Georgia State Panthers vs Charlotte 49ers basketball final score
Thu, Nov 5 · 7:00 PM ET · Halton Arena, Charlotte, NC
Our play
How our line is built
each step, from an even game to our lineThe spread is seen from the home side: a plus moves it toward Charlotte. Our total joins once both teams have played 3 games.
Pace & total
possessions per 40 minutesProjected possessions: 67.5, from each team's opponent-adjusted tempo. On raw season pace, Georgia St is the faster team (71.0, #152 of 365) and Charlotte the slower (65.4, #261). When tempos clash, the slower team usually pulls the pace harder (weights 0.80 vs 0.66).
How this game plays
points this game from the four factors, vs an average D-I matchupShot diet
Where each offense shoots from and where each defense lets teams shoot| Zone | D-I avg | ||
|---|---|---|---|
| Rim | 35.3%#278 | 57.7%#137 | 58.7% |
| Short 2 (≤9 ft) | 40.0%#103 | 40.0%#158 | 36.5% |
| Mid 2 (10 ft+) | 42.9%#90 | 40.0%#167 | 35.6% |
| Three | 42.9%#44 | 30.0%#118 | 32.5% |
| Zone | D-I avg | ||
|---|---|---|---|
| Rim | 55.6%#164 | 68.0%#214 | 58.7% |
| Short 2 (≤9 ft) | 50.0%#59 | 40.0%#158 | 36.5% |
| Mid 2 (10 ft+) | 42.9%#90 | 0.0%#1 | 35.6% |
| Three | 48.0%#20 | 38.1%#210 | 32.5% |
Zones from play-by-play shot descriptions; garbage time removed. Bars show the share of field-goal attempts in each zone; where a slice is too thin for its number, the shares are listed under the bar. FG% ranks: #1 = best for that side (most accurate shooting, stingiest defense).
Shot volume
Extra scoring chances from rebounds, turnovers and the foul lineCharlotte has more extra scoring chances per game: +0.8 (#134 of 365) to Georgia St’s −9.8 (#231).
Grade = extra shots and foul-line trips per game compared with a D-I average team, built from six season rates. Cell shading is the national rank for each rate (greener = better for that team).
Rotation
| # | Player | Pos | Cl | Ht | GP-GS | MPG | PPG | RPG | APG | TOV | eFG% | 3P% | 3PA/g | FT% | Usage |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 14 | G | Jr | 6'0" | 3-3 | 36.0 | 17.0 | 3.3 | 1.3 | 1.3 | 56.7% | 37.5% | 13.3 | — | 25.3% | |
| 4 | G | Sr | 6'2" | 3-3 | 35.0 | 15.3 | 2.3 | 6.3 | 2.7 | 46.2% | 33.3% | 4.0 | 62.5% | 29.1% | |
| 12 | G | Sr | 6'2" | 3-3 | 34.7 | 12.7 | 4.0 | 3.3 | 1.0 | 40.0% | 19.0% | 7.0 | 76.9% | 23.7% | |
| 10 | F | Jr | 6'7" | 3-3 | 29.7 | 14.3 | 10.3 | 1.7 | 1.3 | 70.0% | 75.0% | 2.7 | 25.0% | 22.6% | |
| 0 | G | So | 6'6" | 3-2 | 24.0 | 13.0 | 5.0 | 0.7 | 1.0 | 80.6% | 25.0% | 1.3 | 58.8% | 22.4% | |
| 50 | C | Sr | 6'10" | 3-1 | 15.3 | 1.3 | 3.7 | 0.3 | 1.3 | 33.3% | — | 0.0 | 0.0% | 13.3% | |
| 15 | F | So | 6'7" | 2-0 | 15.0 | 4.5 | 4.5 | 0.5 | 0.5 | 44.4% | 0.0% | 1.5 | 50.0% | 19.1% | |
| 11 | F | Sr | 6'10" | 3-0 | 9.7 | 3.0 | 2.7 | 0.3 | 0.3 | 66.7% | — | 0.0 | 50.0% | 14.5% | |
| 2 | G | Fr | 6'2" | 1-0 | 12.0 | 10.0 | 1.0 | 0.0 | 1.0 | 83.3% | 66.7% | 3.0 | — | 30.3% | |
| 32 | G | Fr | 6'0" | 1-0 | 5.0 | 2.0 | 0.0 | 1.0 | 0.0 | 50.0% | — | 0.0 | — | 20.8% |
Trends
Results against the closing spread and total, last ten games, entering this game| Date | Opponent | Site | Result | Total | PPP for | PPP vs | Pace | |||
