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

Montana

Efficiency #207

2025-26: 18-16 · 12-9 conf

San Francisco

Efficiency #148

2025-26: 17-16 · 9-11 conf

Tue, Nov 10 · TBD

72.0

win 31%

Projected

77.9

win 69%

No line posted yet.

Model: SF −5.9 · total 149.9 · 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, Montana 69.8 → 68.8 possessions

+1.1

San Francisco offense vs Montana defense

+1.3

Montana offense vs San Francisco defense

−0.7

Projected total

149.9

Axis starts at 147 pointsPoints added or removed at each step

Projected margin

Even game

0.0

San Francisco offense vs Montana defense

+1.3

Montana offense vs San Francisco defense

+0.7

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

+4.0

San Francisco by 5.9

5.9

Montana side ◂▸ San Francisco side

Steps are rounded to one decimal, so they can differ from the total by 0.1: the margin steps add to +6.0 against +5.9. 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: 68.8, from each team's opponent-adjusted tempo. On raw 2025-26 season pace, Montana is the faster team (71.1, #48 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

68.8

per team, 40 min

Projected total

149.9

model

Projected team totals

72.0 / 77.9

Montana / San Francisco

Adjusted tempo, vs an average opponent

69.8#67

Montana

67.4#261

San Francisco

How this game plays

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

AdvantageMontana

Where Montana struggles: the offensive glass

Montana rebounds 20.7% of its own misses (#363); San Francisco lets opponents grab 29.0% of their own misses (#105). Expect about 23.0%, 7.5 points below an average D1 matchup — worth roughly -4.5 points per 100 possessions.

AdvantageSan Francisco

Where San Francisco scores: ball control

San Francisco turns it over on 15.8% of possessions (#125); Montana forces turnovers on 14.3% of opponent possessions (#326). Expect about 14.6%, 2.1 points below an average D1 matchup — worth roughly +2.6 points per 100 possessions.

Watch for noise

3-point caution

A notable season 3-point number here (Montana) is close to a coin flip going forward — the study's model of next-game 3P% barely beats guessing the D1 average. Shot volume is what actually carries: expect Montana at about 39.0% of its shots from three, San Francisco about 43.8%.

ClashSan Francisco

Style clash: paint scoring

San Francisco gets only 36.9% of its points in the paint; Montana gives up 46.3% of opponents' points in the paint (D1 average 42.8%). Expect about 42.5% — the offense's habit usually carries a bit more weight (0.25 vs 0.34).

Montana has the ball

OffenseSan Francisco allowsvs D1 avg

55.8% #23

50.8% #143

+3.4 pt/100

19.6% #340

14.1% #330

+0.1 pt/100

20.7% #363

29.0% #105

-4.5 pt/100

36.8% #135

29.6% #51

-0.3 pt/100

77.3% #27

—

+0.4 pt/100

Montana net across the four factors + FT%, vs. a D1-average matchup: -0.9 pts/100

San Francisco has the ball

OffenseMontana allowsvs D1 avg

51.2% #184

50.5% #129

-0.6 pt/100

15.8% #125

14.3% #326

+2.6 pt/100

31.3% #148

29.6% #143

+0.2 pt/100

40.1% #59

32.6% #120

+0.1 pt/100

70.9% #242

—

-0.1 pt/100

San Francisco net across the four factors + FT%, vs. a D1-average matchup: +2.2 pts/100

Shot diet

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

Montanaoffense vsSan Franciscodefense

Share of shots by zone

Montana shoots

37.3

7.1

13.9

41.7

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	61.5%#83	59.3%#205	58.6%
Short 2 (≤9 ft)	45.3%#60	45.5%#312	39.5%
Mid 2 (10 ft+)	45.9%#8	35.0%#78	38.0%
Three	36.6%#38	34.1%#187	33.7%

San Franciscooffense vsMontanadefense

Share of shots by zone

San Francisco shoots

34.3

4.9

14.3

46.5

Montana allows

38.3

9.0

15.3

37.4

D-I average

38.5

6.4

15.8

39.3

FG% by zone

Zone			D-I avg
Rim	57.1%#229	59.9%#221	58.6%
Short 2 (≤9 ft)	41.5%#132	36.6%#103	39.5%
Mid 2 (10 ft+)	35.4%#278	38.5%#175	38.0%
Three	34.6%#140	32.3%#74	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

