Arkansas-Pine Bluff Golden Lions vs UCLA Bruins basketball prediction & odds

Wed, Nov 11 · 9:00 PM ET · Pauley Pavilion, Los Angeles, CA

Non-conferencePeacockPauley Pavilion, Los Angeles, CA
AR-Pine Bluff
0-2 · 0-0 conf
Efficiency #357
@
9UCLA
2-0 · 0-0 conf
Efficiency #25
Wed, Nov 11 · 9:00 PM ET
60.596.0
Projected score
UAPB win 0%UCLA win 100%
No line posted yet.

Our play

How our line is built

each step, from an even game to our line
Spread
Even game
0.0
UCLArated 14.6 above average
+14.6
AR-Pine Bluffrated 16.6 below average
+16.6
Home court
+4.2
Our line
UCLA −35.4
◂ AR-Pine Bluff sideUCLA side ▸

The spread is seen from the home side: a plus moves it toward UCLA. Our total joins once both teams have played 3 games.

Pace & total

possessions per 40 minutes
Tempo, possessions per 40 minutes

Projected possessions: 74.6, from each team's opponent-adjusted tempo. On raw season pace, AR-Pine Bluff is the faster team (80.0, #16 of 365) and UCLA the slower (76.9, #40). When tempos clash, the slower team usually pulls the pace harder (weights 0.80 vs 0.66).

Projected possessions
74.6
per team, 40 min
Adjusted tempo, vs an average opponent
74.5#23
AR-Pine Bluff
70.7#172
UCLA

How this game plays

points this game from the four factors, vs an average D-I matchup
Our line
UCLA −35.4
Four factors +41.7 · not in these stats −6.3
From the four factors
UCLA has the ball+19.9
AR-Pine Bluff has the ball−21.9
UCLA has the ball
✓Takes care of the ballTO% 9.7% #4 · UAPB forces 12.5% #322 · ~7 turnovers+7.8
✓Shoots it welleFG% 54.6% #118 · UAPB allows 55.5% #268+5.5
✓Wins second chancesOR% 34.5% #116 · UAPB allows 48.7% #353+4.7
✓Gets to the lineFTR 41.8% #118 · UAPB allows 61.8% #342 · FT 74.6% #111+1.9
AR-Pine Bluff has the ball
✗Tough shooting lookeFG% 42.4% #300 · UCLA allows 41.1% #35−9.9
✗Coughs it upTO% 36.3% #359 · UCLA forces 18.2% #168 · ~21 turnovers−9.4
✗Few second chancesOR% 28.6% #233 · UCLA allows 24.7% #59−2.4
✗Few trips to the lineFTR 36.2% #188 · UCLA allows 40.7% #221 · FT 65.8% #246−0.1

Shot diet

Where each offense shoots from and where each defense lets teams shoot
AR-Pine Bluffoffense vs#9UCLAdefense
Share of shots by zone
AR-Pine Bluff shoots
UCLA allows
D-I average
FG% by zone
ZoneD-I avg
Rim71.4%#3845.7%#4358.0%
Short 2 (≤9 ft)22.2%#26633.3%#12538.2%
Mid 2 (10 ft+)16.7%#29810.0%#2634.7%
Three26.8%#25826.6%#7632.5%
#9UCLAoffense vsAR-Pine Bluffdefense
Share of shots by zone
UCLA shoots
AR-Pine Bluff allows
D-I average
FG% by zone
ZoneD-I avg
Rim54.8%#22689.3%#35858.0%
Short 2 (≤9 ft)66.7%#2933.3%#12538.2%
Mid 2 (10 ft+)37.5%#14223.1%#7634.7%
Three41.4%#4723.4%#3532.5%
RimShort 2 (≤9 ft)Mid 2 (10 ft+)Three

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 line
AR-Pine Bluff
−29.9extra scoring chances per game vs a D-I average team#359 of 365
Off reb %
28.6%
#233
Def reb %
51.3%
#353
Turnover %
36.3%
#359
Forced TO %
12.5%
#322
FT rate
36.2%
#188
FT allowed
61.8%
#342
Where the chances come from (per game)
Offensive rebounding−1.0
Defensive rebounding−5.7
Ball security−12.8
Forcing turnovers−3.9
Foul shots drawn−0.3
Foul shots allowed−6.2
#9UCLA
+9.9extra scoring chances per game vs a D-I average team#54 of 365
Off reb %
34.5%
#116
Def reb %
75.3%
#59
Turnover %
9.7%
#4
Forced TO %
18.2%
#168
FT rate
41.8%
#118
FT allowed
40.7%
#221
Where the chances come from (per game)
Offensive rebounding+1.0
Defensive rebounding+2.3
Ball security+6.0
Forcing turnovers+0.1
Foul shots drawn+1.2
Foul shots allowed−0.7

UCLA has more extra scoring chances per game: +9.9 (#54 of 365) to AR-Pine Bluff’s −29.9 (#359).

