CBB Matchups

Every D1 game with tempo-free ratings, four factors and market lines, one place.

College basketball is being built for the 2026-27 season (tip-off Nov 3). What's here fills in as games are played.

Non-conferenceThe Sobrato Center, San Francisco, CA

UNLV

Efficiency #124

2025-26: 18-17 · 12-10 conf

San Francisco

Efficiency #148

2025-26: 17-16 · 9-11 conf

Wed, Dec 2 · TBD

75.3

win 39%

Projected

78.4

win 61%

No line posted yet.

Model: SF −3.1 · total 153.7 · ratings as of Sat, Oct 3

Preseason ratings start from 2025-26's final adjusted ratings, regressed toward the D1 average. The stats below are 2025-26's too; both update once 2026-27 games are played.

How the projection is built

each step, from an average D-I game to this one

Projected total

Average D-I game

148.2

PaceAdjusted tempo: San Francisco 67.4, UNLV 69.9 → 69.0 possessions

+1.4

San Francisco offense vs UNLV defense

+1.6

UNLV offense vs San Francisco defense

+2.4

Projected total

153.7

Axis starts at 146 pointsPoints added or removed at each step

Projected margin

Even game

0.0

San Francisco offense vs UNLV defense

+1.6

UNLV offense vs San Francisco defense

−2.4

Home court+2.9 points per 100 possessions to the home offense, −2.9 to the visitors

+4.0

San Francisco by 3.1

3.1

UNLV side ◂▸ San Francisco side

Steps are rounded to one decimal, so they can differ from the total by 0.1: the total steps add to 153.6 against a projected 153.7, and the margin steps add to +3.2 against +3.1. The margin is the same build seen from the home side; positive numbers help San Francisco.

Pace & total

possessions per 40 minutes

Tempo, possessions per 40 minutes

Projected possessions: 69.0, from each team's opponent-adjusted tempo. On raw 2025-26 season pace, UNLV is the faster team (70.5, #75 of 365) and San Francisco the slower (66.7, #256). When tempos clash, the slower team usually pulls the pace harder (study weights 0.80 vs 0.66).

Projected possessions

69.0

per team, 40 min

Projected total

153.7

model

Projected team totals

75.3 / 78.4

UNLV / San Francisco

Adjusted tempo, vs an average opponent

69.9#55

UNLV

67.4#261

San Francisco

How this game plays

what the study found each side's numbers actually do when these two teams meet

AdvantageUNLV

Where UNLV scores: ball control

UNLV turns it over on 17.1% of possessions (#209); San Francisco forces turnovers on 14.1% of opponent possessions (#330). Expect about 15.3%, 1.5 points below an average D1 matchup — worth roughly +1.9 points per 100 possessions.

DefenseUNLV

UNLV's shot-blocking

UNLV ranks #33 nationally in block rate — one of the few defensive numbers that travels. Expect about 11.4% of San Francisco's two-point attempts to get blocked against this defense.

ClashUNLV

Strength vs strength: free-throw rate

UNLV (#51 in free-throw rate) against San Francisco (#51 in the same stat allowed) — both rank inside the national top 60. Expect about 34.5%. Historically San Francisco's own number has carried a bit more weight in that exchange (0.50 vs 0.61).

UNLV has the ball

OffenseSan Francisco allowsvs D1 avg

53.6% #81

50.8% #143

+1.5 pt/100

17.1% #209

14.1% #330

+1.9 pt/100

30.2% #189

29.0% #105

-0.5 pt/100

40.7% #51

29.6% #51

-0.1 pt/100

67.7% #331

—

-0.4 pt/100

UNLV net across the four factors + FT%, vs. a D1-average matchup: +2.4 pts/100

San Francisco has the ball

OffenseUNLV allowsvs D1 avg

51.2% #184

52.3% #231

+0.7 pt/100

15.8% #125

17.4% #126

+0.2 pt/100

31.3% #148

32.0% #256

+0.9 pt/100

40.1% #59

44.9% #349

+1.0 pt/100

70.9% #242

—

-0.1 pt/100

San Francisco net across the four factors + FT%, vs. a D1-average matchup: +2.7 pts/100

Shot diet

Where each offense shoots from and where each defense lets teams shoot · 2025-26 numbers