Montana

−5.2extra scoring chances per game vs a D-I average team#348 of 365

Off reb %

20.7%

#363

Def reb %

70.4%

#143

Turnover %

19.6%

#340

Forced TO %

14.3%

#326

FT rate

36.8%

#135

FT allowed

32.6%

#120

Where the chances come from (per game)

Offensive rebounding−3.1

Defensive rebounding+0.3

Ball security−1.9

Forcing turnovers−1.6

Foul shots drawn+0.4

Foul shots allowed+0.7

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 Montana’s −5.2 (#348).

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

Montana2025-26 numbers

#	Player	Pos	Cl	Ht	GP-GS	MPG	PPG	RPG	APG	TOV	eFG%	3P%	3PA/g	FT%	Usage
4	Tyler Thompson	G	Fr	6'6"	33-33	29.3	8.4	4.0	1.3	1.2	58.9%	40.1%	5.2	80.6%	15.5%
32	Te'Jon Sawyer	F	Sr	6'8"	34-33	27.9	11.4	5.4	1.1	1.7	63.6%	35.8%	2.8	69.6%	21.3%
24	Kenyon Aguino	F	Fr	6'7"	34-34	23.6	8.4	4.2	1.5	1.2	57.9%	30.3%	1.0	71.8%	19.2%
8	Tyler Isaak	G	Jr	6'4"	34-17	22.4	6.1	2.8	2.3	0.9	50.0%	31.0%	2.5	85.3%	15.6%
3	Brooklyn Hicks	G	Jr	6'3"	34-8	22.1	9.0	3.8	0.9	1.0	55.7%	36.8%	3.4	70.0%	22.4%
11	Grant Kepley	G	So	6'4"	28-10	21.4	6.2	2.7	2.8	1.9	46.7%	30.0%	1.8	68.1%	21.2%
1	Trae Taylor	F	Sr	6'9"	29-0	8.3	2.2	1.6	0.1	0.4	67.5%	—	0.0	44.0%	14.7%
10	Connor Dick	G	So	6'3"	23-0	10.4	2.7	1.8	0.3	0.6	45.2%	23.5%	0.7	77.4%	16.4%
2	Chase Henderson	G	So	6'0"	19-0	7.3	2.5	0.6	0.6	0.7	51.3%	33.3%	0.8	81.8%	22.4%
5	Amari Jedkins	F	Jr	6'7"	23-1	5.3	1.3	1.1	0.0	0.1	51.9%	33.3%	0.5	60.0%	14.4%
13	Courtney Anderson Jr.	G	So	6'5"	10-0	11.3	5.7	1.4	0.2	0.7	71.4%	46.7%	3.0	77.8%	22.5%
7	Kadyn Betts	F	Jr	6'8"	9-0	6.6	3.1	1.1	0.2	1.0	71.9%	62.5%	0.9	83.3%	26.7%
22	Luke Moxon	G	Fr	6'3"	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.

