Who will win Canisius vs Cornell?
The model gives Cornell a 79% chance to beat Canisius, with a projected score of Cornell 66, Canisius 56.
Half of games like thisFour in five
Calls of 70–80% have been right 74.9% of the time in 7,564 past games, and the typical miss on the margin is 9.5 points. After the final, the result is pinned to this strip. As of 2:23 AM ET on November 13, 2026. Updated three times a day until tip-off.
Players to watch
| Player | Pts | Reb | Ast | Last games | Chance of |
|---|---|---|---|---|---|
 Cornell | |||||
| LeonardG · 19 min | 9.4 | 2.2 | 1.6 | 10+ 44% | |
| JacksonG · 25 min | 8.6 | 4.7 | 2.4 | 10+ 38% | |
| KausF · 20 min | 8.4 | 4.1 | 1.1 | 10+ 36% | |
| ChenG · 19 min | 7.4 | 1.9 | 2.0 | 5+ 68% | |
 Canisius | |||||
| VitucciG · 26 min | 11.1 | 2.6 | 1.7 | 10+ 56% | |
| GailesF · 20 min | 9.7 | 5.4 | 0.8 | 10+ 46% | |
| HuppF · 25 min | 7.9 | 6.1 | 0.7 | 10+ 33% | |
| DjibrilF · 21 min | 6.5 | 3.0 | 1.0 | 5+ 61% | |
Bars: points in the player's latest games this season. Blue line: tonight's projection. Every regular's line
The game without one player
Without Rachel Kaus: Canisius 22%Cornell 78%
The white mark is the call with her: Cornell 79%.
| Player | Points a game she adds | Cornell without her | Change | Projected score |
|---|---|---|---|---|
| Cornell | ||||
| Rachel Kaus | 0.5 | 78% | −1 | 56–66 |
Change is in Cornell's win chance, in points. Scores read Canisius, then Cornell. A player's value is what the team is better by with her than with a replacement, from the player ratings.
Model against the line
Your call
All of today's gamesPlay-by-play
Team numbers
Form
Canisius 2-0WW
- Nov 8W 73-61vs UMass Lowell
- Nov 5W 52-48at New Hampshire
- Last 2
- 2–0, scoring 62.5 and allowing 54.5
The spread and the total are the lines logged with each prediction. Form is what happened; the ratings above already count recent games more.
Offense against defense
| Canisius | Cornell | |
|---|---|---|
| Points scored per 100 possessions | 81.4 303rd | 86.3 245th |
| Points allowed per 100 | 98.6 263rd | 95.2 200th |
| Possessions a game | 71.1 272nd | 70.2 331st |
| Shooting (effective field-goal %) | 44.9% 212th | 43.0% 314th |
| Opponents' shooting | 44.8% 140th | 48.7% 334th |
| Turnovers, share of possessions | 24.5% 260th | 25.5% 304th |
| Offensive rebounds, share of misses | 34.6% 94th | 30.1% 312th |
| Free throws per shot | 0.25 25th | 0.19 317th |
The widest gap: Cornell's defense (200th) against Canisius's offense (303rd), of 363 teams.
First half
- Projected halftime score
- Canisius 26, Cornell 32
- First-half margin
- Cornell by 5.9
- First-half points, both teams
- 57.8
- Projected second half
- Canisius 30, Cornell 34
- Second-half points, both teams
- 64.1
- Tied at the half
- 4%
- Canisius, first halves so far
- Led 1 of 2 · 28.5 scored, 27.0 allowed
- Cornell, first halves so far
- Led 1 of 3 · 26.0 scored, 39.0 allowed
Our own projection, not a sportsbook's first-half line. On 10,911 past games it had not seen, the halftime leader was right 73.0% of the time and the first-half total was off by 8.0 points on average. This season: 404 of 492 halftime leaders right. Scorecard
Player projections
Canisius
| Player | Min | Pts | Reb | Ast | 3s |
|---|---|---|---|---|---|
| Sofia VitucciG | 26 | 11.1 | 2.6 | 1.7 | 0.6 |
| 10+ pts 56% · 3+ reb 46% · 2+ ast 49% | |||||
| Maria Sanchez PitarchG | 26 | 4.6 | 1.5 | 1.4 | 0.2 |
| 5+ pts 42% · 2+ reb 40% · 2+ ast 40% | |||||
| Aubree HuppF | 25 | 7.9 | 6.1 | 0.7 | 0.3 |
| 10+ pts 33% · 6+ reb 53% · 1+ threes 22% | |||||
| Yasmine DjibrilF | 21 | 6.5 | 3.0 | 1.0 | 0.2 |
| 5+ pts 61% · 3+ reb 53% · 2+ ast 27% | |||||
| Corniya ClayG | 20 | 3.9 | 1.5 | 0.9 | 0.5 |
| 5+ pts 34% · 2+ reb 42% · 1+ threes 37% | |||||
| Shariah GailesF | 20 | 9.7 | 5.4 | 0.8 | 0.3 |
| 10+ pts 46% · 6+ reb 44% · 1+ threes 24% | |||||
| Mary CoppleG | 16 | 2.7 | 1.4 | 0.8 | 0.7 |
| 5+ pts 22% · 2+ reb 37% · 1+ threes 47% | |||||
| Celena GrantG | 16 | 3.4 | 2.0 | 0.9 | 0.4 |
| 5+ pts 29% · 2+ reb 54% · 1+ threes 30% | |||||
Cornell
| Player | Min | Pts | Reb | Ast | 3s |
|---|---|---|---|---|---|
| Clarke JacksonG | 25 | 8.6 | 4.7 | 2.4 | 0.5 |
| 10+ pts 38% · 5+ reb 48% · 3+ ast 41% | |||||
| Kelsey LangstonG | 22 | 2.5 | 2.4 | 3.6 | 0.4 |
| 5+ pts 20% · 3+ reb 41% · 4+ ast 47% | |||||
| Paige EngelsG | 21 | 3.9 | 2.2 | 2.4 | 0.5 |
| 5+ pts 35% · 2+ reb 59% · 3+ ast 42% | |||||
| Rachel KausF | 20 | 8.4 | 4.1 | 1.1 | 0.5 |
| 10+ pts 36% · 4+ reb 55% · 1+ threes 36% | |||||
| Katie LeonardG | 19 | 9.4 | 2.2 | 1.6 | 1.8 |
| 10+ pts 44% · 2+ ast 46% · 2+ threes 48% | |||||
| Audrey ChenG | 19 | 7.4 | 1.9 | 2.0 | 1.4 |
| 5+ pts 68% · 2+ reb 51% · 2+ ast 56% | |||||
| Ally PapeG | 16 | 6.8 | 2.7 | 0.9 | 1.1 |
| 5+ pts 64% · 3+ reb 47% · 1+ threes 61% | |||||
| Ashley ChildersF | 15 | 4.7 | 3.5 | 0.7 | 0.4 |
| 5+ pts 43% · 4+ reb 45% · 1+ threes 32% | |||||
Our own projections from each player's minutes and production, this opponent and the game's pace: not a sportsbook's lines. Under each name, the round numbers the player is about as likely as not to reach. How they have done
Win probability
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