UNLVoffense vsSan Franciscodefense

Share of shots by zone

UNLV shoots

41.7

6.1

15.9

36.4

San Francisco allows

37.7

8.4

18.3

35.6

D-I average

38.5

6.4

15.8

39.3

FG% by zone

Zone			D-I avg
Rim	60.3%#111	59.3%#205	58.6%
Short 2 (≤9 ft)	40.0%#171	45.5%#312	39.5%
Mid 2 (10 ft+)	42.0%#58	35.0%#78	38.0%
Three	35.2%#102	34.1%#187	33.7%

San Franciscooffense vsUNLVdefense

Share of shots by zone

San Francisco shoots

34.3

4.9

14.3

46.5

UNLV allows

40.9

7.0

15.9

36.3

D-I average

38.5

6.4

15.8

39.3

FG% by zone

Zone			D-I avg
Rim	57.1%#229	58.5%#165	58.6%
Short 2 (≤9 ft)	41.5%#132	26.2%#2	39.5%
Mid 2 (10 ft+)	35.4%#278	42.7%#323	38.0%
Three	34.6%#140	35.2%#259	33.7%

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 · 2025-26 numbers

UNLV

−1.2extra scoring chances per game vs a D-I average team#244 of 365

Off reb %

30.2%

#189

Def reb %

68.0%

#256

Turnover %

17.1%

#209

Forced TO %

17.4%

#126

FT rate

40.7%

#51

FT allowed

44.9%

#349

Where the chances come from (per game)

Offensive rebounding−0.1

Defensive rebounding−0.4

Ball security−0.2

Forcing turnovers+0.5

Foul shots drawn+1.4

Foul shots allowed−2.5

San Francisco

+2.5extra scoring chances per game vs a D-I average team#78 of 365

Off reb %

31.3%

#148

Def reb %

71.0%

#105

Turnover %

15.8%

#125

Forced TO %

14.1%

#330

FT rate

40.1%

#59

FT allowed

29.6%

#51

Where the chances come from (per game)

Offensive rebounding+0.3

Defensive rebounding+0.5

Ball security+0.7

Forcing turnovers−1.8

Foul shots drawn+1.3

Foul shots allowed+1.5

San Francisco has more extra scoring chances per game: +2.5 (#78 of 365) to UNLV’s −1.2 (#244).

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

UNLV2025-26 numbers

ESPN hasn't posted UNLV's 2026-27 roster yet — these are last season's players.

#	Player	Pos	Cl	Ht	GP-GS	MPG	PPG	RPG	APG	TOV	eFG%	3P%	3PA/g	FT%	Usage
0	Dra Gibbs-Lawhorn	G	Jr	6'1"	35-35	34.2	20.7	3.1	2.5	2.5	59.5%	41.4%	7.0	83.8%	31.7%
2	Kimani Hamilton	F	Sr	6'8"	35-35	29.3	12.8	4.9	2.3	1.6	53.1%	34.3%	2.9	72.7%	24.8%
3	Howie Fleming Jr.	G	Sr	6'5"	32-27	29.1	9.0	6.3	3.7	2.0	50.0%	31.3%	2.6	80.2%	19.5%
6	Tyrin Jones	F	Fr	6'9"	32-15	27.0	11.9	5.0	1.4	1.1	59.8%	25.0%	0.3	48.8%	23.9%
12	Issac Williamson	G	Fr	6'0"	33-15	23.1	8.6	1.8	1.2	1.5	47.9%	33.3%	3.9	67.1%	24.3%
22	Walter Brown	F	Sr	6'5"	33-14	20.3	3.8	2.8	1.1	0.9	51.9%	34.7%	1.5	57.1%	12.7%
10	Jacob Bannarbie	F	So	6'9"	30-15	16.2	5.4	4.8	1.3	1.2	52.4%	25.0%	0.1	63.0%	21.1%
34	Emmanuel Stephen	C	So	7'0"	24-13	15.5	3.5	4.2	0.3	0.8	51.4%	0.0%	0.0	42.3%	15.9%
7	Al Green	G	Sr	6'3"	29-3	12.6	4.4	1.2	0.7	0.5	49.5%	31.1%	2.1	87.5%	20.6%
24	Naas Cunningham	F	Fr	6'7"	21-0	13.4	5.0	1.1	0.8	0.6	39.5%	23.4%	2.2	80.6%	24.2%
1	Ladji Dembele	F	Jr	6'8"	5-3	20.0	5.2	4.2	1.4	1.2	44.4%	28.6%	2.8	50.0%	18.2%
13	Jalen Cunningham	G	So	6'2"	6-0	3.3	0.5	0.2	0.3	0.0	30.0%	20.0%	0.8	—	14.3%
8	Mason Abittan	G	Fr	6'6"	0-0	0.0	0.0	0.0	0.0	0.0	—	—	0.0	—	—
77	Myles Che	G	Jr	6'3"	0-0	0.0	0.0	0.0	0.0	0.0	—	—	0.0	—	—
—	Xavier Brumfield	G	Fr	6'1"	0-0	0.0	0.0	0.0	0.0	0.0	—	—	0.0	—	—

