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Patrick Geary Elite Prospects ↗

Position: Defense DOB: 2004-02-18 Country: USA
2024 · Round 6, Pick #172  ·  Buffalo Sabres Buffalo Sabres
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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 — NAHL 2 0 0 0 0.000 — — — —
2021-22 — USHL 55 4 13 17 0.309 0.1823 0.1900 0.9284 0.9675
2022-23 — USHL 60 3 10 13 0.217 0.1278 0.1265 0.6508 0.6444
■ 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 Michigan D1 BigTen — 35 2 9 11 0.314
2024-25 Michigan D1 BigTen SO 37 1 6 7 0.189
2023-24 Michigan D1 BigTen FR 32 5 8 13 0.406
Pre-College Projection vs. Actual Freshman Year
Projected PPG
0.14
before college
→
Actual FR PPG
0.41
2023-24 · Michigan
+183.3% vs. projection

College Pathway Likelihood (based on 40 comparables)

57%
NCAA D1
8%
NCAA D2/D3
18%
Age-Out / Club
18%
Pro / Other

NCAAe Rankings

#10161
Defenseman overall
#2200
Defenseman born in 2004

D1 Comparables

Garret Cockerill
USHL · 2012-13 · 0.26 PPG
→ Northeastern (0.41 D1 FR PPG)
0.15 Strong D
NCAAe PPG
Johnny Wingels
USHL · 2012-13 · 0.29 PPG
→ Miami
0.17 No data
NCAAe PPG
Sam Piazza
USHL · 2012-13 · 0.16 PPG
→ Michigan (0.10 D1 FR PPG)
0.09 Developing D
NCAAe PPG
Tim Davison
USHL · 2012-13 · 0.23 PPG
→ Wisconsin
0.13 No data
NCAAe PPG
Justin Woods
USHL · 2012-13 · 0.32 PPG
→ Alaska Fairbanks (0.18 D1 FR PPG)
0.18 Average D
NCAAe PPG

D2/3 Comparables

Tyler Ignazzitto
Albertus Magnus · 2018-19
0.917 Strong
actual D2/3 PPG
Jack Seaverson
St. Norbert · 2020-21
0.452 Average
actual D2/3 PPG
Dave McKenna
Elmira · 2002-03
0.560 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.