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Christian Kocsis Elite Prospects ↗

Position: Forward DOB: 2004-06-09 Country: USA
No commitment set

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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
2020-21 Lincoln Stars USHL 6 0 1 1 0.167 0.1025 0.1025 0.4911 0.4911
2021-22 — USHL 57 6 6 12 0.210 0.1294 0.1368 0.6202 0.6558
2022-23 Des Moines Buccaneers USHL 53 10 14 24 0.453 0.2783 0.2798 1.3340 1.3413
2023-24 Des Moines Buccaneers USHL 48 8 11 19 0.396 0.2433 0.2325 1.1661 1.1146
■ 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 Mercyhurst D1 AHA SO 37 6 5 11 0.297
2024-25 Mercyhurst D1 AHA — 25 0 2 2 0.080
Pre-College Projection vs. Actual Freshman Year
Projected PPG
0.22
before college
→
Actual FR PPG
0.08
2024-25 · Mercyhurst
-62.8% vs. projection

College Pathway Likelihood (based on 40 comparables)

50%
NCAA D1
18%
NCAA D2/D3
32%
Age-Out / Club
0%
Pro / Other

NCAAe Rankings

#24001
Forward overall
#1332
Forward born in 2004
#2374
in USHL

D1 Comparables

Alfred Larsson
USHL · 2012-13 · 0.39 PPG
→ Merrimack (0.20 D1 FR PPG)
0.23 Developing
NCAAe PPG
Tanner Pond
USHL · 2012-13 · 0.39 PPG
→ Northeastern (0.11 D1 FR PPG)
0.23 Developing
NCAAe PPG
Matt Pohlkamp
USHL · 2012-13 · 0.33 PPG
→ Bowling Green (0.41 D1 FR PPG)
0.20 Average
NCAAe PPG
Zach Saar
USHL · 2012-13 · 0.33 PPG
→ Penn State (0.33 D1 FR PPG)
0.20 Developing
NCAAe PPG
Brett Skibba
USHL · 2012-13 · 0.50 PPG
→ UConn (0.23 D1 FR PPG)
0.29 Developing
NCAAe PPG

D2/3 Comparables

Sean David
Canton · 2016-17
0.800 Strong
actual D2/3 PPG
Joe Anderson
Wisconsin-Stout · 2013-14
0.625 Average
actual D2/3 PPG
Gavin Bloder
Fredonia · 2022-23
0.750 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.