ 24 90.0 wRC+, 0.228/0.327/0.332, 9 HR, 8 SB, 64 Runs, 47 RBI
14 Javier Valdes C AA 26 87.4 wRC+, 0.217/0.305/0.355, 16 HR, 0 SB, 62 Runs, 59 RBI
15 Luis Guanipa CF A 19 84.9 wRC+, 0.232/0.293/0.362, 14 HR, 12 SB, 62 Runs, 57 RBI
16 Landon Stephens 1B AA 26 79.4 wRC+, 0.186/0.274/0.368, 25 HR, 1 SB, 60 Runs, 72 RBI
17 Carlos D. Rodriguez CF AAA 24 88.2 wRC+, 0.261/0.319/0.335, 3 HR, 14 SB, 63 Runs, 39 RBI
18 Colin Burgess C AA 24 82.4 wRC+, 0.225/0.288/0.360, 16 HR, 7 SB, 61 Runs, 59 RBI
19 Juan Mateo SS CPX 18 82.8 wRC+, 0.237/0.293/0.353, 12 HR, 9 SB, 57 Runs, 55 RBI
20 Isaiah Drake CF A 19 76.1 wRC+, 0.214/0.285/0.336, 11 HR, 33 SB, 69 Runs, 50 RBI
21 Junior Garcia LF A 19 81.0 wRC+, 0.220/0.293/0.346, 14 HR, 8 SB, 61 Runs, 55 RBI
22 David McCabe DH AA 25 83.1 wRC+, 0.213/0.305/0.336, 13 HR, 1 SB, 59 Runs, 55 RBI
23 Luis Parababire C A 19 81.5 wRC+, 0.208/0.306/0.328, 12 HR, 5 SB, 62 Runs, 53 RBI
24 J.P. Martínez N/A MLB 29 74.2 wRC+, 0.206/0.290/0.320, 10 HR, 37 SB, 66 Runs, 48 RBI
25 Dylan Dodd SP MLB 27 4.42 ERA, 134 IP, 38 BB, 104 K, 7.0 K/9, 1.18 WHIP
26 Colby Jones 2B AA 21 73.8 wRC+, 0.219/0.292/0.316, 8 HR, 41 SB, 59 Runs, 46 RBI
27 Hurston Waldrep SP MLB 23 4.60 ERA, 146 IP, 76 BB, 126 K, 7.7 K/9, 1.41 WHIP
28 Drew Compton 1B AA 24 81.1 wRC+, 0.227/0.302/0.332, 10 HR, 1 SB, 56 Runs, 52 RBI
29 Tyler Tolve C AA 24 74.0 wRC+, 0.206/0.263/0.363, 19 HR, 3 SB, 61 Runs, 66 RBI
30 Josnaider Orellana C A 20 77.1 wRC+, 0.216/0.285/0.340, 14 HR, 6 SB, 59 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 Drake Baldwin Matt Olson Ozzie Albies Elian Cortorreal Austin Riley Jarred Kelenic Ronald Acuña Jr. Eli White
Projected Backup Sean Murphy Garrett Cooper Eddy Alvarez John Gil Nacho Alvarez Jr. Jurickson Profar Michael Harris II Skye Bolt
Depth Austin Machado Drew Compton Whit Merrifield Juan Mateo Charles Leblanc Alex Verdugo Owen Carey Jake Marisnick

Starting Pitchers

Projected #1 Chris Sale
Projected #2 Spencer Strider
Projected #3 Spencer Schwellenbach
Projected #4 Reynaldo López
Projected #5 AJ Smith-Shawver
Depth Owen Murphy
Depth Cam Caminiti
Depth Bryce Elder
Depth Grant Holmes
Depth Dylan Dodd

Relief Pitchers

Projected Closer Aaron Bummer
Projected Setup #1 Joe Jiménez
Projected Setup #2 Ray Kerr
Next Up Dylan Lee
Next Up Raisel Iglesias
Next Up Pierce Johnson
Depth Enoli Paredes
Depth Hayden Harris
Depth Michael Petersen
Depth Daysbel Hernandez

Top prospects by tool!

Hit Power Speed
Nacho Alvarez Jr. – 60 Landon Stephens – 60 Colby Jones – 70
Owen Carey – 55 Ryan Casteel – 55 Patrick Clohisy – 70
Carlos D. Rodriguez – 55 Jesse Franklin V – 55 John Gil – 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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