icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | — | BCHL | 39 | 19 | 17 | 90.2% | 3.43 | 0 | 0.9990 | 86.1% |
| 2023-24 | Youngstown Phantoms | USHL | 23 | 8 | 8 | 86.7% | 3.69 | 0 | 0.9983 | 84.2% |
| 2022-23 | — | USHL | 25 | 11 | 10 | 89.1% | 3.15 | 0 | 0.9983 | 89.8% |
| 2021-22 | — | NCDC | 44 | 25 | 12 | 91.9% | 2.58 | 4 | 0.9400 | 92.9% |
| 2021-22 | — | NTDP-U18 | 1 | 0 | 0 | 50.0% | 18.00 | 0 | 0.9200 | 45.7% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | St. Lawrence | D1 | 9 | 0 | 7 | 88.3% | 4.50 | 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 |
|---|---|---|---|---|---|---|
| Nick Bevilacqua | NCDC | 94.8% | 86.1% | Bentley | 95.2% | 0.99 |
| Michael Sochan | BCHL | 90.6% | 86.1% | Robert Morris | 100.0% | — |
| Adam Manji | BCHL | 90.4% | 86.0% | American International | 92.1% | 2.70 |
| Beni Halasz | NAHL | 92.1% | 87.8% | Northern Michigan | 91.9% | 2.32 |
| Max Hildebrand | WHL | 91.8% | 85.6% | Bemidji State | 89.5% | 2.71 |
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 |
|---|---|---|---|---|---|---|---|
| Ben Cunneen | USPHL-Premier | 92.9% | 86.2% | Post | D2 | 89.2% | 4.30 |
| Dane Couture | NAHL | 88.1% | 86.3% | Concordia | D3 | 87.3% | 2.94 |
| Braedyn McIntosh | BCHL | 91.9% | 85.5% | Aurora | D3 | 91.7% | 3.09 |
| Kevin Lake | NAHL | 87.9% | 85.8% | Hamline | D3 | 91.7% | 2.54 |
| Duncan Rolleman | USPHL-Premier | 92.5% | 86.2% | Wilkes | D3 | 90.0% | 3.84 |
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.