A relative strength
Opponent free-throw attempt rate
33.5% · rank 156 of 366 · 30 games
Which defenders can protect the paint without surrendering free throws?
← Program librarySource edition Sep 12, 2026
The program dossier / men’s basketball
UTSA
2025–26 performance, personnel and game context.
A starting point for 2026–27 preparation.
Independent preseason modelNo.312
-11.6 adjusted net
per 100 estimated possessions
5–252025–26 recorded finals
102.1Adjusted offense · 2026–27 baseline
113.8Adjusted defense · lower is better
69.9Model tempo · possessions / 40 min
Publisher lens / exact source team ID
A second read on UTSA.
Checking the attributed publisher rating…
01 / Both ends of the floor
The possession profile.
5–2530 recorded games · 30 paired efficiency samples · pace 70.2Mean opponent adj. net 2.6 · 28 rated opponents
Offense
Effective FG%
45.9%30 games · higher is betterRank 356 / 366 · 3th favorable percentileDefense
Opponent effective FG%
52.0%30 games · lower is betterRank 247 / 366 · 33th favorable percentileOffense
Turnover rate
17.0%30 games · lower is betterRank 212 / 366 · 42th favorable percentileDefense
Turnovers forced
15.4%30 games · higher is betterRank 279 / 366 · 24th favorable percentileOffense
Offensive rebound rate
31.0%30 games · higher is betterRank 188 / 366 · 49th favorable percentileDefense
Opponent offensive rebound rate
36.9%30 games · lower is betterRank 361 / 366 · 1th favorable percentileOffense
Free-throw attempt rate
29.0%30 games · higher is betterRank 329 / 366 · 10th favorable percentileDefense
Opponent free-throw attempt rate
33.5%30 games · lower is betterRank 156 / 366 · 58th favorable percentileShooting and ball-movement detail
| Metric | Observed rate | Games | Definition |
|---|---|---|---|
| Offensive efficiency | 99.0 | 30 | Points per 100 estimated possessions. |
| Defensive efficiency | 115.0 | 30 | Opponent points per 100 estimated possessions. |
| Two-point FG% | 46.8% | 30 | (FGM − 3PM) / (FGA − 3PA). |
| Opponent two-point FG% | 53.0% | 30 | Opponent (FGM − 3PM) / (FGA − 3PA). |
| Three-point FG% | 29.7% | 30 | 3PM / 3PA. |
| Opponent three-point FG% | 33.8% | 30 | Opponent 3PM / 3PA. |
| Three-point attempt share | 40.6% | 30 | 3PA / FGA; a style measure, not a quality grade. |
| Opponent three-point attempt share | 43.5% | 30 | Opponent 3PA / FGA; a style measure. |
| Free-throw accuracy | 69.1% | 30 | FTM / FTA. |
| Opponent free-throw accuracy | 71.1% | 30 | Opponent FTM / FTA; not attributed to defensive skill. |
| Assisted field-goal share | 43.9% | 30 | Assists / FGM; describes recorded ball movement. |
| Opponent assisted FG share | 55.7% | 30 | 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?
2,116 source possession rows across 30 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
Offensive rebound rate
31.0% · rank 188 of 366 · 30 games
Who crashes the glass, and how does that affect transition defense?
A closer look
Effective FG%
45.9% · rank 356 of 366 · 30 games
Which actions create the team's efficient looks, and which personnel can reproduce them?
A closer look
Opponent offensive rebound rate
36.9% · rank 361 of 366 · 30 games
Which matchups demand an extra box-out assignment?
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 3 times in the selected window; UTSA won 1. 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 8, 2026 · road vs Rice · L 71–80 · offense 103.2 / defense 116.3
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 · 30 games
| Game / venue | Result | Current opponent rank | Off. eff. | Def. eff. | Pace | eFG% | TO% | ORB% |
|---|---|---|---|---|---|---|---|---|
| RiceMar 8, 2026 · road | L 71–80 | 224 | 103.2 | 116.3 | 68.8 | 40.7 | 7.3 | 36.2 |
