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Nathan Lewis Elite Prospects ↗

Position: Forward DOB: 2004-07-27 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
2021-22 Madison Capitols USHL 43 7 7 14 0.326 0.2001 0.2129 0.9593 1.0207
2022-23 Madison Capitols USHL 62 11 28 39 0.629 0.3866 0.3913 1.8532 1.8755
2023-24 Youngstown Phantoms USHL 12 8 7 15 1.250 0.7684 0.7395 3.6828 3.5442
■ 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 Ohio State D1 BigTen SO 23 4 1 5 0.217
2024-25 Ohio State D1 BigTen — 28 2 4 6 0.214
Pre-College Projection vs. Actual Freshman Year
Projected PPG
0.56
before college
→
Actual FR PPG
0.21
2024-25 · Ohio State
-61.6% vs. projection

College Pathway Likelihood (based on 40 comparables)

95%
NCAA D1
0%
NCAA D2/D3
5%
Pro / Other

NCAAe Rankings

#5124
Forward overall
#143
Forward born in 2004
#288
in USHL

D1 Comparables

J.T. Stenglein
USHL · 2012-13 · 1.04 PPG
→ Michigan (0.07 D1 FR PPG)
0.61 Developing
NCAAe PPG
Zach Stepan
USHL · 2012-13 · 1.39 PPG
→ Minnesota (0.60 D1 FR PPG)
0.84 Strong
NCAAe PPG
Peter Quenneville
USHL · 2012-13 · 1.11 PPG
→ Quinnipiac (0.80 D1 FR PPG)
0.68 Elite
NCAAe PPG
Dominic Toninato
USHL · 2012-13 · 1.09 PPG
→ Minnesota Duluth (0.43 D1 FR PPG)
0.67 Average
NCAAe PPG
Frank Vatrano
USHL · 2012-13 · 1.00 PPG
→ UMass
0.61 No data
NCAAe PPG

D2/3 Comparables

Arkhip Ledenkov
St. Scholastica · 2018-19
1.636 Elite
actual D2/3 PPG
Neil Trimm
Neumann · 2003-04
1.800 Elite
actual D2/3 PPG
Filimon Ledenkov
St. Scholastica · 2018-19
1.636 Elite
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.