icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Chicago Steel | USHL | 4 | 1 | 0 | 1 | 0.250 | 0.1537 | 0.1700 | 0.7366 | 0.8145 |
| 2018-19 | Chicago Steel | USHL | 59 | 14 | 16 | 30 | 0.508 | 0.3126 | 0.3295 | 1.4981 | 1.5793 |
| 2019-20 | Lincoln Stars | USHL | 48 | 14 | 35 | 49 | 1.021 | 0.6275 | 0.6275 | 3.0075 | 3.0075 |
| 2025-26 | Mora IK | Allsvenskan | 45 | 6 | 14 | 20 | 0.444 | 1.1110 | 1.2528 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2024-25 | Quinnipiac | D1 | ECAC | — | 38 | 16 | 20 | 36 | 0.947 |
| 2023-24 | Quinnipiac | D1 | ECAC | — | 30 | 12 | 12 | 24 | 0.800 |
| 2022-23 | Ohio State | D1 | BigTen | JR | 35 | 8 | 13 | 21 | 0.600 |
| 2021-22 | Ohio State | D1 | BigTen | SO | 36 | 7 | 7 | 14 | 0.389 |
| 2020-21 | Ohio State | D1 | BigTen | FR | 25 | 8 | 12 | 20 | 0.800 |
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.