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-conferenceBryce Jordan Center, University Park, PA
Canisius
Efficiency #344
2025-26: 10-21 · 5-15 conf
@
Penn State
Efficiency #194
2025-26: 12-20 · 3-18 conf
Mon, Nov 2 · TBD
66.3
win 17%
Projected
77.5
win 83%
No line posted yet.
Model: PSU −11.2 · total 143.9 · 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: Penn State 68.4, Canisius 66.2 → 66.3 possessions
−4.5
Penn State offense vs Canisius defense
+3.7
Canisius offense vs Penn State defense
−3.6
Projected total
143.9
Axis starts at 140 pointsPoints added or removed at each step
Projected margin
Even game
0.0
Penn State offense vs Canisius defense
+3.7
Canisius offense vs Penn State defense
+3.6
Home court+2.9 points per 100 possessions to the home offense, −2.9 to the visitors
+3.8
Penn State by 11.2
11.2
Canisius side ◂▸ Penn State side

Steps are rounded to one decimal, so they can differ from the total by 0.1: the total steps add to 143.8 against a projected 143.9, and the margin steps add to +11.1 against +11.2. The margin is the same build seen from the home side; positive numbers help Penn State.

Pace & total

possessions per 40 minutes
Tempo, possessions per 40 minutes

Projected possessions: 66.3, from each team's opponent-adjusted tempo. On raw 2025-26 season pace, Penn State is the faster team (67.5, #224 of 365) and Canisius the slower (64.3, #348). When tempos clash, the slower team usually pulls the pace harder (study weights 0.80 vs 0.66).

Projected possessions
66.3
per team, 40 min
Projected total
143.9
model
Projected team totals
66.3 / 77.5
Canisius / Penn State
Adjusted tempo, vs an average opponent
66.2#336
Canisius
68.4#175
Penn State

How this game plays

what the study found each side's numbers actually do when these two teams meet
Pace
Half-court grind
Penn State averages 67.5 possessions per 40, Canisius 64.3. Slower teams pull the pace toward themselves more than fast teams push it (0.80 vs 0.66 in five seasons of games), so expect about 65 — more possessions mean more points in the total and more chances for the better team to separate.
AdvantageCanisius
Where Canisius struggles: ball control
Canisius turns it over on 19.6% of possessions (#341); Penn State forces turnovers on 17.7% of opponent possessions (#113). Expect about 19.0%, 2.2 points above an average D1 matchup — worth roughly -2.7 points per 100 possessions.
AdvantagePenn State
Where Penn State scores: shooting
Penn State shoots an effective 53.0% (#102); Canisius allows 52.2% (#225). Expect about 52.8%, 1.5 points above an average D1 matchup — worth roughly +2.1 points per 100 possessions.
GlassPenn State
Penn State gets out-rebounded
Projected offensive rebound rate of 27.0% is worth roughly -2.1 points per 100 possessions against Penn State's offense.
Watch for noise
3-point caution
A notable season 3-point number here (Penn State's defense) 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 Canisius at about 42.0% of its shots from three, Penn State about 41.2%.
Canisius has the ball
OffensePenn State allowsvs D1 avg
46.3% #348
58.4% #363
+1.1 pt/100
19.6% #341
17.7% #113
-2.7 pt/100
29.3% #226
31.1% #210
-0.3 pt/100
31.4% #271
27.5% #28
-0.8 pt/100
71.9% #212
—
-0.0 pt/100
Canisius net across the four factors + FT%, vs. a D1-average matchup: -2.7 pts/100
Penn State has the ball
OffenseCanisius allowsvs D1 avg
53.0% #102
52.2% #225
+2.1 pt/100
15.6% #108
16.0% #222
+1.4 pt/100
25.9% #325
29.8% #151
-2.1 pt/100
33.8% #219
35.2% #184
-0.1 pt/100
75.0% #83
—
+0.2 pt/100
Penn State net across the four factors + FT%, vs. a D1-average matchup: +1.6 pts/100

Shot diet

Where each offense shoots from and where each defense lets teams shoot · 2025-26 numbers
Canisiusoffense vsPenn Statedefense
Share of shots by zone
Canisius shoots
Penn State allows
D-I average
FG% by zone
ZoneD-I avg
Rim47.2%#36567.3%#36258.6%
Short 2 (≤9 ft)50.5%#1035.2%#6339.5%
Mid 2 (10 ft+)34.6%#29843.7%#33838.0%
Three33.3%#21338.8%#36333.7%
Penn Stateoffense vsCanisiusdefense
Share of shots by zone
Penn State shoots
Canisius allows
D-I average
FG% by zone
ZoneD-I avg
Rim62.1%#6960.1%#22958.6%
Short 2 (≤9 ft)42.5%#11139.0%#15839.5%
Mid 2 (10 ft+)42.8%#4240.7%#26638.0%
Three32.4%#26333.0%#12433.7%
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
Canisius
−3.4extra scoring chances per game vs a D-I average team#313 of 365
Off reb %
29.3%
#226
Def reb %
70.2%
#151
Turnover %
19.6%
#341
Forced TO %
16.0%
#222
FT rate
31.4%
#271
FT allowed
35.2%
#184
Where the chances come from (per game)
Offensive rebounding−0.4
Defensive rebounding+0.3
Ball security−1.9
Forcing turnovers−0.5
Foul shots drawn−0.9
Foul shots allowed0.0
Penn State
+1.5extra scoring chances per game vs a D-I average team#118 of 365
Off reb %
25.9%
#325
Def reb %
68.9%
#210
Turnover %
15.6%
#108
Forced TO %
17.7%
#113
FT rate
33.8%
#219
FT allowed
27.5%
#28
Where the chances come from (per game)
Offensive rebounding−1.4
Defensive rebounding−0.2
Ball security+0.8
Forcing turnovers+0.7
Foul shots drawn−0.3
Foul shots allowed+2.0

Penn State has more extra scoring chances per game: +1.5 (#118 of 365) to Canisius’s −3.4 (#313).

