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West Bauman Elite Prospects ↗

Position: Forward DOB: 1989-05-02 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
2008-09 Seguin Bruins OJHL 19 0 4 4 0.210 0.0632 0.0604 0.1441 0.1378
2009-10 Seguin Bruins OJHL 50 6 9 15 0.300 0.0901 0.0814 0.2054 0.1856
■ 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
2013-14 Milwaukee School of Engineering D3 — SR 27 2 12 14 0.518
2012-13 Milwaukee School of Engineering D3 — JR 26 1 10 11 0.423
2011-12 Milwaukee School of Engineering D3 — SO 30 8 18 26 0.867
2010-11 Milwaukee School of Engineering D3 — FR 28 4 14 18 0.643
Pre-College Projection vs. Actual Freshman Year
Projected PPG
0.06
before college
→
Actual FR PPG
0.64
2010-11 · Milwaukee School of Engineering
+928.6% vs. projection

NCAAe Rankings

#51158
Forward overall
#1712
Forward born in 1989
#4581
in OJHL

D1 Comparables

Eli Lichtenwald
USHL · 2012-13 · 0.36 PPG
→ Union (0.68 D1 FR PPG)
0.20 Strong
NCAAe PPG
Ali Thomas
USHL · 2012-13 · 0.34 PPG
→ Notre Dame (0.18 D1 FR PPG)
0.19 Developing
NCAAe PPG
Yasin Cissé
QMJHL · 2012-13 · 0.52 PPG
→ Boston University
0.23 No data
NCAAe PPG
Cullen Hurley
USHL · 2012-13 · 0.38 PPG
→ Wisconsin
0.22 No data
NCAAe PPG
Tayler Munson
USHL · 2012-13 · 0.31 PPG
→ Alaska Fairbanks (0.35 D1 FR PPG)
0.18 Average
NCAAe PPG

D2/3 Comparables

Caden Pattison
Albertus Magnus · 2021-22
0.522 Average
actual D2/3 PPG
Chris Rampone
St. Norbert · 2003-04
0.000 No data
actual D2/3 PPG
Peter Falivena
Bryn Athyn · 2018-19
0.368 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.