Algosys College Basketball

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Hofstra

CAA · 2025–26 · Raw net rank 57 · Raw net 9.3 · Tempo 65.4 · 33 Division I games · Through 2026-03-20

All seasons
Record
22–11
22 wins
AdjNet
8.7β
rank 76 of 365
AdjO
112.9β
rank 81 of 365
AdjD
104.3β
rank 80 of 365
AdjT
66.0β
SOS
0.8β
rank 134 of 363
NCSOS
3.3β
WAB
-3.4β
rank 82 of 363
RR
-0.8β
Exp. W
22.8β

Scouting Report

CategoryOffenseDefenseD-I Average
Efficiency
Efficiency / 100 poss.112.986103.669108.5
Four Factors
Effective FG%51.417946.31451.4
TO / 100 poss.16.114914.929116.7
Offensive rebound %34.75331.020330.6
FTA / FGA %31.626435.118135.0
Shooting
3P%37.12532.37933.9
2P%48.130544.7551.7
FT%75.85771.713772.5
Style
3PA / FGA %42.841.139.5
Assists / FGM %48.355.052.6
Blocks / opp. 2PA %10.410.79.5
Point Distribution
3-pointers %37.733.831.4
2-pointers %43.444.848.8
Free throws %18.921.419.8

Best · Median · Worst · Mark: further right is a better national rank, of 365 teams.

Rotation Depth

Effective Rotation Size
7.6
Top Three Share of Minutes
52%
Bench Share of Minutes
27%
Players with Logged Minutes
12

Bench: players outside the top five in minutes. Definitions

Schedule and Results

DateOpponentResultPoss.SiteRecord
11-03UCFL 78–8272.8Away0–1
11-07IonaL 73–8174.7Away0–2
11-14BucknellW 83–7774.6Away1–2
11-19TempleL 76–8169.4Away1–3
11-28La SalleW 63–5866.5Neutral2–3
11-29MerrimackW 78–5867.1Neutral3–3
11-30PennW 77–6066.8Away4–3
12-03ColumbiaL 70–7266.0Away4–4
12-07PittsburghW 80–7361.5Away5–4
12-13SyracuseW 70–6958.2Away6–4
12-21QuinnipiacW 74–6667.2Home7–4
12-29CampbellW 86–7266.2Home8–4
01-03DrexelW 70–6759.3Away9–4
01-08TowsonW 78–6767.0Away10–4
01-10MonmouthW 67–64 1OT71.3Home11–4
01-15Stony BrookL 71–7659.2Away11–5
01-17ElonL 85–8966.4Home11–6
01-22N.C. A&TL 78–7966.1Away11–7
01-24William & MaryL 82–8967.2Away11–8
01-29Col. of CharlestonL 64–6668.4Home11–9
01-31MonmouthW 73–5765.0Away12–9
02-05NortheasternW 80–6366.4Home13–9
02-07TowsonW 71–4961.8Home14–9
02-12Col. of CharlestonW 66–6270.2Away15–9
02-14UNCWL 66–7061.0Away15–10
02-19HamptonW 79–4361.0Home16–10
02-21NortheasternW 82–6864.1Away17–10
02-28Stony BrookW 67–5869.2Home18–10
03-03DrexelW 62–5156.7Home19–10
03-08William & MaryW 92–6165.7Neutral20–10
03-09TowsonW 68–65 1OT60.9Neutral21–10
03-10MonmouthW 75–6966.4Neutral22–10
03-20AlabamaL 70–9069.7—22–11

