icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
Calgary Flames
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | — | OHL | 55 | 12 | 19 | 31 | 0.564 | 0.3260 | 0.3556 | 1.4482 | 1.5795 |
| 2023-24 | Ottawa 67's | OHL | 65 | 15 | 46 | 61 | 0.939 | 0.5429 | 0.5661 | 2.4115 | 2.5147 |
| 2024-25 | Sudbury Wolves | OHL | 68 | 14 | 68 | 82 | 1.206 | 0.6976 | 0.6915 | 3.0986 | 3.0713 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Michigan | D1 | BigTen | FR | 10 | 0 | 9 | 9 | 0.900 |
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.