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Model Predictions

Model Loyola Maryland Greyhounds Canisius Golden Griffins Spread Result
Elo 25.3% 74.7% - โœ“
Bradley-Terry 41.3% 58.7% - โœ“
Margin 31.9% 68.1% - โœ“
Pythagorean 35.3% 64.7% - โœ“
Adjusted Efficiency 23.5% 76.5% - โœ“
Log Adjusted 23.3% 76.7% - โœ“
Points Off/Def 32.0% 68.0% - โœ“

Actual: Canisius Golden Griffins +9 (92-83). Win probabilities: out-of-sample forecasts from the weekly fit before the game, the same forecasts as the model pages.

RAPM GS requires a reviewed game-score run and a qualified player and game match. A dash means the score is unavailable.

Loyola Maryland Greyhounds

Player MIN FG 3PT FT REB AST STL BLK TO PTS Nums RAPM GS
Josko Alujevic 36 4-9 0-1 0-0 4 3 0 0 0 8 6 -
Freddie Stanback 35 6-12 1-5 2-3 5 6 0 0 1 15 13 -
Brad Farrell 30 1-6 0-1 2-3 10 6 1 0 1 4 14 -
Shane James 26 3-6 3-3 0-0 5 1 0 0 2 9 7 -
Charlie Bell 18 6-10 0-1 5-7 5 1 0 0 3 17 10 -
Greg Manning 15 2-2 2-2 1-1 1 0 0 0 1 7 5 -
Sean Corrigan 14 4-9 4-8 3-3 6 1 0 0 1 15 12 -
Linton Hinds 10 0-1 0-0 0-0 3 2 0 0 2 0 2 -
Jim Chivers 9 2-8 0-0 2-3 2 0 0 0 0 6 0 -
Bernard Allen 7 1-6 0-1 0-0 2 0 0 2 2 2 -2 -
James Fox 0 0-0 0-0 0-0 1 0 0 0 0 0 1 -

Canisius Golden Griffins

Player MIN FG 3PT FT REB AST STL BLK TO PTS Nums RAPM GS
Kevin Downey 38 7-12 2-4 1-1 4 5 0 0 0 17 14 -
C. Harris 33 3-8 1-3 4-6 2 4 2 0 1 11 10 -
Jon Popofski 32 9-11 3-4 2-2 3 2 2 0 0 23 19 -
Darnell Wilson 29 8-13 0-0 2-4 10 3 2 2 0 18 22 -
Dewitt Doss 29 3-11 0-6 6-7 2 4 0 0 3 12 4 -
Rigoberto Sargeant 16 3-7 0-0 0-0 2 0 1 2 0 6 4 -
Anthony Byrd 9 0-1 0-1 0-0 1 0 0 0 0 0 0 -
Marcus Vanderheide 7 0-2 0-0 0-0 1 2 0 0 0 0 1 -
Andrew Spitler 5 1-1 1-1 2-2 0 1 0 0 0 5 5 -
Jess Poe 1 0-0 0-0 0-0 0 0 0 0 0 0 0 -
Mike Hanley 1 0-0 0-0 0-0 0 0 0 0 0 0 0 -

* = starter