icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
St. Louis Blues
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | Dubuque Fighting Saints | USHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Michigan | D1 | BigTen | — | 37 | 1 | 10 | 11 | 0.297 |
| 2025-26 | Michigan State | D1 | BigTen | SO | 37 | 1 | 10 | 11 | 0.297 |
| 2024-25 | St. Cloud State | D1 | NCHC | — | 35 | 1 | 7 | 8 | 0.229 |
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.