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

Canisius2025-26 numbers
#PlayerPosClHtGP-GSMPGPPGRPGAPGTOVeFG%3P%3PA/gFT%UsageStatus
4Preist Ryanat Cleveland StFSr6'6"31-2422.37.24.01.31.245.8%30.0%0.669.3%20.6%
1Vinny Sigonaat East Texas A&MGSr6'0"28-620.08.11.01.81.257.8%40.1%5.687.5%22.9%
5Clinton Efindaat UNC GreensboroFSr6'5"33-014.94.51.60.70.551.3%38.5%2.078.8%17.5%
33Michael Wilson Jr.at BellarmineGJr6'6"30-413.55.71.80.70.753.2%31.6%1.364.3%25.5%
2Demarris Wintersat UT Rio GrandeGSo6'3"21-07.12.40.70.50.261.8%39.3%1.360.0%17.6%
7Nate Deerat OaklandFSr6'10"9-05.11.21.60.10.355.6%—0.025.0%15.9%
12Trevor AugustineGJr6'2"8-01.80.50.10.00.350.0%33.3%0.450.0%25.1%
15Nate Foutsat Le MoyneFSr6'8"0-00.00.00.00.00.0——0.0——
10Will Fowlerat 124947GSo6'2"0-00.00.00.00.00.0——0.0——
22Abu RiakFFr6'8"0-00.00.00.00.00.0——0.0——
3Alex MackGFr6'4"0-00.00.00.00.00.0——0.0——
95Dorsett MulcahyGFr6'7"0-00.00.00.00.00.0——0.0——
14Jerry GuerreroGSo6'3"0-00.00.00.00.00.0——0.0——
13Will TaylorFSo6'9"0-00.00.00.00.00.0——0.0——
Rosters come from ESPN and are still filling in; incoming transfers and freshmen may be missing.
Transfers in: Nate Deer (from Oakland), Clinton Efinda (from UNC Greensboro), Nate Fouts (from Le Moyne), Will Fowler (from 124947), Preist Ryan (from Cleveland St), Vinny Sigona (from East Texas A&M), Michael Wilson Jr. (from Bellarmine), Demarris Winters (from UT Rio Grande)

Tale of the tape

national rank toned left for away, right for home
CanisiusPenn State
Efficiency
99.6
110.8
111.8
111.8
66.2
68.4
—
—
Shooting
46.3%
53.0%
44.0%
55.8%
33.3%
32.4%
71.9%
75.0%
31.4%
33.8%
Ball control & glass
19.6%
15.6%
16.0%
17.7%
29.3%
25.9%
29.8%
31.1%
10.5%
8.6%
9.7%
9.8%
Style
39.5%
38.1%
39.3%
46.1%
11.6%
14.8%
55.4%
48.3%
27.8%
33.2%
Roster
3.69
1.82
6'4.2"
6'7.1"
0.2%
86.3%

Offseason

roster movement into this season — descriptive, not a model input
Canisius
Returning minutes: 0.2%Returning production: -0.0%
Lost
  • Kahlil Singleton 33.7 mpg, 13.4 ppg · not on a D1 roster yet
  • Bryan Ndjonga 32.7 mpg, 13.9 ppg · not on a D1 roster yet
  • Mike Evbagharu 32.2 mpg, 8.9 ppg · not on a D1 roster yet
  • Myles Wilmoth 23.2 mpg, 5.2 ppg · not on a D1 roster yet
  • Javante Edwards 20.0 mpg, 5.7 ppg · not on a D1 roster yet
  • Chris Kumu 11.2 mpg, 3.2 ppg · not on a D1 roster yet
Added
  • Preist Ryan from Cleveland St · 20.9 mpg, 6.8 ppg last season
  • Vinny Sigona from East Texas A&M · 17.5 mpg, 7.1 ppg last season
  • Clinton Efinda from UNC Greensboro · 14.5 mpg, 4.3 ppg last season
  • Michael Wilson Jr. from Bellarmine · 12.7 mpg, 5.3 ppg last season
  • Demarris Winters from UT Rio Grande · 4.5 mpg, 1.5 ppg last season
  • Nate Deer from Oakland · 1.4 mpg, 0.3 ppg last season

Returns 0% of last season's minutes; lost 5 of its top 5. Teams returning under 40% of last season's minutes have historically fallen about 0.8 points of AdjEM (n=716 team-seasons, 2022-2026).

Penn State
Returning minutes: 86.3%Returning production: 82.2%
Lost
  • Freddie Dilione V 27.5 mpg, 14.0 ppg · transferred to Georgia
Added
  • Reggie Grodin no D1 minutes last season

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

Returns 86% 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.