A relative strength
Turnovers forced
19.0% · rank 67 of 366 · 33 games
Which defensive actions produce takeaways, and what shots do they concede?
← Program librarySource edition Sep 12, 2026
The program dossier / men’s basketball
San Diego
2025–26 performance, personnel and game context.
A starting point for 2026–27 preparation.
Independent preseason modelNo.263
-7.4 adjusted net
per 100 estimated possessions
12–212025–26 recorded finals
103.8Adjusted offense · 2026–27 baseline
111.2Adjusted defense · lower is better
70.0Model tempo · possessions / 40 min
Publisher lens / exact source team ID
A second read on San Diego.
Checking the attributed publisher rating…
01 / Both ends of the floor
The possession profile.
12–2133 recorded games · 33 paired efficiency samples · pace 69.3Mean opponent adj. net 2.0 · 31 rated opponents
Offense
Effective FG%
52.1%33 games · higher is betterRank 169 / 366 · 54th favorable percentileDefense
Opponent effective FG%
53.8%33 games · lower is betterRank 316 / 366 · 14th favorable percentileOffense
Turnover rate
17.8%33 games · lower is betterRank 273 / 366 · 25th favorable percentileDefense
Turnovers forced
19.0%33 games · higher is betterRank 67 / 366 · 82th favorable percentileOffense
Offensive rebound rate
29.1%33 games · higher is betterRank 253 / 366 · 31th favorable percentileDefense
Opponent offensive rebound rate
33.7%33 games · lower is betterRank 328 / 366 · 10th favorable percentileOffense
Free-throw attempt rate
25.7%33 games · higher is betterRank 359 / 366 · 2th favorable percentileDefense
Opponent free-throw attempt rate
37.2%33 games · lower is betterRank 259 / 366 · 29th favorable percentileShooting and ball-movement detail
| Metric | Observed rate | Games | Definition |
|---|---|---|---|
| Offensive efficiency | 106.2 | 33 | Points per 100 estimated possessions. |
| Defensive efficiency | 111.1 | 33 | Opponent points per 100 estimated possessions. |
| Two-point FG% | 51.4% | 33 | (FGM − 3PM) / (FGA − 3PA). |
| Opponent two-point FG% | 57.7% | 33 | Opponent (FGM − 3PM) / (FGA − 3PA). |
| Three-point FG% | 35.3% | 33 | 3PM / 3PA. |
| Opponent three-point FG% | 32.0% | 33 | Opponent 3PM / 3PA. |
| Three-point attempt share | 43.1% | 33 | 3PA / FGA; a style measure, not a quality grade. |
| Opponent three-point attempt share | 40.0% | 33 | Opponent 3PA / FGA; a style measure. |
| Free-throw accuracy | 75.6% | 33 | FTM / FTA. |
| Opponent free-throw accuracy | 73.4% | 33 | Opponent FTM / FTA; not attributed to defensive skill. |
| Assisted field-goal share | 60.0% | 33 | Assists / FGM; describes recorded ball movement. |
| Opponent assisted FG share | 57.1% | 33 | Opponent assists / FGM. |
Window changes describe the historical sample; they do not refit the preseason model. Full-season ranks require 10 games. Percentiles compare qualifying programs in the model’s rated field. Source coverage can differ by metric.
NCAA source context / 2025–26
What did the possessions look like?
2,303 source possession rows across 33 recorded team-games. These are descriptive NCAA source aggregates: they do not assign individual credit or enter the forecast.
02 / The film queue
Turn a number into a question.
A relative strength
Effective FG%
52.1% · rank 169 of 366 · 33 games
Which actions create the team's efficient looks, and which personnel can reproduce them?
A closer look
Opponent offensive rebound rate
33.7% · rank 328 of 366 · 33 games
Which matchups demand an extra box-out assignment?
A closer look
Free-throw attempt rate
25.7% · rank 359 of 366 · 33 games
Who generates contact, and how do opponents keep them off the line?
These are stat-led film prompts, not verified explanations of a scheme. Lower-ranked factors can still be above average. A five-point-or-closer final occurred 9 times in the selected window; San Diego won 5. That small-sample record is not a clutch-skill estimate.
03 / How the season moved
Read beyond the average.
● Offense● Opponent offenseRaw points / 100 possessions · game order
Mar 7, 2026 · neutral vs Seattle U · L 56–58 · offense 91.6 / defense 94.9
Higher offense and lower opponent offense are better. Opponent strength and venue are not adjusted here. Missing paired boxes create gaps.
