Who will win Fordham vs Manhattan?
The model gives Fordham a 62% chance to beat Manhattan, with a projected score of Fordham 64, Manhattan 60.
Half of games like thisFour in five
Calls of 60–70% have been right 64.3% of the time in 7,507 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 |
|---|---|---|---|---|---|
 Fordham | |||||
| EdwardsG · 35 min | 14.2 | 2.5 | 1.3 | 15+ 44% | |
| SirtautaiteF · 26 min | 12.7 | 6.5 | 0.6 | 15+ 35% | |
| EasleyG · 30 min | 10.7 | 3.3 | 4.0 | 10+ 53% | |
| KulykG · 19 min | 9.0 | 2.8 | 0.5 | 10+ 41% | |
 Manhattan | |||||
| MurtaghG · 33 min | 12.5 | 3.5 | 1.8 | 10+ 65% | |
| Grgicevich LasseyG · 30 min | 8.8 | 3.4 | 2.3 | 10+ 40% | |
| BaumgarteF · 31 min | 8.5 | 6.3 | 2.1 | 10+ 37% | |
| HarperG · 24 min | 6.5 | 2.1 | 1.7 | 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 Olivia Kulyk: Fordham 58%Manhattan 42%
The white mark is the call with her: Fordham 62%.
| Player | Points a game she adds | Fordham without her | Change | Projected score |
|---|---|---|---|---|
| Fordham | ||||
| Olivia Kulyk | 1.5 | 58% | −4 | 63–60 |
| Ugne Sirtautaite | 1.0 | 59% | −3 | 63–60 |
Change is in Fordham's win chance, in points. Scores read Fordham, then Manhattan. 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
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
| Fordham | Manhattan | |
|---|---|---|
| Points scored per 100 possessions | 87.4 228th | 79.0 322nd |
| Points allowed per 100 | 94.4 179th | 95.5 209th |
| Possessions a game | 72.1 164th | 72.0 179th |
| Shooting (effective field-goal %) | 47.6% 67th | 44.7% 231st |
| Opponents' shooting | 45.6% 181st | 44.4% 119th |
| Turnovers, share of possessions | 24.8% 272nd | 24.0% 219th |
| Offensive rebounds, share of misses | 32.8% 176th | 30.0% 317th |
| Free throws per shot | 0.23 61st | 0.19 316th |
The widest gap: Fordham's defense (179th) against Manhattan's offense (322nd), of 363 teams.
First half
- Projected halftime score
- Fordham 30, Manhattan 28
- First-half margin
- Fordham by 2.3
- First-half points, both teams
- 58.4
- Projected second half
- Fordham 33, Manhattan 32
- Second-half points, both teams
- 64.8
- Tied at the half
- 4%
- Fordham, first halves so far
- Led 3 of 4 · 39.0 scored, 30.8 allowed
- Manhattan, first halves so far
- Led 1 of 4 · 26.0 scored, 30.8 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
Fordham
| Player | Min | Pts | Reb | Ast | 3s |
|---|---|---|---|---|---|
| Lakresha EdwardsG | 35 | 14.2 | 2.5 | 1.3 | 2.5 |
| 15+ pts 44% · 3+ reb 42% · 3+ threes 42% | |||||
| Carryn EasleyG | 30 | 10.7 | 3.3 | 4.0 | 0.8 |
| 10+ pts 53% · 4+ ast 54% · 1+ threes 51% | |||||
| Anastasija VeljovicG | 27 | 8.2 | 5.6 | 1.1 | 0.6 |
| 10+ pts 35% · 6+ reb 47% · 1+ threes 42% | |||||
| Ugne SirtautaiteF | 26 | 12.7 | 6.5 | 0.6 | 0.1 |
| 15+ pts 35% · 7+ reb 45% | |||||
| Zala SrotF | 23 | 4.1 | 3.9 | 1.1 | 0.3 |
| 5+ pts 36% · 4+ reb 52% · 2+ ast 31% | |||||
| Caitlyn MartinG | 20 | 3.2 | 1.6 | 1.7 | 0.4 |
| 5+ pts 28% · 2+ reb 44% · 2+ ast 47% | |||||
| Olivia KulykG | 19 | 9.0 | 2.8 | 0.5 | 1.3 |
| 10+ pts 41% · 3+ reb 48% · 2+ threes 36% | |||||
| Precious OmosholaF | 14 | 3.0 | 3.8 | 0.3 | 0.0 |
| 5+ pts 25% · 4+ reb 48% | |||||
Manhattan
| Player | Min | Pts | Reb | Ast | 3s |
|---|---|---|---|---|---|
| Taylah MurtaghG | 33 | 12.5 | 3.5 | 1.8 | 1.8 |
| 10+ pts 65% · 2+ ast 52% · 2+ threes 50% | |||||
| Amanda BaumgarteF | 31 | 8.5 | 6.3 | 2.1 | 0.4 |
| 10+ pts 37% · 6+ reb 55% · 2+ ast 58% | |||||
| Olivia Grgicevich LasseyG | 30 | 8.8 | 3.4 | 2.3 | 0.8 |
| 10+ pts 40% · 4+ reb 43% · 1+ threes 49% | |||||
| Celeste HarperG | 24 | 6.5 | 2.1 | 1.7 | 1.3 |
| 5+ pts 61% · 2+ reb 56% · 2+ ast 49% | |||||
| Laura RingF | 22 | 6.4 | 4.2 | 1.0 | 0.9 |
| 5+ pts 60% · 4+ reb 56% · 1+ threes 54% | |||||
| Laia Izquierdo AltimiraF | 18 | 4.1 | 3.6 | 1.0 | 0.5 |
| 5+ pts 37% · 4+ reb 46% · 1+ threes 38% | |||||
| Ana ZesatiF | 16 | 4.7 | 3.2 | 0.8 | 0.1 |
| 5+ pts 43% · 3+ reb 57% · 2+ ast 21% | |||||
| Cortney HowellF | 14 | 3.7 | 3.3 | 0.4 | 0.1 |
| 5+ pts 33% · 3+ reb 59% | |||||
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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