icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | Markham Thunder | CWHL | 23 | 5 | 4 | 9 | 0.391 | — | — | — | — |
| 2014-15 | Markham Thunder | CWHL | 24 | 7 | 9 | 16 | 0.667 | — | — | — | — |
| 2015-16 | Markham Thunder | CWHL | 24 | 14 | 10 | 24 | 1.000 | — | — | — | — |
| 2016-17 | Markham Thunder | CWHL | 24 | 17 | 20 | 37 | 1.542 | — | — | — | — |
| 2017-18 | Buffalo Beauts | PHF | 14 | 4 | 5 | 9 | 0.643 | — | — | — | — |
| 2018-19 | Markham Thunder | CWHL | 25 | 9 | 6 | 15 | 0.600 | — | — | — | — |
| 2019-20 | Markham Thunder | CWHL | 25 | 9 | 6 | 15 | 0.600 | — | — | — | — |
| 2020-21 | Markham Thunder | CWHL | 25 | 9 | 6 | 15 | 0.600 | — | — | — | — |
| 2021-22 | Markham Thunder | CWHL | 25 | 9 | 6 | 15 | 0.600 | — | — | — | — |
| 2022-23 | Markham Thunder | CWHL | 25 | 9 | 6 | 15 | 0.600 | — | — | — | — |
| 2023-24 | Markham Thunder | CWHL | 25 | 9 | 6 | 15 | 0.600 | — | — | — | — |
| 2025-26 | Markham Thunder | CWHL | 25 | 9 | 6 | 15 | 0.600 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | Mercyhurst | D1 | CHA-W | SR | 34 | 13 | 35 | 48 | 1.412 |
| 2010-11 | Mercyhurst | D1 | CHA-W | JR | 29 | 12 | 14 | 26 | 0.897 |
| 2009-10 | Mercyhurst | D1 | CHA-W | SO | 36 | 20 | 26 | 46 | 1.278 |
| 2008-09 | Mercyhurst | D1 | CHA-W | FR | 36 | 16 | 18 | 34 | 0.944 |
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.