icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | NCDC | 27 | 12 | 9 | 91.9% | 2.76 | 1 | 0.9400 | 83.0% |
| 2021-22 | — | EHL | 5 | 2 | 2 | 88.6% | 3.69 | 1 | 0.9400 | 84.1% |
| 2021-22 | — | NAHL | 1 | 0 | 1 | 80.0% | 5.00 | 0 | 0.9843 | 78.3% |
| 2020-21 | — | NAHL | 1 | 1 | 0 | 90.3% | 3.00 | 0 | 0.9843 | 88.9% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Saint Anselm | D2 | 23 | — | — | 90.8% | 2.64 | 1 |
| 2024-25 | Saint Anselm | D2 | 25 | 16 | 7 | 90.9% | 3.02 | 0 |
| 2023-24 | Saint Anselm | D2 | 25 | 9 | 14 | 91.2% | 3.22 | — |
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 |
| Ryan Keyes | NCDC | 92.6% | 83.2% | Merrimack | 92.0% | 2.22 |
| Gavin Moffatt | USHL | 89.3% | 82.4% | Western Michigan | — | — |
| Aaron Randazzo | USHL | 88.8% | 82.5% | Air Force | 82.4% | 5.23 |
| Joshua Seeley | NAHL | 90.0% | 84.9% | Bentley | 82.6% | 8.58 |
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 |
|---|---|---|---|---|---|---|---|
| Nolan Hildebrand | AJHL | 87.4% | 82.5% | Babson | D3 | 87.8% | 3.82 |
| Dean Hahn | USPHL-Premier | 91.6% | 84.1% | Salem State | D3 | 88.9% | 3.95 |
| Josh Koziol | NA3HL | 93.3% | 83.8% | Augsburg | D3 | 71.4% | 5.76 |
| Jeffrey Reda | USPHL-Premier | 90.6% | 83.7% | Franklin Pierce | D2 | 85.9% | 5.85 |
| Owen Swanbon | USPHL-Premier | 90.4% | 83.4% | Framingham State | D3 | 83.3% | 8.53 |
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.