icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Lone Star Brahmas | NAHL | 56 | 21 | 14 | 35 | 0.625 | 0.2476 | 0.2732 | 0.6562 | 0.7240 |
| 2015-16 | Sioux Falls Stampede | USHL | 50 | 7 | 7 | 14 | 0.280 | 0.1721 | 0.1764 | 0.8249 | 0.8453 |
| 2016-17 | Wenatchee Wild | BCHL | 55 | 39 | 27 | 66 | 1.200 | 0.4470 | 0.4442 | 1.7485 | 1.7376 |
| 2017-18 | Wenatchee Wild | BCHL | 49 | 37 | 25 | 62 | 1.265 | 0.4713 | 0.4457 | 1.8437 | 1.7436 |
| 2023-24 | Kalmar HC | Allsvenskan | 50 | 15 | 11 | 26 | 0.520 | 1.3000 | 1.2696 | — | — |
| 2024-25 | Kalmar HC | Allsvenskan | 51 | 27 | 36 | 63 | 1.235 | 3.0883 | 2.8272 | — | — |
| 2025-26 | — | Allsvenskan | 25 | 9 | 10 | 19 | 0.760 | 1.9000 | 1.7974 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Northern Michigan | D1 | CCHA | — | 35 | 13 | 19 | 32 | 0.914 |
| 2021-22 | Northern Michigan | D1 | CCHA | — | 36 | 24 | 19 | 43 | 1.194 |
| 2020-21 | Northern Michigan | D1 | WCHA | — | 29 | 14 | 13 | 27 | 0.931 |
| 2019-20 | Northern Michigan | D1 | WCHA | — | 8 | 2 | 7 | 9 | 1.125 |
| 2018-19 | Ohio State | D1 | BigTen | — | 0 | 0 | 0 | 0 | 0.000 |
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.