Roster · 12 players

Player logs in 33 of 33 team games

MinutesPer 40 MinutesShootingLast Five Team Games
PlayerGMPGTeam Min%PtsRebAstStlBlkTOPF2P2P%3P3P%FTFT%eFG%TS%FTA/FGAGMPGMin%Pts/G
Cruz Davis3337:5193.9%21.23.74.91.10.42.72.6147–32745.0%77–19140.3%138–16583.6%50.7%56.1%31.9%536:03 −1:4987.9%16.4 −3.7
Preston Edmead3334:3285.7%19.14.25.00.50.02.62.968–16441.5%92–23738.8%131–15783.4%51.4%57.8%39.2%538:56 +4:2494.9%20.8 +4.3
German Plotnikov3132:5676.8%11.44.10.91.10.81.02.342–8549.4%56–14538.6%40–4785.1%54.8%58.2%20.4%530:30 −2:2674.4%10.8 +1.4
Joshua DeCady3124:2256.8%10.45.71.01.20.51.24.152–10947.7%16–5529.1%44–7657.9%46.3%49.6%46.3%525:51 +1:2963.0%4.4 −1.9
Silas Sunday3320:2150.5%10.213.81.40.52.22.54.275–11565.2%0–10.0%†22–3562.9%64.7%65.4%30.2%526:10 +5:4963.8%4.8 −0.4
Biggie Patterson2921:0746.0%17.510.10.71.20.21.63.664–13746.7%30–10229.4%50–6774.6%45.6%49.9%28.0%520:33 −0:3450.1%9.6 +0.4
Victory Onuetu3317:4043.8%10.215.20.91.02.32.37.363–11256.3%0–0—23–4551.1%56.3%56.5%40.2%512:20 −5:2030.1%2.8 −1.7
Joshua Aaron Reaves239:1616.0%9.07.50.20.90.20.42.32–825.0%†13–3834.2%†5–683.3%†46.7%†49.3%†13.0%†510:36 +1:2025.9%3.0 +0.9
Jaeden Roberts217:4212.2%18.52.73.71.20.51.23.211–2055.0%†16–3941.0%†5–862.5%†59.3%†60.0%†13.6%†22:11 −5:312.1%0.0 −3.6
A.J. Wills169:2711.4%10.61.31.91.10.01.32.66–2227.3%†8–2236.4%†4–4100.0%†40.9%†43.7%†9.1%†23:01 −6:262.9%2.0 −0.5
Alex Tsynkevich143:393.8%6.310.90.80.80.80.84.73–837.5%†0–0—2–2100.0%†37.5%†45.0%†25.0%†22:17 −1:222.2%0.0 −0.6
Amir Williams11:390.1%0.024.20.00.00.00.024.20–0—0–0—0–0————————
Team, games with logs · per 40 team minutes33 games73.837.912.23.510.6533–110748.1%308–83037.1%464–61275.8%51.4%55.6%31.6%
Sum of players73.833.812.24.83.59.617.3Shooting residuals: see Player Lines Against Team Totals.
Residual: team minus players0.0+4.10.00.0+1.0

G: logged games. Team Min%: share of team minutes on court (40 per game plus overtime). 2P, 3P and FT show made–attempted. † Few attempts: under 100 FGA, 50 3PA or 25 FTA. Few G: under 10 games. <100 min: under 100 minutes. Last Five Team Games columns show change from the season value and hide on narrow screens.

Speculative Compensation · 2025–26β

Estimated share of the school's revenue-sharing budget for men's basketball. Not observed pay.

Team Pool
$280K
80% Range $105K to $740K
Tier
Low and other
low evidence
Team Pool, Scenarios Z1 to Z4
$265K to $320K
Scenario medians
Players with Figures
12
2 floor only

The widest scenario range, $115K to $850K, is wider than the 80% Range above (soft check S5). Methodology

Players in possession-share order
PlayerPoss. ShareSpeculative Best Guess80% RangeRange GraphicMedian % of Team PoolScenarios Z1 to Z4Floor PartEvidence and Flags
Cruz Davis96.4%$50K$17K to $135K18.5%$47K to $56K$2KSufficient evidenceRange driven by assumption, not data
Preston Edmead86.1%$72K$24K to $205K23.8%$67K to $81K$2KSufficient evidenceRange driven by assumption, not data
German Plotnikov80.3%$35K$10K to $105K13.7%$32K to $39K$2KSufficient evidenceRange driven by assumption, not data
Joshua DeCady56.3%$21K$5K to $65K8.8%$19K to $23K$2KSufficient evidenceRange driven by assumption, not data
Silas Sunday49.2%$33K$11K to $95K11.5%$31K to $38K$2KSufficient evidenceRange driven by assumption, not data
Victory Onuetu45.6%$21K$6K to $63K8.2%$19K to $23K$2KSufficient evidenceRange driven by assumption, not data
Biggie Patterson45.6%$14K$3K to $45K6.1%$13K to $16K$2KSufficient evidenceRange driven by assumption, not data
Joshua Aaron Reaves15.4%$8K$2K to $22K3.0%$7K to $9K$2KSufficient evidenceRange driven by assumption, not data
A.J. Wills11.0%$4K$1K to $12K1.4%$3K to $4K$2KLimited evidenceRange driven by assumption, not data
Jaeden Roberts10.2%$6K$2K to $16K2.2%$5K to $6K$2KLimited evidenceRange driven by assumption, not data
Alex Tsynkevich3.9%$2K$1K to $6K0.8%$2K to $3K$2KFloor only: below 300 possessions, no value estimateRange driven by assumption, not data
Amir Williams0.1%$2K$1K to $6K0.8%$2K to $3K$2KFloor only: below 300 possessions, no value estimateRange driven by assumption, not data
Team Pool—$280K$105K to $740K100%$265K to $320K—

What-If Calculator · Speculativeβ

Re-runs the 4,000 joint draws with your inputs. The address saves your inputs.