Open the game-by-game scouting log · 33 games
| Game / venue | Result | Current opponent rank | Off. eff. | Def. eff. | Pace | eFG% | TO% | ORB% |
|---|---|---|---|---|---|---|---|---|
| Seattle UMar 7, 2026 · neutral | L 56–58 | 120 | 91.6 | 94.9 | 61.1 | 47.9 | 22.9 | 28.1 |
| LMUMar 6, 2026 · neutral | W 66–62 | 160 | 107.6 | 101.1 | 61.3 | 45.5 | 16.3 | 37.5 |
| PortlandFeb 28, 2026 · road | L 74–87 | 258 | 107.0 | 125.8 | 69.2 | 61.6 | 21.7 | 15.4 |
| Oregon StFeb 26, 2026 · road | L 82–92 | 139 | 110.3 | 123.8 | 66.1 | 57.4 | 13.5 | 20.0 |
| LMUFeb 21, 2026 · home | L 65–77 | 160 | 104.7 | 124.0 | 62.1 | 50.9 | 16.1 | 29.4 |
| San FranciscoFeb 15, 2026 · home | L 79–92 | 89 | 114.3 | 133.2 | 69.1 | 55.2 | 13.0 | 22.6 |
| PortlandFeb 12, 2026 · home | W 71–58 | 258 | 111.4 | 91.0 | 63.7 | 55.9 | 20.4 | 34.3 |
| LMUFeb 8, 2026 · road | L 63–83 | 160 | 99.8 | 131.5 | 63.1 | 47.4 | 12.7 | 23.5 |
| Saint Mary'sFeb 5, 2026 · road | L 60–87 | 18 | 94.0 | 136.3 | 63.8 | 48.2 | 17.2 | 26.3 |
| Oregon StJan 31, 2026 · home | L 76–78 | 139 | 93.0 | 95.4 | 72.7 | 50.0 | 24.5 | 30.0 |
| PepperdineJan 29, 2026 · road | W 92–88 | 261 | 114.5 | 109.6 | 71.4 | 49.3 | 14.9 | 36.6 |
| Santa ClaraJan 25, 2026 · home | L 73–85 | 42 | 97.9 | 114.0 | 74.6 | 41.5 | 16.1 | 35.4 |
| Washington StJan 22, 2026 · home | W 96–92 | 117 | 137.1 | 131.4 | 70.0 | 62.7 | 8.6 | 42.9 |
| BethesdaJan 17, 2026 · home | W 113–67 | Unrated | 140.8 | 83.5 | 80.2 | 66.2 | 22.4 | 57.1 |
| Seattle UJan 16, 2026 · road | L 64–75 | 120 | 88.6 | 103.8 | 72.3 | 44.2 | 22.1 | 27.0 |
| PacificJan 11, 2026 · road | L 70–77 | 207 | 100.1 | 110.1 | 69.9 | 47.5 | 17.2 | 23.7 |
| PepperdineJan 9, 2026 · home | W 83–63 | 261 | 123.4 | 93.7 | 67.2 | 63.6 | 16.4 | 32.0 |
| Santa ClaraJan 5, 2026 · road | L 70–98 | 42 | 94.0 | 131.6 | 74.5 | 50.8 | 21.5 | 18.9 |
| San FranciscoJan 3, 2026 · road | L 64–74 | 89 | 89.7 | 103.7 | 71.4 | 46.6 | 14.0 | 9.1 |
| GonzagaDec 31, 2025 · home | L 93–99 | 8 | 116.7 | 124.3 | 79.7 | 61.9 | 13.8 | 17.1 |
| PacificDec 28, 2025 · home | W 66–54 | 207 | 103.0 | 84.3 | 64.1 | 48.0 | 12.5 | 18.8 |
| WashingtonDec 23, 2025 · road | L 56–86 | 66 | 75.7 | 116.2 | 74.0 | 43.9 | 24.3 | 17.5 |
| UC San DiegoDec 20, 2025 · road | W 82–80 | 97 | 121.6 | 118.7 | 67.4 | 53.7 | 14.8 | 39.5 |
| N ArizonaDec 13, 2025 · home | W 78–69 | 308 | 117.2 | 103.7 | 66.5 | 60.0 | 21.0 | 32.1 |
| USCDec 10, 2025 · home | L 81–94 | 72 | 103.2 | 119.7 | 78.5 | 46.2 | 17.8 | 30.2 |
| San José StDec 6, 2025 · road | L 69–86 | 226 | 94.6 | 117.9 | 73.0 | 39.4 | 15.1 | 38.8 |
| Long Beach StNov 30, 2025 · road | L 72–76 | 265 | 114.2 | 120.6 | 63.0 | 57.9 | 23.8 | 46.2 |
| CA BaptistNov 25, 2025 · neutral | L 61–76 | 131 | 86.2 | 107.4 | 70.7 | 49.1 | 17.0 | 3.1 |
| UC RiversideNov 22, 2025 · home | L 71–85 | 241 | 104.5 | 125.1 | 68.0 | 46.7 | 16.2 | 36.1 |
| GramblingNov 19, 2025 · home | W 78–68 | 307 | 105.5 | 91.9 | 74.0 | 44.3 | 21.6 | 30.3 |
| IdahoNov 13, 2025 · home | W 78–74 | 214 | 116.3 | 110.4 | 67.1 | 63.4 | 19.4 | 27.6 |
| Idaho StNov 8, 2025 · home | L 68–71 | 239 | 107.4 | 112.1 | 63.3 | 49.2 | 15.8 | 34.3 |
| OccidentalNov 5, 2025 · home | W 88–59 | Unrated | 118.0 | 79.1 | 74.6 | 60.7 | 21.5 | 39.4 |
04 / The people behind the possessions
Personnel and workload.