Rosters come from ESPN and are still filling in; incoming transfers and freshmen may be missing.

San Francisco2025-26 numbers

#	Player	Pos	Cl	Ht	GP-GS	MPG	PPG	RPG	APG	TOV	eFG%	3P%	3PA/g	FT%	Usage
0	Ryan Beasley	G	Jr	5'11"	31-31	33.2	13.6	3.4	4.0	1.6	48.4%	32.7%	4.8	82.7%	25.3%
5	Tyrone Riley IV	G	So	6'6"	31-31	31.8	12.2	4.8	1.2	0.9	54.2%	36.8%	3.7	70.7%	22.1%
7	Vukasin Masic	G	Sr	6'5"	33-21	21.7	5.3	1.6	2.0	1.0	47.1%	29.1%	3.3	69.6%	18.0%
13	Legend Smiley	G	Fr	6'5"	33-14	21.3	8.1	1.9	0.6	0.8	59.8%	42.0%	4.0	87.5%	20.2%
35	Junjie Wang	F	Jr	6'9"	33-24	20.2	8.5	3.0	0.8	1.2	51.7%	34.2%	3.4	75.3%	25.7%
1	Mookie Cook	F	Jr	6'6"	25-5	20.8	7.6	4.2	1.5	1.7	52.4%	39.7%	2.3	71.4%	24.4%
14	Veniamin Abosi	G	So	6'6"	24-1	17.6	5.0	4.1	1.2	1.3	52.8%	40.4%	2.2	68.3%	19.4%
10	Saba Gigiberia	C	Sr	7'2"	26-0	6.3	2.2	2.7	0.6	0.5	44.6%	0.0%	0.0	34.8%	28.8%
2	Aidan Braccia	G	Jr	6'1"	15-0	6.0	0.8	0.6	0.3	0.1	23.5%	13.3%	1.0	66.7%	14.0%
23	Weilun Zhao	G	Fr	6'0"	14-0	5.4	1.3	0.2	1.1	0.6	26.3%	0.0%	0.9	72.7%	25.0%
21	Sean Blakely Drummond	G	Fr	6'4"	5-0	2.0	0.4	0.4	0.0	0.2	33.3%	0.0%	0.4	0.0%	26.8%
12	Isa Silva	G	Sr	6'4"	0-0	0.0	0.0	0.0	0.0	0.0	—	—	0.0	—	—
3	Ndewedo Newbury	F	Sr	6'7"	0-0	0.0	0.0	0.0	0.0	0.0	—	—	0.0	—	—

Rosters come from ESPN and are still filling in; incoming transfers and freshmen may be missing.

UNLV2025-26 numbers

ESPN hasn't posted UNLV's 2026-27 roster yet — these are last season's players.

