icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | Tri-City Storm | USHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2012-13 | Tri-City Storm | USHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2013-14 | Tri-City Storm | USHL | 57 | 14 | 15 | 29 | 0.509 | 0.3128 | 0.3058 | 1.4990 | 1.4653 |
| 2014-15 | Tri-City Storm | USHL | 58 | 10 | 20 | 30 | 0.517 | 0.3179 | 0.2951 | 1.5238 | 1.4146 |
| 2022-23 | Bietigheim Steelers | DEL | 51 | 8 | 25 | 33 | 0.647 | 0.7077 | 0.7289 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Penn State | D1 | BigTen | SR | 39 | 14 | 15 | 29 | 0.744 |
| 2017-18 | Penn State | D1 | BigTen | JR | 38 | 11 | 16 | 27 | 0.711 |
| 2016-17 | Penn State | D1 | BigTen | SO | 39 | 13 | 23 | 36 | 0.923 |
| 2015-16 | Penn State | D1 | BigTen | FR | 38 | 13 | 13 | 26 | 0.684 |
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.