icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | AJHL | 45 | 23 | 15 | 91.9% | 2.66 | 3 | 0.9700 | 77.5% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2023-24 | RIT | D1 | 4 | 2 | 2 | 91.9% | 2.27 | 0 |
| 2022-23 | Sacred Heart | D1 | 35 | 14 | 16 | 89.9% | 2.69 | 1 |
| 2021-22 | Sacred Heart | D1 | 4 | 1 | 3 | 92.5% | 2.37 | — |
| 2020-21 | Sacred Heart | D1 | 6 | 2 | 3 | 88.7% | 3.29 | 0 |
| 2019-20 | Sacred Heart | D1 | 4 | 1 | 0 | 91.5% | 2.11 | 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 |
|---|---|---|---|---|---|---|
| Aaron Matthews | NCDC | 90.7% | 77.9% | Providence | — | — |
| Daniel Hauser | WHL | 91.3% | 76.6% | Wisconsin | 90.0% | 2.49 |
| Ryan Snowden | USHL | 89.8% | 76.4% | Ohio State | 90.5% | 2.52 |
| Jacob Zacharewicz | NAHL | 89.2% | 79.5% | Brown | 86.8% | 4.19 |
| Charles-Edward Gravel | QMJHL | 91.4% | 77.9% | Mercyhurst | 90.7% | 3.22 |
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 |
|---|---|---|---|---|---|---|---|
| Jeffrey Dreger | MJHL | 86.4% | 77.7% | SUNY Morrisville | D3 | 84.5% | 4.37 |
| Vincent Lamberti | BCHL | 88.8% | 76.8% | Amherst | D3 | 90.2% | 2.47 |
| Paul Knapik | USPHL-Premier | 90.5% | 77.5% | Roger Williams | D3 | — | — |
| Anthony Bonaldi | USPHL-Premier | 90.6% | 78.2% | Nichols | D3 | 81.8% | 7.78 |
| Nikolas Trakakis | MJHL | 87.9% | 78.3% | Chatham | D3 | 93.4% | 2.45 |
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.