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

Who has been playing, and who has not
AR-Pine Bluff2026-27 numbers · last game: Baylor, Nov 6
#PlayerPosClHtGP-GSMPGMin/40, last 8Last 3 vs beforeStatusPPGRPGAPGTOVeFG%3P%3PA/gFT%Usage
1GSr6'4"2-234.037—Started last13.55.02.56.050.0%20.0%2.566.7%26.4%
22FSr6'8"2-126.029—Bench7.54.52.04.054.2%100.0%0.566.7%20.3%
5FJr6'7"2-123.517—Bench7.52.01.01.546.9%30.0%5.0—20.1%
23GFr6'3"2-122.522—Started last5.51.01.53.541.7%28.6%3.550.0%22.2%
10GFr6'4"2-018.08—Bench4.01.51.01.522.2%0.0%0.566.7%20.8%
3GSo6'7"2-117.516—Bench2.03.50.03.015.0%20.0%2.550.0%24.1%
9FSr6'7"1-129.036—Started last13.06.00.06.038.5%0.0%3.0100.0%33.9%
0GJr6'7"2-112.09—Started last0.01.50.02.00.0%—0.0—12.4%
4FFr6'8"2-112.011—Started last5.01.50.02.570.0%50.0%1.060.0%25.8%
7GSr6'7"2-09.510—Bench5.51.00.50.555.6%28.6%3.550.0%28.5%
8GJr6'7"2-16.07—Bench0.01.00.00.0——0.0—0.0%
6GSr6'4"2-02.5——Active0.00.00.00.0——0.0—0.0%
11GJr6'3"1-04.0——Missed last0.00.00.00.0——0.0—0.0%

Competitive minutes leave out garbage time (provisional rule: a second-half lead of 25+ inside 15:00, 20+ inside 10:00, 15+ inside 5:00 or 10+ inside 2:00, held to the end) and are shown per 40 minutes. Status says only whether a player appeared; the reason is not published.

Team comparison

national rank toned left for away, right for home
AR-Pine Bluff#9UCLA
Efficiency
96.2
117.1
114.0
99.0
74.5
70.7
14.2
3.2
Shooting
42.4%
54.6%
43.8%
49.4%
26.8%
41.4%
65.8%
74.6%
36.2%
41.8%
Ball control & glass
36.3%
9.7%
12.5%
18.2%
28.6%
34.5%
48.7%
24.7%
23.1%
3.9%
21.9%
9.6%
Style
39.0%
41.1%
43.9%
34.3%
9.6%
19.2%
43.6%
61.5%
47.3%
32.4%
Roster
2.82
2.48
6'5.9"
6'5.9"
2.7%
43.3%

Offseason

roster movement into this season — descriptive, not a model input
AR-Pine Bluff
Returning minutes: 2.7%Returning production: 1.8%
Lost
  • Quion Williams 36.1 mpg, 17.7 ppg · not on a D1 roster yet
  • Trevon Payton 33.8 mpg, 10.0 ppg · transferred to Bradley
  • Alex Mirhosseini 30.9 mpg, 11.3 ppg · not on a D1 roster yet
  • Milhan Charles 28.3 mpg, 9.9 ppg · transferred to FAU
  • Jaquan Scott 27.6 mpg, 15.5 ppg · not on a D1 roster yet
  • Ramel Lloyd Jr. 13.2 mpg, 4.3 ppg · not on a D1 roster yet
Added
  • Elijah Hernandez new to D1 · 37.0 mpg, 16.0 ppg last season
  • Jalen Tatum from Jackson St · 8.8 mpg, 2.6 ppg last season
  • David Giddens from Cleveland St · 6.8 mpg, 2.5 ppg last season
  • Macaleab Rich from UTSA · 5.5 mpg, 3.0 ppg last season
  • CJ Smith from UTEP · 2.6 mpg, 0.5 ppg last season
  • Cedric Dixon no D1 minutes last season

Returns 3% of last season's minutes; lost 5 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).

#9UCLA
Returning minutes: 47.6%Returning production: 44.3%
Lost
  • Donovan Dent 33.5 mpg, 12.9 ppg · transferred to LSU
  • Tyler Bilodeau 26.0 mpg, 15.2 ppg · not on a D1 roster yet
  • Skyy Clark 20.7 mpg, 8.3 ppg · transferred to LSU
  • Jamar Brown 15.6 mpg, 3.8 ppg · not on a D1 roster yet
  • Steven Jamerson II 9.4 mpg, 1.8 ppg · not on a D1 roster yet
  • Anthony Peoples Jr. 0.3 mpg, 0.1 ppg · not on a D1 roster yet
Added
  • Jaylen Petty from Texas Tech · 29.5 mpg, 9.6 ppg last season
  • Filip Jovic from Auburn · 17.8 mpg, 6.1 ppg last season
  • Sergej Macura from Mississippi St · 16.2 mpg, 4.4 ppg last season
  • Azavier Robinson from Butler · 12.6 mpg, 4.2 ppg last season
  • Joe Philon III no D1 minutes last season
  • Gunars Grinvalds no D1 minutes last season

Returns 48% of last season's minutes; lost 3 of its top 5 (2 transferred).

Head-to-head

this season and last
No meetings the last two seasons.

More games on Wed, Nov 11

← Tue, Nov 10 · Thu, Nov 12 → · Full season schedule

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.