|---|---|---|---|---|---|---|---|---|---|---|
| Nov 2 | Bowling Green | H | L 73–76 | −3.5 | L−6.5 | 162.0 | U149 | 102.8 | 107.0 | 71.0 |
| Mar 3 | Louisiana | N | L 75–84 | −1.0 | L−10.0 | 134.0 | O159 | 108.3 | 121.3 | 69.3 |
| Feb 27 | Old Dominion | H | L 73–81 | +1.0 | L−7.0 | 149.5 | O154 | 99.1 | 109.9 | 73.7 |
| Feb 24 | Coastal | H | L 71–76 | +1.0 | L−4.0 | 141.0 | O147 | 105.9 | 113.3 | 67.1 |
| Feb 21 | James Madison | H | L 65–80 | +2.5 | L−12.5 | 142.5 | O145 | 97.0 | 119.4 | 67.0 |
| Feb 19 | GA Southern | H | W 66–64 | +1.0 | W+3.0 | 155.0 | U130 | 96.2 | 93.3 | 68.6 |
| Feb 14 | Old Dominion | A | L 55–78 | +4.0 | L−19.0 | 147.0 | U133 | 85.2 | 120.8 | 64.6 |
| Feb 12 | James Madison | A | L 79–81 OT | +6.0 | W+4.0 | 144.0 | O160 | 106.8 | 109.5 | 74.0 |
| Feb 7 | N Illinois | H | L 74–75 | −4.5 | L−5.5 | 142.0 | O149 | 103.4 | 104.8 | 71.6 |
| Feb 4 | Troy | H | L 63–74 | +5.5 | L−5.5 | 145.5 | U137 | 98.6 | 115.9 | 63.9 |
| Date | Opponent | Site | Result | Total | PPP for | PPP vs | Pace | |||
|---|---|---|---|---|---|---|---|---|---|---|
| Nov 2 | Indiana St | A | W 78–70 | −5.5 | W+2.5 | 152.5 | U148 | 119.3 | 107.1 | 65.4 |
| Mar 14 | South Florida | N | L 64–86 | +15.5 | L−6.5 | 153.5 | U150 | 93.1 | 125.1 | 68.7 |
| Mar 13 | UAB | N | W 83–78 | +5.5 | W+10.5 | 148.0 | O161 | 124.7 | 117.2 | 66.6 |
| Mar 12 | Tulane | N | W 74–60 | −1.0 | W+13.0 | 144.5 | U134 | 121.3 | 98.3 | 61.0 |
| Mar 8 | South Florida | A | L 60–83 | +17.5 | L−5.5 | 155.5 | U143 | 91.0 | 125.9 | 65.9 |
| Mar 4 | UAB | H | L 74–80 | +2.0 | L−4.0 | 148.0 | O154 | 116.0 | 125.4 | 63.8 |
| Mar 1 | FAU | A | L 76–77 OT | +7.0 | W+6.0 | 148.0 | O153 | 104.9 | 106.2 | 72.5 |
| Feb 25 | North Texas | H | W 80–79 | +1.5 | W+2.5 | 133.5 | O159 | 126.4 | 124.8 | 63.3 |
| Feb 21 | East Carolina | H | W 68–56 | −4.5 | W+7.5 | 146.0 | U124 | 104.2 | 85.8 | 65.3 |
| Feb 18 | Tulsa | A | L 74–79 | +13.0 | W+8.0 | 152.0 | O153 | 112.7 | 120.3 | 65.7 |
Records vs the closing line describe the past; ten games is a small sample.
Team comparison
national rank toned left for away, right for homeOffseason
roster movement into this season — descriptive, not a model input- Malachi Brown 31.0 mpg, 12.3 ppg · transferred to W Carolina
- Micah Tucker 30.6 mpg, 13.1 ppg · transferred to Grand Canyon
- Jelani Hamilton 26.3 mpg, 15.0 ppg · transferred to FAU
- Anthony Enoh 20.8 mpg, 4.7 ppg · transferred to Kennesaw St
- Joah Chappelle 20.7 mpg, 6.3 ppg · transferred to Tulane
- Ayouba Berthe 16.9 mpg, 4.4 ppg · not on a D1 roster yet
- Jaden Jackson from S Dakota St · 32.1 mpg, 12.3 ppg last season
- Eric Parnell from FDU · 25.7 mpg, 10.7 ppg last season
- Jacob Meyer from UAB · 24.9 mpg, 10.8 ppg last season
- Terrance Dixon Jr. from Southern · 20.5 mpg, 9.0 ppg last season
- Jacolb Fredson-Cole from McNeese · 18.7 mpg, 5.5 ppg last season
- Zion Wilburn from Samford · 16.0 mpg, 4.3 ppg last season
Returns 2% of last season's minutes; lost 5 of its top 5 (5 transferred). Teams returning under 40% of last season's minutes have historically fallen about 0.8 points of AdjEM (n=716 team-seasons, 2022-2026).
