icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2007-08 | Mississauga Chiefs | CWHL | 0 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2012-13 | Toronto Furies | CWHL | 24 | 15 | 8 | 23 | 0.958 | — | — | — | — |
| 2013-14 | Toronto Furies | CWHL | 3 | 2 | 1 | 3 | 1.000 | — | — | — | — |
| 2014-15 | Toronto Furies | CWHL | 20 | 7 | 8 | 15 | 0.750 | — | — | — | — |
| 2015-16 | Toronto Furies | CWHL | 22 | 17 | 13 | 30 | 1.364 | — | — | — | — |
| 2016-17 | Toronto Furies | CWHL | 20 | 13 | 7 | 20 | 1.000 | — | — | — | — |
| 2017-18 | Toronto Furies | CWHL | 0 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2018-19 | Toronto Furies | CWHL | 26 | 15 | 11 | 26 | 1.000 | — | — | — | — |
| 2019-20 | Toronto Furies | CWHL | 26 | 15 | 11 | 26 | 1.000 | — | — | — | — |
| 2020-21 | Toronto Furies | CWHL | 26 | 15 | 11 | 26 | 1.000 | — | — | — | — |
| 2021-22 | Toronto Furies | CWHL | 26 | 15 | 11 | 26 | 1.000 | — | — | — | — |
| 2022-23 | Toronto Furies | CWHL | 26 | 15 | 11 | 26 | 1.000 | — | — | — | — |
| 2023-24 | Toronto Furies | CWHL | 26 | 15 | 11 | 26 | 1.000 | — | — | — | — |
| 2024-25 | Toronto Sceptres | PWHL | 14 | 3 | 2 | 5 | 0.357 | — | — | — | — |
| 2025-26 | Toronto Sceptres | PWHL | 30 | 3 | 5 | 8 | 0.267 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | Ohio State | D1 | WCHA-W | SR | 34 | 31 | 19 | 50 | 1.471 |
| 2010-11 | Ohio State | D1 | WCHA-W | JR | 29 | 26 | 13 | 39 | 1.345 |
| 2009-10 | Ohio State | D1 | WCHA-W | SO | 35 | 22 | 22 | 44 | 1.257 |
| 2008-09 | Ohio State | D1 | WCHA-W | FR | 30 | 21 | 9 | 30 | 1.000 |
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.