| Wichita StMar 2, 2026 · home | L 67–84 | 92 | 96.1 | 120.5 | 69.7 | 37.3 | 8.6 | 29.2 |
| East CarolinaFeb 26, 2026 · home | L 81–82 | 222 | 119.9 | 121.4 | 67.6 | 66.7 | 25.2 | 34.8 |
| TulsaFeb 22, 2026 · road | L 74–100 | 116 | 103.4 | 139.8 | 71.6 | 53.3 | 15.4 | 14.7 |
| FAUFeb 19, 2026 · home | L 52–60 | 94 | 76.9 | 88.7 | 67.6 | 35.4 | 17.7 | 31.9 |
| CharlotteFeb 15, 2026 · road | W 88–79 | 181 | 133.7 | 120.0 | 65.8 | 54.7 | 4.6 | 32.3 |
| East CarolinaFeb 12, 2026 · road | L 72–88 | 222 | 101.3 | 123.9 | 71.1 | 43.8 | 14.1 | 38.0 |
| North TexasFeb 7, 2026 · home | L 58–81 | 101 | 83.2 | 116.1 | 69.7 | 43.4 | 25.8 | 27.3 |
| South FloridaFeb 5, 2026 · road | L 88–109 | 76 | 124.4 | 154.1 | 70.7 | 66.7 | 18.4 | 30.0 |
| UABJan 29, 2026 · home | L 73–83 | 106 | 103.3 | 117.5 | 70.6 | 44.7 | 12.7 | 26.2 |
| TempleJan 24, 2026 · home | L 64–70 | 142 | 102.2 | 111.8 | 62.6 | 45.3 | 17.6 | 40.5 |
| North TexasJan 22, 2026 · road | L 62–81 | 101 | 91.3 | 119.3 | 67.9 | 42.0 | 22.1 | 23.5 |
| MemphisJan 18, 2026 · road | L 69–95 | 85 | 95.3 | 131.2 | 72.4 | 48.5 | 23.5 | 35.0 |
| RiceJan 15, 2026 · home | L 73–89 | 224 | 118.5 | 144.5 | 61.6 | 50.0 | 14.6 | 42.9 |
| TulaneJan 10, 2026 · home | L 52–85 | 168 | 75.7 | 123.8 | 68.7 | 38.7 | 23.3 | 25.6 |
| CharlotteJan 8, 2026 · home | L 58–74 | 181 | 90.0 | 114.9 | 64.4 | 43.2 | 12.4 | 20.0 |
| TempleJan 3, 2026 · road | L 57–76 | 142 | 87.4 | 116.5 | 65.2 | 36.4 | 21.5 | 33.3 |
| FAUDec 31, 2025 · road | L 70–110 | 94 | 87.6 | 137.7 | 79.9 | 38.5 | 18.8 | 21.3 |
| Seattle UDec 22, 2025 · home | L 68–71 | 120 | 91.9 | 95.9 | 74.0 | 50.0 | 21.6 | 21.2 |
| USCDec 18, 2025 · road | L 70–97 | 72 | 94.5 | 130.9 | 74.1 | 40.5 | 22.9 | 42.5 |
| ColoradoDec 13, 2025 · road | L 64–88 | 69 | 88.5 | 121.7 | 72.3 | 43.8 | 22.1 | 32.6 |
| AlabamaDec 7, 2025 · road | L 55–97 | 12 | 70.9 | 125.1 | 77.6 | 39.3 | 23.2 | 19.1 |
| South AlabamaNov 30, 2025 · home | L 58–82 | 165 | 81.7 | 115.5 | 71.0 | 35.4 | 14.1 | 32.1 |
| GA SouthernNov 26, 2025 · neutral | W 77–64 | 244 | 105.0 | 87.3 | 73.3 | 43.3 | 13.6 | 34.9 |
| Abilene ChrstnNov 25, 2025 · neutral | L 50–61 | 248 | 80.7 | 98.5 | 62.0 | 39.8 | 22.6 | 26.5 |
| SW Christian UNov 18, 2025 · home | W 103–70 | Unrated | 131.3 | 89.2 | 78.5 | 59.7 | 11.5 | 42.9 |
| DenverNov 15, 2025 · road | W 84–79 | 268 | 129.1 | 121.4 | 65.1 | 61.6 | 15.4 | 36.7 |
| Texas StNov 13, 2025 · road | L 69–80 | 228 | 98.0 | 113.6 | 70.4 | 44.9 | 15.6 | 25.6 |
| SIUENov 7, 2025 · home | L 60–77 | 231 | 82.6 | 106.0 | 72.7 | 33.1 | 12.4 | 31.5 |
| Biblical StudNov 6, 2025 · home | W 97–30 | Unrated | 122.7 | 37.9 | 79.1 | 56.5 | 12.6 | 39.0 |
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 |
|---|---|---|---|---|---|---|---|---|---|---|
| Jamir SimpsonG | 30 | 34.6 | 16.2 | 4.1 | 2.4 | 49.9 | 25.3% | 30 | 1.2930 games | 17630 games |
| Dorian HayesG | 26 | 30.2 | 8.8 | 1.8 | 1.8 | 49.0 | 16.5% | 26 | 1.4126 games | 16526 games |
| Brent MossG | 29 | 26.8 | 9.6 | 4.7 | 0.9 | 46.9 | 20.3% | 29 | 0.9629 games | 15329 games |
| Baboucarr NjieF | 29 | 25.5 | 9.4 | 5.2 | 1.5 | 50.3 | 22.6% | 29 | 0.6129 games | 3129 games |
| Austin NunezG | 22 | 28.5 | 9.8 | 2.1 | 2.8 | 41.7 | 23.5% | 22 | 1.3622 games | 8722 games |
| Matheo CoffiF | 30 | 19.0 | 3.8 | 4.8 | 0.8 | 57.2 | 10.8% | 30 | 0.9330 games | 3830 games |
| Kaidon RayfieldF | 26 | 20.0 | 6.7 | 4.8 | 0.8 | 45.3 | 20.0% | 26 | 0.8326 games | 4426 games |
| Daniel AkitobyF | 24 | 13.9 | 5.7 | 4.1 | 0.2 | 60.9 | 18.4% | 24 | 0.3824 games | 1024 games |
| LJ BrownG | 17 | 12.5 | 2.4 | 1.5 | 0.6 | 43.7 | 12.7% | 17 | 1.1117 games | 3617 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 UTSA?