School Finances · School-Reported (EADA)

Self-reported to the U.S. Department of Education. Expenses cover coaching, travel, aid and operations, not player pay.

School-reported finances, 2024-25, Hofstra University (NCAA Division I without football)
MeasureSchool-Reported AmountNote
Men's basketball revenue$4,334,986Equals expenses (budget identity)
Men's basketball expenses$4,334,986
Athletics department expenses$30,183,708
Athletics department revenue$30,183,708

Team Totalsβ

Season per 40 minutes, 33 games, 2,174 possessions. Observed box-score sums, unadjusted. Per 40 uses 1330 game minutes, 5 per overtime period. Definitions

StatisticTeamOpponents
Points73.867.7
Field goals made25.322.8
Field goals attempted58.357.5
3-pointers made9.37.6
3-pointers attempted25.023.6
Free throws made14.014.5
Free throws attempted18.420.2
Offensive rebounds12.111.6
Defensive rebounds25.822.8
Total rebounds37.934.3
Assists12.212.5
Blocks3.53.6
Turnovers10.69.8
StealsNo team figure. Players sum to 159.
Personal foulsNo team figure. Players sum to 576.
Minutes (derived)200.0

33 of 33 games have player logs. Residual is team total minus sum of players. Team rebounds and team turnovers have no player owner, so a residual is expected. Definitions

StatisticStatusTeam Total, Logged GamesSum of PlayersResidualToleranceTeam Total, Games Without Logs
PointsReconciled2,4542,4540±12.30
Field goals madeReconciled8418410±4.20
Field goals attemptedReconciled1,9371,9370±9.70
3-pointers madeReconciled3083080±2.00
3-pointers attemptedReconciled8308300±4.20
Free throws madeReconciled4644640±2.30
Free throws attemptedReconciled6126120±3.10
Offensive reboundsNo player split
Defensive reboundsNo player split
Total reboundsResidual shown1,2611,125+136±100.90
AssistsReconciled4064060±2.00
BlocksReconciled1171170±2.00
TurnoversResidual shown351318+33±10.50
StealsNo team figure159
Personal foulsNo team figure576
Minutes (derived)Reconciled6,6506,611+39.1±133.00

Model-Implied Player Valueβ

Ranges are the 10th to 90th percentile of whole-game resampling draws. They are not calibrated intervals.

Open circle: limited evidence. Filled circle: sufficient evidence. Line: zero. No graphic: insufficient evidence.

Net points per 100 possessions, in possession-share order.
PlayerPoss. ShareNet and RangeβRange Graphic
Cruz Davis96.4%+2.1range +1.2 to +3.0Sufficient evidence
Preston Edmead86.1%+3.7range +2.8 to +4.5Sufficient evidence
German Plotnikov80.3%+1.6range +0.5 to +2.9Sufficient evidence
Joshua DeCady56.3%+1.0range -0.3 to +2.5Sufficient evidence
Silas Sunday49.2%+2.9range +1.4 to +4.2Sufficient evidence
Victory Onuetu45.6%+1.5range +0.4 to +2.7Sufficient evidence
Biggie Patterson45.6%+0.5range -0.8 to +1.7Sufficient evidence
Joshua Aaron Reaves15.4%+1.2range +0.4 to +2.0Sufficient evidence
A.J. Wills11.0%-1.1range -2.1 to -0.2Limited evidence
Jaeden Roberts10.2%+1.0range +0.2 to +1.8Limited evidence
Alex Tsynkevich3.9%Fewer than 300 on-court possessions; no value is estimated. Insufficient evidence
Amir Williams0.1%Fewer than 300 on-court possessions; no value is estimated. Insufficient evidence

Team Aggregate of Player Values, 2026β

Summary of the player values below. Split role: descriptive: not used in fit or gates. Model nil-value-v3. Definitions · NIL Methodology

Average value over five on-court slots, net points per 100 possessions
+11.3range +10.5 to +12.2Sufficient evidence

200 joint draws. The range is the 10th to 90th percentile. Player ranges cannot be added.

10 valued players hold 99.2% of on-court time. 2 without a value (under 300 possessions) hold 0.8%, counted at replacement level -9.5. Limited-evidence players hold 4.2%.

NIL Methodology · Scheduling and Model-Implied Value