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 | Waterloo Black Hawks | USHL | 10 | 3 | 2 | 5 | 0.500 | 0.3184 | 0.3427 | 1.4984 | 1.6129 |
| 2011-12 | Waterloo Black Hawks | USHL | 2 | 2 | 2 | 4 | 2.000 | 1.2736 | 1.3114 | 5.9934 | 6.1715 |
| 2012-13 | Waterloo Black Hawks | USHL | 54 | 29 | 58 | 87 | 1.611 | 1.0259 | 1.0018 | 4.8280 | 4.7146 |
| 2020-21 | Torpedo Nizhny Novgorod | KHL | 48 | 11 | 9 | 20 | 0.417 | — | — | — | — |
| 2021-22 | Leksands IF | SHL | 45 | 9 | 13 | 22 | 0.489 | — | — | — | — |
| 2022-23 | Leksands IF | SHL | 43 | 13 | 14 | 27 | 0.628 | — | — | — | — |
| 2023-24 | Leksands IF | SHL | 37 | 7 | 17 | 24 | 0.649 | — | — | — | — |
| 2024-25 | Leksands IF | SHL | 52 | 18 | 15 | 33 | 0.635 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Minnesota | D1 | BigTen | SR | 38 | 18 | 25 | 43 | 1.132 |
| 2015-16 | Minnesota | D1 | BigTen | JR | 37 | 16 | 27 | 43 | 1.162 |
| 2014-15 | Minnesota | D1 | BigTen | SO | 39 | 13 | 19 | 32 | 0.821 |
| 2013-14 | Minnesota | D1 | BigTen | FR | 41 | 16 | 16 | 32 | 0.780 |
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.