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.
15Source-listed players
14Same-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 | 8 | 3,657 | 3,657 | — | 100% | — |
| Forward | 5 | 2,167 | 2,167 | — | 100% | — |
| Center | 2 | 176 | 176 | — | 100% | — |
0 listed players have no recognized source position. The workload denominator is the matched prior-production sample (6,000 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?
15 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% |
|---|---|---|---|---|
| Jamir Simpson →G | Same programUTSA Roadrunners | 34.6 | 16.2 | 49.9% |
| Dorian Hayes →G | Same programUTSA Roadrunners | 30.2 | 8.8 | 49.0% |
| Brent Moss →G | Same programUTSA Roadrunners | 26.8 | 9.6 | 46.9% |
| Baboucarr Njie →F | Same programUTSA Roadrunners | 25.5 | 9.4 | 50.3% |
| Austin Nunez →G | Same programUTSA Roadrunners | 28.5 | 9.8 | 41.7% |
| Matheo Coffi →F | Same programUTSA Roadrunners | 19.0 | 3.8 | 57.2% |
| Kaidon Rayfield →F | Same programUTSA Roadrunners | 20.0 | 6.7 | 45.3% |
| Daniel Akitoby →F | Same programUTSA Roadrunners | 13.9 | 5.7 | 60.9% |
| LJ Brown →G | Same programUTSA Roadrunners | 12.5 | 2.4 | 43.7% |
| Macaleab Rich →G | Same programUTSA Roadrunners | 15.1 | 8.1 | 59.8% |
| Mo Njie →C | Same programUTSA Roadrunners | 7.8 | 1.6 | 55.8% |
| Pierce Spencer →G | Same programUTSA Roadrunners | 12.5 | 3.5 | 41.5% |
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…
UTSA vs San José St
71.3UTSA
79.5San José St
San José St win estimate74.2%
Model signalLean
Projected home margin8.2
Projected total150.8
80% home-margin range-7.8 to 24.1
Estimated possessions67.8
Why the model tiltsfour-factor edge
Shot qualityHome 3.0 pts
San José St attack 50.9% · UTSA defense 53.1%UTSA attack 48.2% · San José St defense 53.3%
Ball securityHome 0.5 pts
San José St attack 16.1% · UTSA defense 16.5%UTSA attack 16.6% · San José St defense 16.6%
Second chancesAway 0.5 pts
San José St attack 29.5% · UTSA defense 33.2%UTSA attack 29.1% · San José St defense 32.3%
Free-throw pressureAway 3.7 pts
San José St attack 31.4% · UTSA defense 35.1%UTSA attack 31.9% · San José St defense 31.9%
Provident Credit Union Event Center
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Air Force vs UTSA
68.5Air Force
75.1UTSA
UTSA win estimate70.7%
Model signalLean
Projected home margin6.6
Projected total143.5
80% home-margin range-9.3 to 22.5
Estimated possessions67.8
Why the model tiltsfour-factor edge
Shot qualityAway 3.5 pts
UTSA attack 48.2% · Air Force defense 53.9%Air Force attack 50.9% · UTSA defense 53.1%
Ball securityHome 3.0 pts
UTSA attack 16.6% · Air Force defense 16.2%Air Force attack 20.0% · UTSA defense 16.5%
Second chancesHome 8.7 pts
UTSA attack 29.1% · Air Force defense 30.0%Air Force attack 23.6% · UTSA defense 33.2%
Free-throw pressureAway 3.6 pts
UTSA attack 31.9% · Air Force defense 36.1%Air Force attack 34.4% · UTSA defense 35.1%
UTSA Convocation Center
Preseason baseline · roster changes are not model features.
No verified pregame market line imported. Check the forecast record →
Army vs UTSA
71.8Army
77.5UTSA
UTSA win estimate68.9%
Model signalLean
Projected home margin5.8
Projected total149.3
80% home-margin range-10.2 to 21.7
Estimated possessions69.3
Why the model tiltsfour-factor edge
Shot qualityAway 1.4 pts
UTSA attack 48.2% · Army defense 53.6%Army attack 49.0% · UTSA defense 53.1%
Ball securityAway 0.0 pts
UTSA attack 16.6% · Army defense 15.7%Army attack 17.5% · UTSA defense 16.5%
Second chancesHome 4.9 pts
UTSA attack 29.1% · Army defense 29.6%Army attack 27.8% · UTSA defense 33.2%
Free-throw pressureHome 1.3 pts
UTSA attack 31.9% · Army defense 36.2%Army attack 29.4% · UTSA defense 35.1%
UTSA Convocation Center
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 →