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Ryan Taylor Elite Prospects ↗

Position: Forward DOB: 2001-03-09 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
2018-19 Bismarck Bobcats NAHL 58 12 20 32 0.552 0.2027 0.2196 0.5823 0.6309
2019-20 — USHL 37 7 3 10 0.270 0.1594 0.1594 0.8118 0.8118
2020-21 Bismarck Bobcats NAHL 48 19 22 41 0.854 0.3138 0.3138 0.9016 0.9016
2021-22 Bismarck Bobcats NAHL 21 12 12 24 1.143 0.4199 0.3929 1.2063 1.1286
■ 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 Robert Morris D1 AHA — 25 6 9 15 0.600
2024-25 Clarkson D1 ECAC GR 31 3 7 10 0.323
2023-24 Clarkson D1 ECAC SR 24 10 6 16 0.667
2022-23 Clarkson D1 ECAC JR 34 8 10 18 0.529
Pre-College Projection vs. Actual Freshman Year
Projected PPG
0.28
before college
→
Actual FR PPG
0.53
2022-23 · Clarkson
+91.1% vs. projection

College Pathway Likelihood (based on 40 comparables)

50%
NCAA D1
2%
NCAA D2/D3
28%
Age-Out / Club
20%
Pro / Other

NCAAe Rankings

#11718
Forward overall
#531
Forward born in 2001
#370
in NAHL

D1 Comparables

Carlos Amestoy
OHL · 2012-13 · 0.75 PPG
→ Maine
0.39 No data
NCAAe PPG
David Goodwin
USHL · 2012-13 · 0.67 PPG
→ Penn State (0.53 D1 FR PPG)
0.35 Average
NCAAe PPG
Dylan Walchuk
WHL · 2012-13 · 0.86 PPG
→ Northern Michigan (0.42 D1 FR PPG)
0.37 Average
NCAAe PPG
Todd Skirving
USHL · 2012-13 · 0.80 PPG
→ RIT (0.65 D1 FR PPG)
0.43 Strong
NCAAe PPG
Jordan Nelson
USHL · 2012-13 · 0.59 PPG
→ Minnesota State (0.22 D1 FR PPG)
0.31 Developing
NCAAe PPG

D2/3 Comparables

Brian Depp
Elmira · 2011-12
0.636 Average
actual D2/3 PPG
Matt Carlson
Wilkes · 2021-22
0.840 Strong
actual D2/3 PPG
John Moncovich
Utica · 2018-19
0.864 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.