#	Player	Pos	Cl	Ht	GP-GS	MPG	PPG	RPG	APG	TOV	eFG%	3P%	3PA/g	FT%	Usage
0	Dra Gibbs-Lawhorn	G	Jr	6'1"	35-35	34.2	20.7	3.1	2.5	2.5	59.5%	41.4%	7.0	83.8%	31.7%
2	Kimani Hamilton	F	Sr	6'8"	35-35	29.3	12.8	4.9	2.3	1.6	53.1%	34.3%	2.9	72.7%	24.8%
3	Howie Fleming Jr.	G	Sr	6'5"	32-27	29.1	9.0	6.3	3.7	2.0	50.0%	31.3%	2.6	80.2%	19.5%
6	Tyrin Jones	F	Fr	6'9"	32-15	27.0	11.9	5.0	1.4	1.1	59.8%	25.0%	0.3	48.8%	23.9%
12	Issac Williamson	G	Fr	6'0"	33-15	23.1	8.6	1.8	1.2	1.5	47.9%	33.3%	3.9	67.1%	24.3%
22	Walter Brown	F	Sr	6'5"	33-14	20.3	3.8	2.8	1.1	0.9	51.9%	34.7%	1.5	57.1%	12.7%
10	Jacob Bannarbie	F	So	6'9"	30-15	16.2	5.4	4.8	1.3	1.2	52.4%	25.0%	0.1	63.0%	21.1%
34	Emmanuel Stephen	C	So	7'0"	24-13	15.5	3.5	4.2	0.3	0.8	51.4%	0.0%	0.0	42.3%	15.9%
7	Al Green	G	Sr	6'3"	29-3	12.6	4.4	1.2	0.7	0.5	49.5%	31.1%	2.1	87.5%	20.6%
24	Naas Cunningham	F	Fr	6'7"	21-0	13.4	5.0	1.1	0.8	0.6	39.5%	23.4%	2.2	80.6%	24.2%
1	Ladji Dembele	F	Jr	6'8"	5-3	20.0	5.2	4.2	1.4	1.2	44.4%	28.6%	2.8	50.0%	18.2%
13	Jalen Cunningham	G	So	6'2"	6-0	3.3	0.5	0.2	0.3	0.0	30.0%	20.0%	0.8	—	14.3%
8	Mason Abittan	G	Fr	6'6"	0-0	0.0	0.0	0.0	0.0	0.0	—	—	0.0	—	—
77	Myles Che	G	Jr	6'3"	0-0	0.0	0.0	0.0	0.0	0.0	—	—	0.0	—	—
—	Xavier Brumfield	G	Fr	6'1"	0-0	0.0	0.0	0.0	0.0	0.0	—	—	0.0	—	—

Rosters come from ESPN and are still filling in; incoming transfers and freshmen may be missing.

Trends

Last 10 games of 2025-26

UNLV

Against the spread

Season

16-18

Home

8-7

Road

8-6

Last 10

5-5

avg cover +2.5

Missed the spread in the last gameCovered 4 of 7 as an underdog

Over / under

Season

20-14

Home

11-4

Road

8-6

Last 10

5-5

avg vs total +1.8

Under 4 straightOver in 3 of 7 as an underdog

Last 10 games, newest first

Date	Opponent	Site	Result			Total		PPP for	PPP vs	Pace
Mar 22	TulsaAdjEM #46	A	L 66–77	+5.0	L−6.0	161.5	U143	100.3	117.0	65.8
Mar 17	UC IrvineAdjEM #105	A	W 75–72	+1.0	W+4.0	152.5	U147	101.3	97.3	74.0
Mar 12	Utah StateAdjEM #24	N	L 60–80	+8.5	L−11.5	156.5	U140	86.0	114.6	69.8
Mar 11	WyomingAdjEM #98	N	W 73–70	−3.5	L−0.5	153.0	U143	111.3	106.7	65.6
Mar 6	San Diego StAdjEM #53	A	L 86–89	+9.0	W+6.0	153.5	O175	116.6	120.7	73.7
Mar 3	Utah StateAdjEM #24	H	W 92–65	+7.5	W+34.5	156.5	O157	130.9	92.5	70.3
Feb 28	NevadaAdjEM #71	H	W 85–83 OT	+1.0	W+3.0	151.5	O168	112.7	110.0	75.4
Feb 25	Grand CanyonAdjEM #65	A	L 67–80	+7.5	L−5.5	150.5	U147	96.4	115.1	69.5
Feb 21	Air ForceAdjEM #360	A	W 91–66	−16.5	W+8.5	153.0	O157	132.0	95.7	69.0
Feb 18	Colorado StAdjEM #88	H	L 86–91	−2.5	L−7.5	148.0	O177	131.5	139.2	65.4