2025–26 recorded affiliations, independent of the split selector. This is not a confirmed 2026–27 roster. Inspect roster observations →
| Player | GP | MIN/G | PTS/G | REB/G | AST/G | TS% | Est. usage | Usage games | AST/TO | 3PA |
|---|---|---|---|---|---|---|---|---|---|---|
| Toneari LaneG | 33 | 26.8 | 11.3 | 2.0 | 0.7 | 60.2 | 19.0% | 33 | 1.0933 games | 19333 games |
| Adrian McIntyreG | 32 | 24.8 | 9.8 | 3.6 | 2.9 | 59.6 | 20.4% | 32 | 1.9032 games | 7832 games |
| Juanse GorositoG | 32 | 24.3 | 10.5 | 2.7 | 2.2 | 54.6 | 22.9% | 32 | 1.6432 games | 17832 games |
| Vuk BoskovicF | 33 | 20.3 | 6.1 | 3.2 | 2.0 | 56.6 | 17.6% | 33 | 1.2433 games | 10933 games |
| Ty-Laur JohnsonG | 23 | 28.0 | 14.6 | 2.7 | 4.3 | 52.7 | 29.6% | 23 | 1.4923 games | 8123 games |
| Assane DiopF | 29 | 18.9 | 5.7 | 5.2 | 1.3 | 56.9 | 16.8% | 29 | 1.0529 games | 4329 games |
| Dominique FordG | 31 | 17.3 | 5.6 | 2.2 | 0.8 | 50.0 | 18.4% | 31 | 1.2431 games | 4831 games |
| Tim Moore Jr.F | 31 | 14.9 | 6.6 | 2.4 | 0.3 | 54.8 | 21.7% | 31 | 0.5631 games | 5531 games |
| Gavin RippF | 26 | 17.0 | 4.1 | 2.5 | 1.5 | 52.5 | 14.7% | 26 | 1.5426 games | 1726 games |
| Alejandro AvilesF | 24 | 10.8 | 2.6 | 1.7 | 0.8 | 44.9 | 15.8% | 24 | 1.5424 games | 224 games |
| D'Arrae GoodwinF | 14 | 14.6 | 4.7 | 2.5 | 0.8 | 54.7 | 17.4% | 14 | 1.0014 games | 3614 games |
Usage is a minutes-based estimate over the stated sample, not a direct measure of on-court possessions. Low-minute estimates are noisy. AST/TO is unavailable when recorded turnovers are zero; missing fields are never filled with zero.
05 / Recruiting evidence
What changed around San Diego?
This panel keeps dated school publications, source-listed roster observations and prior college production in separate evidence lanes. A source record does not establish eligibility, availability or a future role.
20Source-listed players
18Same-program prior records
0Different-program records
100%Prior minutes represented
Role workload watch
Which source-listed role is represented?
Prior minutes are grouped by the source-reported position on the current listing. “Unrepresented” means prior minutes not attached to a same-program listing in this release; it does not establish a departure, transfer, eligibility or expected role.
| Role | Listed | Prior minutes | Returning minutes | Incoming prior minutes | Returning share | Unrepresented |
|---|---|---|---|---|---|---|
| Guard | 13 | 3,993 | 3,993 | — | 100% | — |
| Forward | 6 | 2,584 | 2,584 | — | 100% | — |
| Center | 1 | 97 | 97 | — | 100% | — |
0 listed players have no recognized source position. The workload denominator is the matched prior-production sample (6,674 minutes).
No dated school announcement is in the selected review file for this program. The roster row below is observation-only; absence of a reviewed announcement does not mean the program made no move.
No announced additions are in the reviewed file for this program.
Roster observation
Who is listed in the source release?
