Texas Southern at UC San Diego
Monday, November 16, 2026, 10:00 PM ET at LionTree Arena. Texas Southern our rank 347 · 1-2; UC San Diego our rank 113 · 2-0.
Who will win Texas Southern vs UC San Diego?
The model gives UC San Diego a 96% chance to beat Texas Southern, with a projected score of UC San Diego 86, Texas Southern 66.
Half of games like thisFour in five
Calls of 90–100% have been right 95.4% of the time in 11,767 past games, and the typical miss on the margin is 8.8 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 |
|---|---|---|---|---|---|
| UC San Diego | |||||
| BarnoG · 29 min | 13.8 | 3.4 | 4.4 | 15+ 41% | |
| BeathF · 30 min | 13.6 | 5.3 | 1.8 | 15+ 40% | |
| EaglestaffG · 26 min | 13.1 | 5.3 | 2.2 | 15+ 37% | |
| DotsonG · 20 min | 9.7 | 2.9 | 1.8 | 10+ 46% | |
| Texas Southern | |||||
| PattersonG · 22 min | 11.6 | 3.0 | 1.3 | 10+ 59% | |
| KimbroughG · 28 min | 10.4 | 2.6 | 2.3 | 10+ 51% | |
| BilalG · 31 min | 10.3 | 2.7 | 1.9 | 10+ 50% | |
| VungoG · 25 min | 8.0 | 6.9 | 0.7 | 10+ 34% | |
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 Treysen Eaglestaff: Texas Southern 6%UC San Diego 94%
The white mark is the call with him: UC San Diego 96%.
| Player | Points a game he adds | UC San Diego without him | Change | Projected score |
|---|---|---|---|---|
| UC San Diego | ||||
| Treysen Eaglestaff | 2.1 | 94% | −2 | 67–85 |
| Leo Beath | 1.8 | 94% | −2 | 67–85 |
| Tom Beattie | 1.1 | 95% | −1 | 67–86 |
| Rahmir Barno | 0.8 | 95% | −1 | 67–86 |
Change is in UC San Diego's win chance, in points. Scores read Texas Southern, then UC San Diego. A player's value is what the team is better by with him than with a replacement, from the player ratings.
Model against the line
Your call
All of today's gamesPlay-by-play
Team numbers
Form
Texas Southern 1-2LLW
- Nov 10W 98-78vs College of Biblical Studies
- Nov 6L 51-92at LSUDidn't cover +35.5 · Under 161.5
- Nov 2L 79-103at Grand Canyon
- Last 3
- 1–2, scoring 76.0 and allowing 91.0
- Against the spread, this season
- 0–1
- Totals, this season
- 0 over, 1 under
UC San Diego 2-0WW
- Last 2
- 2–0, scoring 90.5 and allowing 70.0
- Against the spread, this season
- 1–0
- Totals, this season
- 0 over, 1 under
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
| Texas Southern | UC San Diego | |
|---|---|---|
| Points scored per 100 possessions | 96.4 320th | 107.1 123rd |
| Points allowed per 100 | 115.4 343rd | 104.8 113th |
| Possessions a game | 72.3 49th | 70.8 184th |
| Shooting (effective field-goal %) | 48.4% 319th | 50.9% 153rd |
| Opponents' shooting | 52.1% 291st | 50.1% 155th |
| Turnovers, share of possessions | 17.2% 83rd | 17.6% 121st |
| Offensive rebounds, share of misses | 30.3% 267th | 31.0% 231st |
| Free throws per shot | 0.29 67th | 0.23 325th |
The widest gap: UC San Diego's offense (123rd) against Texas Southern's defense (343rd), of 365 teams.
First half
- Projected halftime score
- Texas Southern 30, UC San Diego 41
- First-half margin
- UC San Diego by 11.1
- First-half points, both teams
- 71.6
- Projected second half
- Texas Southern 36, UC San Diego 45
- Second-half points, both teams
- 81.0
- Tied at the half
- 4%
- Texas Southern, first halves so far
- Led 1 of 3 · 35.7 scored, 44.0 allowed
- UC San Diego, first halves so far
- Led 0 of 2 · 36.0 scored, 40.0 allowed
Our own projection, not a sportsbook's first-half line. On 11,516 past games it had not seen, the halftime leader was right 67.2% of the time and the first-half total was off by 8.1 points on average. This season: 366 of 476 halftime leaders right. Scorecard
Player projections
Texas Southern
| Player | Min | Pts | Reb | Ast | 3s |
|---|---|---|---|---|---|
| Karris BilalG | 31 | 10.3 | 2.7 | 1.9 | 1.0 |
| 10+ pts 50% · 3+ reb 48% · 2+ ast 54% | |||||
| Jason KimbroughG | 28 | 10.4 | 2.6 | 2.3 | 1.5 |
| 10+ pts 51% · 3+ reb 46% · 2+ threes 42% | |||||
| Ben VungoG | 25 | 8.0 | 6.9 | 0.7 | 0.5 |
| 10+ pts 34% · 7+ reb 50% · 1+ threes 41% | |||||
| Kehlin FarooqG | 23 | 4.7 | 4.3 | 1.1 | 0.8 |
| 5+ pts 43% · 4+ reb 58% · 1+ threes 53% | |||||
| Cameron PattersonG | 22 | 11.6 | 3.0 | 1.3 | 0.4 |
| 10+ pts 59% · 3+ reb 53% · 2+ ast 35% | |||||
| Josh AkpovwaF | 19 | 5.1 | 2.8 | 0.4 | 0.1 |
| 5+ pts 47% · 3+ reb 49% | |||||
| Xander WedlowF | 16 | 5.7 | 3.0 | 0.3 | 0.2 |
| 5+ pts 53% · 3+ reb 52% · 1+ threes 17% | |||||
| Sayed SayedG | 14 | 3.3 | 1.9 | 0.9 | 0.5 |
| 5+ pts 28% · 2+ reb 51% · 1+ threes 41% | |||||
UC San Diego
| Player | Min | Pts | Reb | Ast | 3s |
|---|---|---|---|---|---|
| Leo BeathF | 30 | 13.6 | 5.3 | 1.8 | 1.1 |
| 15+ pts 40% · 5+ reb 56% · 2+ ast 51% | |||||
| Rahmir BarnoG | 29 | 13.8 | 3.4 | 4.4 | 0.3 |
| 15+ pts 41% · 4+ reb 43% · 5+ ast 45% | |||||
| Treysen EaglestaffG | 26 | 13.1 | 5.3 | 2.2 | 1.8 |
| 15+ pts 37% · 5+ reb 57% · 2+ threes 48% | |||||
| Alex ChaikinG | 22 | 8.2 | 2.3 | 1.0 | 2.0 |
| 10+ pts 35% · 2+ reb 61% · 2+ threes 53% | |||||
| Kayde DotsonG | 20 | 9.7 | 2.9 | 1.8 | 1.8 |
| 10+ pts 46% · 3+ reb 51% · 2+ threes 50% | |||||
| Jake HolmesF | 18 | 6.6 | 3.7 | 1.0 | 0.7 |
| 5+ pts 61% · 4+ reb 47% · 1+ threes 48% | |||||
| Tom BeattieG | 17 | 7.6 | 3.0 | 1.9 | 0.9 |
| 5+ pts 69% · 3+ reb 53% · 2+ ast 53% | |||||
| Dimitrije VukicevicC | 17 | 5.6 | 4.7 | 1.0 | 0.1 |
| 5+ pts 52% · 5+ reb 47% · 2+ ast 26% | |||||
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
Game chat
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