Tennessee Tech at MTSU
Women's · Monday, November 16, 2026, 7:30 PM ET at Murphy Center. Tennessee Tech our rank 276 · 1-2; MTSU our rank 183 · 1-2.
Who will win Tennessee Tech vs MTSU?
The model gives Middle Tennessee a 84% chance to beat Tennessee Tech, with a projected score of MTSU 76, Tennessee Tech 63.
Half of games like thisFour in five
Calls of 80–90% have been right 85.0% of the time in 7,719 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 |
|---|---|---|---|---|---|
| MTSU | |||||
| BaugusG · 33 min | 15.5 | 8.6 | 1.7 | 15+ 52% | |
| WhitfieldG · 26 min | 11.8 | 3.4 | 2.3 | 10+ 61% | |
| KoneG · 30 min | 10.2 | 5.2 | 1.5 | 10+ 50% | |
| VerhulstG · 29 min | 7.2 | 3.6 | 2.5 | 5+ 67% | |
| Tennessee Tech | |||||
| MartinG · 32 min | 11.2 | 3.1 | 2.7 | 10+ 57% | |
| CawthornF · 25 min | 10.2 | 8.1 | 0.8 | 10+ 50% | |
| DavisG · 32 min | 9.6 | 2.5 | 1.7 | 10+ 45% | |
| FreemanG · 27 min | 8.5 | 2.4 | 2.6 | 10+ 37% | |
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 Blair Baugus: Tennessee Tech 22%MTSU 78%
The white mark is the call with her: MTSU 84%.
| Player | Points a game she adds | MTSU without her | Change | Projected score |
|---|---|---|---|---|
| MTSU | ||||
| Blair Baugus | 2.7 | 78% | −6 | 65–74 |
| Mya Kone | 0.8 | 82% | −2 | 64–75 |
| Tennessee Tech | ||||
| Karson Martin | 1.0 | 86% | +2 | 63–76 |
| LaReesha Cawthorn | 1.0 | 86% | +2 | 63–76 |
Change is in MTSU's win chance, in points. Scores read Tennessee Tech, then MTSU. 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
Tennessee Tech 1-2LWL
- Last 3
- 1–2, scoring 73.3 and allowing 87.0
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
| Tennessee Tech | MTSU | |
|---|---|---|
| Points scored per 100 possessions | 90.1 177th | 89.6 184th |
| Points allowed per 100 | 105.0 348th | 94.3 178th |
| Possessions a game | 72.6 129th | 71.3 251st |
| Shooting (effective field-goal %) | 45.6% 166th | 43.8% 290th |
| Opponents' shooting | 49.9% 357th | 46.2% 220th |
| Turnovers, share of possessions | 21.3% 31st | 26.2% 328th |
| Offensive rebounds, share of misses | 30.5% 298th | 34.4% 104th |
| Free throws per shot | 0.19 325th | 0.24 42nd |
The widest gap: MTSU's offense (184th) against Tennessee Tech's defense (348th), of 363 teams.
First half
- Projected halftime score
- Tennessee Tech 29, MTSU 36
- First-half margin
- MTSU by 7.1
- First-half points, both teams
- 65.8
- Projected second half
- Tennessee Tech 34, MTSU 39
- Second-half points, both teams
- 73.0
- Tied at the half
- 4%
- Tennessee Tech, first halves so far
- Led 1 of 3 · 33.7 scored, 42.0 allowed
- MTSU, first halves so far
- Led 1 of 3 · 34.0 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
Tennessee Tech
| Player | Min | Pts | Reb | Ast | 3s |
|---|---|---|---|---|---|
| Karson MartinG | 32 | 11.2 | 3.1 | 2.7 | 1.4 |
| 10+ pts 57% · 3+ reb 55% · 3+ ast 49% | |||||
| Savannah DavisG | 32 | 9.6 | 2.5 | 1.7 | 2.2 |
| 10+ pts 45% · 3+ reb 43% · 2+ ast 49% | |||||
| Evie FreemanG | 27 | 8.5 | 2.4 | 2.6 | 0.5 |
| 10+ pts 37% · 3+ reb 41% · 3+ ast 47% | |||||
| LaReesha CawthornF | 25 | 10.2 | 8.1 | 0.8 | 0.2 |
| 10+ pts 50% · 8+ reb 53% · 2+ ast 21% | |||||
| Morgan SieperG | 25 | 6.0 | 2.6 | 0.8 | 1.0 |
| 5+ pts 56% · 3+ reb 46% · 1+ threes 58% | |||||
| Amaya ReddF | 17 | 7.1 | 4.7 | 0.4 | 0.3 |
| 5+ pts 66% · 5+ reb 48% · 1+ threes 26% | |||||
| Amelia PfeifferC | 11 | 1.4 | 2.8 | 0.5 | 0.0 |
| 3+ reb 50% | |||||
MTSU
| Player | Min | Pts | Reb | Ast | 3s |
|---|---|---|---|---|---|
| Blair BaugusG | 33 | 15.5 | 8.6 | 1.7 | 0.3 |
| 15+ pts 52% · 9+ reb 47% · 2+ ast 49% | |||||
| Mya KoneG | 30 | 10.2 | 5.2 | 1.5 | 1.7 |
| 10+ pts 50% · 5+ reb 55% · 2+ threes 47% | |||||
| Kirston VerhulstG | 29 | 7.2 | 3.6 | 2.5 | 1.2 |
| 5+ pts 67% · 4+ reb 47% · 3+ ast 43% | |||||
| Xai WhitfieldG | 26 | 11.8 | 3.4 | 2.3 | 0.9 |
| 10+ pts 61% · 4+ reb 42% · 1+ threes 55% | |||||
| Carsyn SwaneyG | 21 | 5.5 | 2.4 | 0.8 | 1.1 |
| 5+ pts 52% · 3+ reb 41% · 1+ threes 61% | |||||
| Stanislava KabernickF | 18 | 3.0 | 5.1 | 1.1 | 0.6 |
| 5+ pts 25% · 5+ reb 53% · 1+ threes 40% | |||||
| Aaliyah BlanchardG | 18 | 6.0 | 3.9 | 1.0 | 0.8 |
| 5+ pts 57% · 4+ reb 50% · 1+ threes 49% | |||||
| Maayan CohenG | 14 | 3.8 | 1.9 | 0.9 | 0.8 |
| 5+ pts 33% · 2+ reb 52% · 1+ threes 52% | |||||
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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