San Francisco

Against the spread

Season

14-18

Home

5-10

Road

6-5

Last 10

4-6

avg cover −5.7

Missed the spread in the last gameCovered 3 of 6 as a favoriteCovered 1 of 4 as an underdog

Over / under

Season

18-14

Home

9-6

Road

5-6

Last 10

7-3

avg vs total +6.7

Over 2 straightOver in 6 of 6 as a favoriteOver in 1 of 4 as an underdog

Last 10 games, newest first

Date	Opponent	Site	Result			Total		PPP for	PPP vs	Pace
Mar 8	Oregon StAdjEM #219	N	L 77–78	−3.5	L−4.5	145.5	O155	116.6	118.1	66.0
Mar 7	PortlandAdjEM #259	N	W 82–65	−7.0	W+10.0	144.5	O147	122.3	97.0	67.0
Feb 28	PacificAdjEM #126	A	W 72–61	+4.5	W+15.5	143.5	U133	111.7	94.6	64.5
Feb 21	Santa ClaraAdjEM #33	H	L 73–94	+6.5	L−14.5	159.0	O167	97.8	125.9	74.7
Feb 18	#11GonzagaAdjEM #8	H	L 59–80	+15.5	L−5.5	151.0	U139	87.9	119.2	67.1
Feb 15	San DiegoAdjEM #269	A	W 92–79	−5.0	W+8.0	148.0	O171	133.2	114.3	69.1
Feb 12	Oregon StAdjEM #219	H	L 63–90	−9.0	L−36.0	141.0	O153	103.8	148.3	60.7
Feb 7	Saint Mary'sAdjEM #23	A	L 54–79	+11.5	L−13.5	143.0	U133	84.1	123.1	64.2
Feb 4	LMUAdjEM #183	H	L 75–84	−8.0	L−17.0	146.0	O159	108.8	121.8	69.0
Jan 31	PacificAdjEM #126	H	W 87–82	−4.0	W+1.0	138.0	O169	128.4	121.1	67.7

Records vs the closing line describe the past; ten games is a small sample.

Tale of the tape

national rank toned left for away, right for home

UNLVSan Francisco

Efficiency

111.3

110.5

108.8

109.2

69.9

67.4

—

Shooting

53.6%

51.2%

54.0%

50.7%

35.2%

34.6%

67.7%

70.9%

40.7%

40.1%

Ball control & glass

17.1%

15.8%

17.4%

14.1%

30.2%

31.3%

32.0%

29.0%

9.2%

7.8%

8.7%

Style

36.4%

46.1%

46.9%

36.9%

13.8%

10.1%

51.3%

55.6%

29.1%

34.2%

Roster

2.76

2.61

6'5.4"

6'4.8"

—

81.0%

Offseason

roster movement into this season — descriptive, not a model input

UNLV

Returning minutes: 100.0%Returning production: 100.0%

ESPN hasn't posted UNLV's roster for this season yet — no movement to show.

Returns 100% of last season's minutes. Teams returning at least 65% of last season's minutes have historically gained about 2.2 points of AdjEM (n=156 team-seasons, 2022-2026). (ESPN hasn't posted this season's roster yet -- this may still be last season's list.)

San Francisco

Returning minutes: 81.0%Returning production: 76.4%

Lost

David Fuchs 21.1 mpg, 11.2 ppg · transferred to Clemson
Guillermo Diaz Graham 17.2 mpg, 5.2 ppg · not on a D1 roster yet

Added

Ndewedo Newbury no D1 minutes last season
Isa Silva no D1 minutes last season

No incoming D1 transfers are listed on ESPN's roster yet — until they are, returning shares read high.

Returns 81% of last season's minutes; lost 1 of its top 5 (1 transferred). Teams returning at least 65% of last season's minutes have historically gained about 2.2 points of AdjEM (n=156 team-seasons, 2022-2026).

Head-to-head

this season and last

No meetings the last two seasons.

The CBB Matchups tab lays out the day's Division I slate: matchup, tip time, records and rank, and — once posted — Pinnacle's spread and total (the median across books when Pinnacle has no line). 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, built bottom-up from those same numbers: expected possessions times each side's opponent-adjusted points per possession, plus home court.

What these numbers mean: line shopping.