icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2010-11 | Maple Grove High (W) | USHS-MN-W | 25 | 11 | 14 | 25 | 1.000 | 0.1606 | 0.1587 | — | — |
| 2011-12 | Maple Grove High (W) | USHS-MN-W | 25 | 9 | 21 | 30 | 1.200 | 0.1927 | 0.1821 | — | — |
| 2012-13 | Maple Grove High (W) | USHS-MN-W | 25 | 19 | 15 | 34 | 1.360 | 0.2184 | 0.1983 | — | — |
| 2018-19 | KRS Shenzhen | CWHL | 28 | 3 | 3 | 6 | 0.214 | — | — | — | — |
| 2019-20 | KRS Shenzhen | CWHL | 28 | 3 | 3 | 6 | 0.214 | — | — | — | — |
| 2020-21 | KRS Shenzhen | CWHL | 28 | 3 | 3 | 6 | 0.214 | — | — | — | — |
| 2021-22 | KRS Shenzhen | CWHL | 28 | 3 | 3 | 6 | 0.214 | — | — | — | — |
| 2022-23 | KRS Shenzhen | CWHL | 28 | 3 | 3 | 6 | 0.214 | — | — | — | — |
| 2023-24 | KRS Shenzhen | CWHL | 28 | 3 | 3 | 6 | 0.214 | — | — | — | — |
| 2025-26 | KRS Shenzhen | CWHL | 28 | 3 | 3 | 6 | 0.214 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Brown | D1 | ECAC-W | — | 5 | 1 | 3 | 4 | 0.800 |
| 2015-16 | Brown | D1 | ECAC-W | — | 29 | 6 | 9 | 15 | 0.517 |
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.