icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | NAHL | 35 | 29 | 3 | 93.1% | 2.12 | 1 | 0.9843 | 89.6% |
| 2018-19 | — | NTDP-U18 | 1 | 0 | 1 | 83.3% | 7.37 | 0 | 0.9200 | 68.3% |
| 2018-19 | — | USHL | 1 | 0 | 1 | 83.3% | 7.37 | 0 | 0.9983 | 79.0% |
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2024-25 | Mercyhurst | D1 | 22 | 2 | 14 | 91.0% | 3.44 | 0 |
| 2023-24 | Miami | D1 | 2 | — | — | 88.5% | 4.71 | 0 |
| 2022-23 | Miami | D1 | — | — | — | — | — | — |
| 2021-22 | Ferris State | D1 | 2 | 0 | 0 | 92.0% | 2.74 | — |
| 2020-21 | Ferris State | D1 | 2 | 0 | 2 | 83.9% | 5.75 | 0 |
| 2019-20 | Ferris State | D1 | 9 | 1 | 6 | 88.6% | 3.74 | 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 |
|---|---|---|---|---|---|---|
| John Roberts | NAHL | 92.5% | 89.0% | Northern Michigan | 100.0% | — |
| Lassi Lehti | NAHL | 92.0% | 88.7% | Alaska Fairbanks | 83.3% | 5.56 |
| Quentin Miller | BCHL | 92.3% | 89.4% | Denver | 91.6% | 2.39 |
| Callum Tung | BCHL | 91.7% | 88.5% | UConn | 93.3% | 2.01 |
| Max Lacroix | NAHL | 91.4% | 88.4% | Boston University | 87.2% | 3.59 |
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 |
|---|---|---|---|---|---|---|---|
| Peter Sterling | NAHL | 90.7% | 89.9% | Endicott | D3 | 93.3% | 1.63 |
| Ryan Henry | NCDC | 91.6% | 89.5% | Nichols | D3 | 92.9% | 2.39 |
| Andrew Albano | OJHL | 91.7% | 89.9% | Norwich | D3 | 82.4% | 3.00 |
| Riley Mastowski | EHL | 89.9% | 88.0% | Franklin Pierce | D2 | 89.4% | 3.80 |
| Charles Watson | EHL | 93.2% | 91.4% | Castleton | D3 | 89.7% | 3.70 |
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.