icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
San Jose Sharks
| Season | Team | League | GP | W | L | SV% | GAA | SO | SVe Factor | Age-Adj SV% |
|---|---|---|---|---|---|---|---|---|---|---|
| 2026-27 | Saginaw Spirit | OHL | 3 | 2 | 0 | 89.4% | 2.92 | 0 | 1.0008 | 89.5% |
| 2025-26 | U.S. National U18 Team | NTDP-U18 | 34 | 15 | 13 | 88.3% | 3.51 | 0 | 0.9200 | 79.1% |
| 2025-26 | USNTDP Juniors | USHL | 15 | 8 | 5 | 88.6% | 3.33 | 0 | 0.9987 | 91.4% |
| 2024-25 | U.S. National U17 Team | NTDP-U18 | 12 | 2 | 8 | 82.9% | 6.22 | 0 | 0.9200 | 77.4% |
| 2024-25 | USNTDP Juniors | USHL | 13 | 1 | 7 | 81.3% | 6.83 | 0 | 0.9987 | 86.7% |
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 |
|---|---|---|---|---|---|---|
| Owen Bartoszkiewicz | USHL | 88.9% | 88.5% | Minnesota | 88.3% | 3.72 |
| Mikhail Yegorov | USHL | 91.2% | 90.5% | Boston University | 90.4% | 2.73 |
| Aku Koskenvuo | SM-Liiga-Jr | 89.7% | 87.2% | Harvard | 87.5% | 3.56 |
| Jere Huhtamaa | SM-Liiga-Jr | 90.3% | 88.3% | Merrimack | 86.4% | 3.47 |
| Blake Pietila | USHL | 91.2% | 90.4% | Michigan Tech | 86.8% | 3.24 |
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 |
|---|---|---|---|---|---|---|---|
| Brody Haynes | NCDC | 92.5% | 92.3% | Elmira | D3 | 94.8% | 1.22 |
| Cooper Rautenstrauch | NCDC | 90.6% | 92.2% | Colby | D3 | 93.4% | 2.08 |
| Cooper Rautenstrauch | NAHL | 88.9% | 92.2% | Colby | D3 | 93.4% | 2.08 |
| Nevin Tardif | USPHL-Premier | 90.4% | 87.8% | Worcester State | D3 | 89.8% | 3.54 |
| Vaughn Makar | NAHL | 90.9% | 94.0% | St. Norbert | D3 | 93.2% | 1.73 |
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.