icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
No junior season data found for this player.
| Season | School | Div | GP | W | L | SV% | GAA | SO |
|---|---|---|---|---|---|---|---|---|
| 2025-26 | Saint Mary's | D3 | 13 | 3 | 7 | 90.8% | 2.70 | 1 |
| 2024-25 | Saint Mary's (MN) | D3 | 13 | 7 | 6 | 90.9% | 2.47 | — |
| 2024-25 | Saint Mary's | D3 | 13 | 7 | 6 | 90.9% | 2.47 | 0 |
| 2023-24 | Saint Mary's (MN) | D3 | 27 | 19 | 6 | 93.7% | 1.46 | — |
| 2023-24 | Saint Mary's | D3 | 23 | 16 | 5 | 93.6% | 1.54 | 3 |
| 2022-23 | Saint Mary's (MN) | D3 | 13 | 4 | 6 | 92.0% | 1.99 | — |
| 2022-23 | Saint Mary's | D3 | 13 | 4 | 6 | 92.0% | 1.99 | 2 |
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.