icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | KRS Shenzhen | CWHL | 28 | 4 | 6 | 10 | 0.357 | — | — | — | — |
| 2019-20 | KRS Shenzhen | CWHL | 28 | 4 | 6 | 10 | 0.357 | — | — | — | — |
| 2020-21 | KRS Shenzhen | CWHL | 28 | 4 | 6 | 10 | 0.357 | — | — | — | — |
| 2021-22 | KRS Shenzhen | CWHL | 28 | 4 | 6 | 10 | 0.357 | — | — | — | — |
| 2022-23 | KRS Shenzhen | CWHL | 28 | 4 | 6 | 10 | 0.357 | — | — | — | — |
| 2023-24 | KRS Shenzhen | CWHL | 28 | 4 | 6 | 10 | 0.357 | — | — | — | — |
| 2024-25 | Toronto Six | PHF | 24 | 7 | 7 | 14 | 0.583 | — | — | — | — |
| 2025-26 | KRS Shenzhen | CWHL | 28 | 4 | 6 | 10 | 0.357 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | UConn | D1 | HEA-W | SR | 39 | 10 | 20 | 30 | 0.769 |
| 2016-17 | UConn | D1 | HEA-W | JR | 35 | 18 | 11 | 29 | 0.829 |
| 2015-16 | UConn | D1 | HEA-W | SO | 37 | 10 | 14 | 24 | 0.649 |
| 2014-15 | UConn | D1 | HEA-W | FR | 37 | 4 | 15 | 19 | 0.513 |
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.