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Charlie Smith Elite Prospects ↗

Position: Forward DOB: 2004-04-05 Country: USA
No commitment set

Set Commitment

NCAA Division I

NCAA D3 / D2

Career Trajectory
Dashed = raw PPG  ·  ■ Solid blue = age-adjusted NCAAe-PPG  ·  ■ Green = actual college PPG
Junior Seasons
Season Team League GP G A Pts PPG NCAAe-PPG Age-Adj D3e-PPG Age-Adj
2020-21 Windom USHS-MN 8 0 0 0 0.000 — — — —
2022-23 Windom USHS-MN 26 0 2 2 0.077 0.0097 0.0097 0.0187 0.0187
2023-24 Odessa Jackalopes NAHL 58 6 8 14 0.241 0.0887 0.0880 0.2548 0.2529
2024-25 Odessa Jackalopes NAHL 59 14 30 44 0.746 0.2740 0.2575 0.7872 0.7399
■ Blue = NCAAe (D1 anchor)   ■ Green = D3e (D3 anchor)   COVID-flagged seasons highlighted in yellow
College Seasons (Historical)
Season School Div Conference Year GP G A Pts PPG
2025-26 Chatham D3 UCHC FR 24 4 11 15 0.625
Pre-College Projection vs. Actual Freshman Year
Projected PPG
0.16
before college
→
Actual FR PPG
0.62
2025-26 · Chatham
+284.9% vs. projection

College Pathway Likelihood (based on 40 comparables)

40%
NCAA D1
18%
NCAA D2/D3
22%
Age-Out / Club
20%
Pro / Other

NCAAe Rankings

#33410
Forward overall
#2022
Forward born in 2004

D1 Comparables

Yasin Cissé
QMJHL · 2012-13 · 0.52 PPG
→ Boston University
0.23 No data
NCAAe PPG
Jordan Nelson
USHL · 2012-13 · 0.59 PPG
→ Minnesota State (0.22 D1 FR PPG)
0.31 Developing
NCAAe PPG
Davey Middleton
USHL · 2012-13 · 0.50 PPG
→ Brown (0.10 D1 FR PPG)
0.27 Developing
NCAAe PPG
Ali Thomas
USHL · 2012-13 · 0.34 PPG
→ Notre Dame (0.18 D1 FR PPG)
0.18 Developing
NCAAe PPG
David Goodwin
USHL · 2012-13 · 0.67 PPG
→ Penn State (0.53 D1 FR PPG)
0.35 Average
NCAAe PPG

D2/3 Comparables

Andrew Kimball
Lake Forest · 2021-22
0.667 Strong
actual D2/3 PPG
Vadim Vasjonkin
Buffalo State · 2016-17
0.889 Strong
actual D2/3 PPG
Matthew Monreal
Southern New Hampshire · 2018-19
0.450 Average
actual D2/3 PPG

How to read this: NCAAe and D3e factors convert a player's junior PPG into expected NCAA scoring at the D1 or D3 level. Harder conferences → lower projected PPG for the same player. A strong junior player (e.g. USHL 0.90 PPG) will project much higher in NESCAC than Big Ten because the D3 scoring environment is lower-difficulty.

Strength factor: conferences above 1.0 are harder than average; below 1.0 are easier. The formula is: Base NCAAe PPG ÷ Conference Strength = Projected PPG.