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 | Youngstown Phantoms | USHL | 32 | 7 | 14 | 21 | 0.656 | 0.4034 | 0.4241 | 1.9333 | 2.0324 |
| 2014-15 | — | USHL | 55 | 4 | 26 | 30 | 0.545 | 0.3353 | 0.3360 | 1.6072 | 1.6106 |
| 2022-23 | Östersunds IK | Allsvenskan | 9 | 3 | 3 | 6 | 0.667 | 1.6667 | 1.5574 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | Colorado College | D1 | NCHC | — | 41 | 15 | 19 | 34 | 0.829 |
| 2017-18 | Colorado College | D1 | NCHC | — | 37 | 7 | 24 | 31 | 0.838 |
| 2016-17 | Colorado College | D1 | NCHC | — | 9 | 0 | 6 | 6 | 0.667 |
| 2015-16 | Colorado College | D1 | NCHC | — | 33 | 9 | 7 | 16 | 0.485 |
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.