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Nathan Burke Elite Prospects ↗

Position: Forward DOB: 1998-12-21 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
2016-17 Aberdeen Wings NAHL 5 2 1 3 0.600 0.2377 0.2536 0.6299 0.6720
2017-18 Aberdeen Wings NAHL 60 32 24 56 0.933 0.3698 0.3762 0.9799 0.9969
■ 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
2022-23 Bowling Green D1 CCHA — 36 17 12 29 0.806
2021-22 Bowling Green D1 CCHA — 37 16 7 23 0.622
2020-21 Minnesota D1 BigTen JR 26 4 3 7 0.269
2019-20 Minnesota D1 BigTen SO 32 3 3 6 0.188
2018-19 Minnesota D1 BigTen FR 26 6 9 15 0.577
Pre-College Projection vs. Actual Freshman Year
Projected PPG
0.28
before college
→
Actual FR PPG
0.58
2018-19 · Minnesota
+106.0% vs. projection

College Pathway Likelihood (based on 40 comparables)

45%
NCAA D1
0%
NCAA D2/D3
55%
Pro / Other

NCAAe Rankings

#10424
Forward overall
#471
Forward born in 1998
#275
in NAHL

D1 Comparables

Kevin Duane
USHL · 2012-13 · 0.67 PPG
→ Boston University (0.31 D1 FR PPG)
0.40 Developing
NCAAe PPG
Joe Cox
USHL · 2012-13 · 0.65 PPG
→ Michigan (0.33 D1 FR PPG)
0.39 Developing
NCAAe PPG
Kyle Schempp
USHL · 2012-13 · 0.64 PPG
→ Ferris State (0.58 D1 FR PPG)
0.39 Strong
NCAAe PPG
Andrew Poturalski
USHL · 2012-13 · 0.62 PPG
→ New Hampshire (0.72 D1 FR PPG)
0.38 Strong
NCAAe PPG
Villiam Haag
USHL · 2012-13 · 0.64 PPG
→ Michigan (0.37 D1 FR PPG)
0.38 Average
NCAAe PPG

D2/3 Comparables

Peter Magagna
SUNY Oswego · 2002-03
0.926 Strong
actual D2/3 PPG
Owen Bourdow
UMass Boston · 2018-19
0.667 Strong
actual D2/3 PPG
Arlen Marshall
Manhattanville · 2003-04
0.840 Strong
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.