Montana2025-26 numbers

#	Player	Pos	Cl	Ht	GP-GS	MPG	PPG	RPG	APG	TOV	eFG%	3P%	3PA/g	FT%	Usage
4	Tyler Thompson	G	Fr	6'6"	33-33	29.3	8.4	4.0	1.3	1.2	58.9%	40.1%	5.2	80.6%	15.5%
32	Te'Jon Sawyer	F	Sr	6'8"	34-33	27.9	11.4	5.4	1.1	1.7	63.6%	35.8%	2.8	69.6%	21.3%
24	Kenyon Aguino	F	Fr	6'7"	34-34	23.6	8.4	4.2	1.5	1.2	57.9%	30.3%	1.0	71.8%	19.2%
8	Tyler Isaak	G	Jr	6'4"	34-17	22.4	6.1	2.8	2.3	0.9	50.0%	31.0%	2.5	85.3%	15.6%
3	Brooklyn Hicks	G	Jr	6'3"	34-8	22.1	9.0	3.8	0.9	1.0	55.7%	36.8%	3.4	70.0%	22.4%
11	Grant Kepley	G	So	6'4"	28-10	21.4	6.2	2.7	2.8	1.9	46.7%	30.0%	1.8	68.1%	21.2%
1	Trae Taylor	F	Sr	6'9"	29-0	8.3	2.2	1.6	0.1	0.4	67.5%	—	0.0	44.0%	14.7%
10	Connor Dick	G	So	6'3"	23-0	10.4	2.7	1.8	0.3	0.6	45.2%	23.5%	0.7	77.4%	16.4%
2	Chase Henderson	G	So	6'0"	19-0	7.3	2.5	0.6	0.6	0.7	51.3%	33.3%	0.8	81.8%	22.4%
5	Amari Jedkins	F	Jr	6'7"	23-1	5.3	1.3	1.1	0.0	0.1	51.9%	33.3%	0.5	60.0%	14.4%
13	Courtney Anderson Jr.	G	So	6'5"	10-0	11.3	5.7	1.4	0.2	0.7	71.4%	46.7%	3.0	77.8%	22.5%
7	Kadyn Betts	F	Jr	6'8"	9-0	6.6	3.1	1.1	0.2	1.0	71.9%	62.5%	0.9	83.3%	26.7%
22	Luke Moxon	G	Fr	6'3"	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

Montana

Against the spread

Season

15-14-1

Home

7-5-1

Road

6-8

Last 10

4-5-1

avg cover −3.9

Missed the spread in the last gameCovered 1 of 4 as a favorite, 1 pushCovered 3 of 6 as an underdog

Over / under

Season

15-15

Home

7-6

Road

6-8

Last 10

5-5

avg vs total +1.2

Under in the last gameOver in 1 of 4 as a favoriteOver in 4 of 6 as an underdog

Last 10 games, newest first

Date	Opponent	Site	Result			Total		PPP for	PPP vs	Pace
Mar 11	IdahoAdjEM #156	N	L 66–77	+3.5	L−7.5	146.5	U143	91.6	106.8	72.1
Mar 10	Portland StAdjEM #145	N	W 75–72	+3.5	W+6.5	145.0	O147	101.9	97.8	73.6
Mar 9	N ColoradoAdjEM #146	N	W 95–89	+4.5	W+10.5	152.5	O184	127.4	119.3	74.6
Mar 2	N ColoradoAdjEM #146	A	L 57–85	+5.5	L−22.5	155.0	U142	77.8	116.0	73.3
Feb 28	Portland StAdjEM #145	H	W 74–68	+1.0	W+7.0	140.0	O142	103.4	95.0	71.5
Feb 26	Sacramento StAdjEM #280	H	W 81–73	−8.0	P0.0	161.5	U154	112.5	101.4	72.0
Feb 21	Weber StAdjEM #203	A	L 72–92	+2.5	L−17.5	152.0	O164	106.6	136.2	67.5
Feb 19	Idaho StAdjEM #253	A	L 69–73	−1.0	L−5.0	150.0	U142	101.8	107.7	67.8
Feb 14	Montana StAdjEM #130	H	L 71–82	−2.0	L−13.0	146.0	O153	107.5	124.2	66.0
Feb 7	IdahoAdjEM #156	H	W 73–68	−2.5	W+2.5	151.0	U141	101.2	94.3	72.1

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

MontanaSan Francisco

Efficiency

106.8

110.5

108.3

109.2

69.8

67.4

—

Shooting

55.8%

51.2%

56.5%

50.7%

36.6%

34.6%

77.3%

70.9%

36.8%

40.1%

Ball control & glass

19.6%

15.8%

14.3%

14.1%

20.7%

31.3%

29.6%

29.0%

11.3%

9.2%

8.7%

Style

41.8%

46.1%

41.8%

36.9%

10.3%

10.1%

55.1%

55.6%

30.6%

34.2%

Roster

2.40

2.61

6'5.5"

6'4.8"

84.4%

81.0%

Offseason

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

Montana

Returning minutes: 84.4%Returning production: 75.9%

Lost

Money Williams 31.2 mpg, 20.6 ppg · transferred to Boston College

Added

Luke Moxon no D1 minutes last season

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

Returns 84% 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).

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.