icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | North Shore Storm | USHS-MN-W | 26 | 9 | 17 | 91.5% | 2.63 | 5 | 0.9200 | 75.4% |
| 2022-23 | North Shore Storm | USHS-MN-W | 24 | 6 | 16 | 90.0% | 2.79 | 4 | 0.9200 | 79.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Hamline | D3 | 22 | 7 | 2 | 93.4% | 1.45 | 2 |
| 2024-25 | Hamline | D3 | 13 | 5 | 1 | 92.3% | 1.17 | 2 |
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 |
|---|---|---|---|---|---|---|
| Grace Zhan | USHS-MN-W | 94.6% | 77.1% | Dartmouth | 94.1% | 1.00 |
| Kaitlin Groess | USHS-MN-W | 95.5% | 78.1% | Bemidji State | 88.7% | 3.98 |
| Erika Lind | CSSHL-U18W | 93.2% | 78.6% | Mercyhurst | 88.4% | 5.23 |
| Samantha Phelan | 19U-AAA-W | 88.8% | 83.4% | St. Lawrence | — | — |
| Hailey Hansen | USHS-MN-W | 93.3% | 73.5% | Minnesota | 88.5% | 3.21 |
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 |
|---|---|---|---|---|---|---|---|
| Alejandra Erdman | JWHL-U19 | 84.4% | 82.7% | Connecticut College | D3 | 88.9% | 1.20 |
| J'Anne Colbow | CSSHL-U18W | 89.8% | 80.1% | SUNY Morrisville | D3 | 92.9% | 2.15 |
| Claire Bronson | USHS-MN-W | 95.7% | 85.9% | Gustavus Adolphus | D3 | 90.3% | 1.90 |
| Jordana DeMarinis | OWHL-U22 | 89.4% | 87.6% | St. Michael's College | D3 | 91.5% | 3.78 |
| Kayla Simonson | USHS-MN-W | 93.8% | 85.5% | Augsburg | D3 | 93.9% | 1.66 |
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.