- Ben Bradford 28.2 mpg, 13.5 ppg · transferred to Charleston
- Dezayne Mingo 26.9 mpg, 12.2 ppg · not on a D1 roster yet
- Anton Bonke 25.6 mpg, 10.6 ppg · transferred to Michigan St
- Damoni Harrison 18.3 mpg, 8.6 ppg · not on a D1 roster yet
- Spencer Elliott 17.2 mpg, 4.1 ppg · transferred to UNC Wilmington
- Major Freeman 14.1 mpg, 5.1 ppg · not on a D1 roster yet
- Dorian Finister from Louisiana · 30.5 mpg, 14.0 ppg last season
- Dylan Grant from Rutgers · 24.1 mpg, 9.5 ppg last season
- Jayden Fort from Georgetown · 13.6 mpg, 3.3 ppg last season
- Keyshuan Tillery from Cincinnati · 11.6 mpg, 3.5 ppg last season
- Tyler McKinley from Cincinnati · 9.2 mpg, 1.3 ppg last season
- Peyton Marshall from Georgia Tech · 6.2 mpg, 1.9 ppg last season
Returns 9% of last season's minutes; lost 4 of its top 5 (2 transferred). Teams returning under 40% of last season's minutes have historically fallen about 0.8 points of AdjEM (n=716 team-seasons, 2022-2026).
Line history
Market line, home spread or game totalLines by book
| Book | Spread (home) open → now | Total open → now | ML home | ML away |
|---|---|---|---|---|
| DraftKings | -11.5-112 | 152.5→143.5o-118 u-102 | -750 | +525 |
| FanDuel | -11.5-115 | 149.5→143.5o-110 u-110 | -800 | +540 |
| BetMGM | -11.5-110 | 151.5→143.5o-110 u-110 | -800 | +550 |
| BetRivers | -11.5-121 | 152.5→143.5o-114 u-109 | -835 | +525 |
| Caesars | -11.5-110 | 152→143.5o-110 u-110 | -800 | +550 |
| Fanatics | -12→-11.5-105 | 149.5→143.5o-115 u-105 | -750 | +525 |
| BetOnline | -11.5-110 | 149→143.5o-115 u-105 | -760 | +538 |
| Bovada | -11.5-105 | 150.5→143.5o-110 u-110 | -800 | +525 |
| theScore Bet | -11.5-110 | 148.5→143.5o-115 u-105 | -750 | +475 |
| Hard Rock | -11.5-120 | 152.5→143.5o-110 u-110 | -850 | +525 |
| Kalshi | -11.5-104 | 143.5o-108 u+104 | -669 | +614 |
| Polymarket | -11.5-104 | 144.5o+104 u-113 | -669 | +614 |
| Novig | -11.5-104 | 152.5→143.5o-108 u+104 | -641 | +614 |
Head-to-head
this season and lastMore games on Thu, Nov 5
- McNeese at North Texas · 5:00 PM ET
- Wake Forest at Vanderbilt · 6:00 PM ET
- Bellarmine at Indiana · 6:00 PM ET
- Chattanooga at Penn State · 6:00 PM ET
- Long Island at Seton Hall · 6:30 PM ET
- Buffalo at Pitt · 7:00 PM ET
- C Connecticut at Syracuse · 7:00 PM ET
- Binghamton at Saint Peter's · 7:00 PM ET
- Chicago St at Incarnate Word · 7:00 PM ET
- Mercyhurst at Notre Dame · 7:00 PM ET
- Mercer at Virginia Tech · 7:00 PM ET
- Vermont at Fairfield · 7:00 PM ET
- NJIT at Iona · 7:00 PM ET
- UMBC at Marist · 7:00 PM ET
- Delaware St at Navy · 7:00 PM ET
- UAlbany at Manhattan · 7:00 PM ET
- UMass Lowell at Merrimack · 7:00 PM ET
- Bryant at Quinnipiac · 7:00 PM ET
- New Hampshire at Rider · 7:00 PM ET
- Maine at Sacred Heart · 7:00 PM ET
- Green Bay at Cincinnati · 7:00 PM ET
- Cornell at Lehigh · 7:00 PM ET
- Hofstra at Princeton · 7:00 PM ET
- Howard at Alcorn St · 7:00 PM ET
- N'Western St at Mississippi St · 7:30 PM ET
- Stonehill at Fordham · 7:30 PM ET
- Jackson St at Tulane · 7:30 PM ET
- Jacksonville at Florida · 8:00 PM ET
- Gardner-Webb at Texas · 8:00 PM ET
- Le Moyne at Creighton · 8:00 PM ET
- Coastal at Duke · 8:00 PM ET
- West Georgia at Loyola Chicago · 8:00 PM ET
- VMI at SMU · 8:00 PM ET
- N Illinois at Tulsa · 8:00 PM ET
- East Texas A&M at Rice · 8:00 PM ET
- Toledo at Michigan St · 8:00 PM ET
- Jax State at South Alabama · 8:00 PM ET
- South Florida at DePaul · 8:30 PM ET
- Penn at Illinois · 8:30 PM ET
- Bethune at Texas Tech · 9:00 PM ET
- Towson at Utah · 9:00 PM ET
- Cal Poly at Arizona · 10:30 PM ET
The CBB Matchups tab lays out the day's Division I slate: matchup, tip time, records and rank, and — once posted — the market spread and total (the median across books when no market line is up). Three views switch the table between projected scores, pace and totals, and each team's offensive and defensive tendencies. Each game opens into opponent-adjusted possessions, efficiency and four-factor tendencies for both teams, plus recent form, rotation and head-to-head history. Every game also carries our projected score, spread and total, from our line: the same view our bets are made from.
What these numbers mean: line shopping.