icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | — | NAHL | 33 | 14 | 11 | 90.0% | 3.36 | 1 | 0.9843 | 80.4% |
| 2022-23 | — | NAHL | 30 | 15 | 13 | 89.5% | 3.48 | 1 | 0.9843 | 85.8% |
| 2021-22 | — | NAHL | 7 | 4 | 1 | 90.8% | 2.68 | 1 | 0.9843 | 93.2% |
| 2021-22 | — | USHL | 15 | 7 | 4 | 86.5% | 3.54 | 0 | 0.9980 | 85.1% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Curry | D3 | 9 | — | — | — | — | — |
| 2024-25 | UConn | D1 | 3 | 1 | 2 | 86.7% | 4.39 | 0 |
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 |
|---|---|---|---|---|---|---|
| Teagan Kendrick | BCHL | 91.5% | 80.5% | Sacred Heart | 92.0% | 2.42 |
| Cullen DeYoung | NAHL | 91.0% | 81.0% | Sacred Heart | 94.3% | 1.73 |
| Jacob Zacharewicz | NAHL | 89.2% | 79.5% | Brown | 86.8% | 4.19 |
| Mitchell Day | NAHL | 91.6% | 81.3% | Niagara | 88.3% | 4.06 |
| Jack LaFontaine | BCHL | 92.3% | 80.1% | Minnesota | 91.9% | 2.55 |
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 |
|---|---|---|---|---|---|---|---|
| Tripp Clarke | USPHL-Premier | 93.7% | 80.6% | Manhattanville | D3 | 75.0% | 4.09 |
| Pierce Diamond | SJHL | 91.5% | 80.1% | Albertus Magnus | D3 | 89.4% | 3.82 |
| Nick Howard | USPHL-Premier | 94.7% | 81.0% | Saint Anselm | D2 | 90.6% | 2.70 |
| Matt Hennessey | AJHL | 90.9% | 79.8% | Anna Maria | D3 | 93.2% | 2.59 |
| William McEvoy | CCHL | 91.2% | 80.0% | Connecticut College | D3 | 90.2% | 3.12 |
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.