icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | NCDC | 41 | 31 | 7 | 92.6% | 2.06 | 2 | 0.9400 | 83.2% |
| 2022-23 | — | NCDC | 19 | 10 | 6 | 91.4% | 3.08 | 2 | 0.9400 | 85.7% |
| 2022-23 | — | NAHL | 1 | 0 | 1 | 91.2% | 3.00 | 0 | 0.9843 | 89.3% |
| 2021-22 | — | NCDC | 12 | 3 | 5 | 84.4% | 4.88 | 0 | 0.9400 | 81.6% |
| 2021-22 | — | NAHL | 1 | 0 | 1 | 71.4% | 12.00 | 0 | 0.9843 | 72.5% |
| 2020-21 | — | NAHL | 18 | 7 | 7 | 87.7% | 3.60 | 0 | 0.9843 | 86.3% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Merrimack | D1 | — | — | — | — | — | — |
| 2024-25 | Merrimack | D1 | 5 | 1 | 1 | 92.0% | 2.22 | 1 |
Historical goalies with similar age-adjusted SVe profiles who went on to play NCAA D1.
| Name | Junior League | Junior SV% | Adj SVe | College | NCAA SV% | NCAA GAA |
|---|---|---|---|---|---|---|
| Alexander Tracy | USHL | 89.6% | 83.0% | Minnesota | 87.9% | 2.24 |
| Gavin Moffatt | USHL | 89.3% | 82.4% | Western Michigan | — | — |
| Ryan Manzella | USHL | 90.4% | 83.1% | Michigan Tech | 89.5% | 3.17 |
| Joshua Seeley | NAHL | 90.0% | 84.9% | Bentley | 82.6% | 8.58 |
| Aaron Randazzo | USHL | 88.8% | 82.5% | Air Force | 82.4% | 5.23 |
Historical goalies with similar age-adjusted SVe profiles who went on to play NCAA D2/D3.
| Name | Junior League | Junior SV% | Adj SVe | College | Div | SV% | GAA |
|---|---|---|---|---|---|---|---|
| Dean Hahn | USPHL-Premier | 91.6% | 84.1% | Salem State | D3 | 88.9% | 3.95 |
| Nolan Hildebrand | AJHL | 87.4% | 82.5% | Babson | D3 | 87.8% | 3.82 |
| Logan Palmer | USPHL-Premier | 92.1% | 84.5% | Western New England | D3 | 90.9% | 3.11 |
| Cameron Hrdlicka | SJHL | 89.6% | 83.0% | Concordia | D3 | 89.0% | 3.97 |
| Dolan Gilbert | NA3HL | 91.0% | 81.2% | Concordia | D3 | 81.0% | 9.00 |
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.