20 source-listed players. Prior rates below are attached by exact source ID where available; missing values remain missing.
| Player | Observation | Prior MPG | Prior PPG | Prior TS% |
|---|---|---|---|---|
| Toneari Lane →G | Same programSan Diego Toreros | 26.8 | 11.3 | 60.2% |
| Adrian McIntyre →G | Same programSan Diego Toreros | 24.8 | 9.8 | 59.6% |
| Juanse Gorosito →G | Same programSan Diego Toreros | 24.3 | 10.5 | 54.6% |
| Vuk Boskovic →F | Same programSan Diego Toreros | 20.3 | 6.1 | 56.6% |
| Ty-Laur Johnson →G | Same programSan Diego Toreros | 28.0 | 14.6 | 52.7% |
| Assane Diop →F | Same programSan Diego Toreros | 18.9 | 5.7 | 56.9% |
| Dominique Ford →G | Same programSan Diego Toreros | 17.3 | 5.6 | 50.0% |
| Tim Moore Jr. →F | Same programSan Diego Toreros | 14.9 | 6.6 | 54.8% |
| Gavin Ripp →F | Same programSan Diego Toreros | 17.0 | 4.1 | 52.5% |
| Alejandro Aviles →F | Same programSan Diego Toreros | 10.8 | 2.6 | 44.9% |
| D'Arrae Goodwin →F | Same programSan Diego Toreros | 14.6 | 4.7 | 54.7% |
| Emmanuel Callas →G | Same programSan Diego Toreros | 9.1 | 0.8 | 45.2% |
Showing the 12 highest prior-minute records. Open the full roster board for every source-listed player.
Recruiting review edition Sep 8, 2026 · coverage is partial (14 programs reviewed). See the full methodology and coverage map before drawing a roster conclusion.
Look ahead / 2026–27
The next assignments.
Checking the live schedule edition…
San Diego vs Colorado
69.0San Diego
85.2Colorado
Colorado win estimate87.3%
Model signalStrong lean
Projected home margin16.1
Projected total154.2
80% home-margin range0.2 to 32.0
Estimated possessions70.9
Why the model tiltsfour-factor edge
Shot qualityAway 0.4 pts
Colorado attack 53.5% · San Diego defense 53.8%San Diego attack 50.1% · Colorado defense 49.9%
Ball securityHome 2.6 pts
Colorado attack 17.1% · San Diego defense 18.0%San Diego attack 18.1% · Colorado defense 16.4%
Second chancesAway 3.2 pts
Colorado attack 30.9% · San Diego defense 31.6%San Diego attack 29.2% · Colorado defense 26.7%
Free-throw pressureHome 0.1 pts
Colorado attack 36.8% · San Diego defense 41.0%San Diego attack 30.3% · Colorado defense 34.6%
CU Events Center
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Fordham vs San Diego
73.1Fordham
72.7San Diego
San Diego win estimate53.0%
Model signalToss-up
Projected home margin-0.4
Projected total145.8
80% home-margin range-16.3 to 15.5
Estimated possessions69.5
Why the model tiltsfour-factor edge
Shot qualityHome 3.9 pts
San Diego attack 50.1% · Fordham defense 50.9%Fordham attack 49.0% · San Diego defense 53.8%
Ball securityAway 1.0 pts
San Diego attack 18.1% · Fordham defense 17.3%Fordham attack 17.9% · San Diego defense 18.0%
Second chancesHome 0.6 pts
San Diego attack 29.2% · Fordham defense 28.2%Fordham attack 32.0% · San Diego defense 31.6%
Free-throw pressureHome 2.4 pts
San Diego attack 30.3% · Fordham defense 36.6%Fordham attack 32.3% · San Diego defense 41.0%
Jenny Craig Pavilion
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Read the evidence correctly.
The top-line adjusted ratings use the full published preseason model. Split statistics below them are unadjusted observations from 2025–26. Opponent ranks are the current model’s ranks, not what was known before each historical game. The “top 50” split is descriptive and does not enter model evaluation.
Rates pool numerators and denominators from games with all fields required for that metric. Missing values remain unavailable; every metric shows its game count. Ranks require at least 10 games and compare programs in the model’s rated field. Ties share rank; percentiles use their average position. High percentiles mean favorable values only for metrics with a defined direction.
Player workloads refer to recorded 2025–26 appearances. Estimated usage divides FGA + 0.475 × FTA + turnovers by minutes-prorated team opportunities in those same games. It assumes team opportunity rates were constant while a player was on court; it is not a lineup or play-by-play measurement. Overtime is included in available minutes. Minutes and usage samples can differ.
Source statistics: SportsDataverse bulk releases, CC BY 4.0. Calculations and model: Silvermine. Definitions draw on publicly documented Four Factors and basketball rate statistics; these are not another publisher’s proprietary ratings. Model notebook →