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Trenton Bliss Elite Prospects ↗

Position: Forward DOB: 1998-03-16 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 Green Bay Gamblers USHL 24 0 1 1 0.042 0.0256 0.0255 0.1229 0.1226
2017-18 Green Bay Gamblers USHL 60 21 34 55 0.917 0.5635 0.5341 2.7008 2.5601
■ 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
2021-22 Michigan Tech D1 CCHA SR 36 12 28 40 1.111
2020-21 Michigan Tech D1 WCHA JR 29 12 13 25 0.862
2019-20 Michigan Tech D1 WCHA SO 39 12 15 27 0.692
2018-19 Michigan Tech D1 WCHA FR 34 6 9 15 0.441
Pre-College Projection vs. Actual Freshman Year
Projected PPG
0.28
before college
→
Actual FR PPG
0.44
2018-19 · Michigan Tech
+55.9% vs. projection

College Pathway Likelihood (based on 40 comparables)

85%
NCAA D1
2%
NCAA D2/D3
12%
Pro / Other

NCAAe Rankings

#12226
Forward overall
#555
Forward born in 1998
#1182
in USHL

D1 Comparables

Michael Vecchione
USHL · 2012-13 · 0.95 PPG
→ Union (0.89 D1 FR PPG)
0.55 Elite
NCAAe PPG
Dominik Shine
USHL · 2012-13 · 0.90 PPG
→ Northern Michigan (0.45 D1 FR PPG)
0.52 Average
NCAAe PPG
Chad McDonald
USHL · 2012-13 · 0.79 PPG
→ Ferris State (0.48 D1 FR PPG)
0.46 Average
NCAAe PPG
Tyler Biggs
OHL · 2012-13 · 0.88 PPG
→ Miami (0.46 D1 FR PPG)
0.49 Average
NCAAe PPG
Phil Marinaccio
USHL · 2012-13 · 0.77 PPG
→ Bemidji State (0.31 D1 FR PPG)
0.45 Developing
NCAAe PPG

D2/3 Comparables

Rihards Marenis
Aurora · 2013-14
1.000 Elite
actual D2/3 PPG
Lucas Signoretti
Buffalo State · 2023-24
1.120 Elite
actual D2/3 PPG
Zach Dill
Salem State · 2021-22
1.111 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.