icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Montréal Canadiennes | CWHL | 22 | 9 | 6 | 15 | 0.682 | — | — | — | — |
| 2018-19 | Montréal Canadiennes | CWHL | 26 | 7 | 9 | 16 | 0.615 | — | — | — | — |
| 2019-20 | Montréal Canadiennes | CWHL | 26 | 7 | 9 | 16 | 0.615 | — | — | — | — |
| 2020-21 | Montréal Canadiennes | CWHL | 26 | 7 | 9 | 16 | 0.615 | — | — | — | — |
| 2021-22 | Montréal Canadiennes | CWHL | 26 | 7 | 9 | 16 | 0.615 | — | — | — | — |
| 2022-23 | Montréal Canadiennes | CWHL | 26 | 7 | 9 | 16 | 0.615 | — | — | — | — |
| 2023-24 | Montréal Canadiennes | CWHL | 26 | 7 | 9 | 16 | 0.615 | — | — | — | — |
| 2024-25 | Montréal Force | PHF | 17 | 7 | 3 | 10 | 0.588 | — | — | — | — |
| 2025-26 | Montréal Canadiennes | CWHL | 26 | 7 | 9 | 16 | 0.615 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Boston University | D1 | HEA-W | SR | 34 | 13 | 22 | 35 | 1.029 |
| 2014-15 | Boston University | D1 | HEA-W | JR | 37 | 23 | 27 | 50 | 1.351 |
| 2013-14 | Boston University | D1 | HEA-W | SO | 38 | 32 | 23 | 55 | 1.447 |
| 2012-13 | Boston University | D1 | HEA-W | FR | 37 | 24 | 19 | 43 | 1.162 |
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.