Texas Tech at Duke
A pregame research note built from the stored 2026–27 forecast, its stored factors and the questions still waiting for film or roster confirmation.
Forecast edition basketball-efficiency-v2-ab7f181f3f19 · captured Sep 23, 2026
Texas Tech 69.1 · Duke 76.8
Primary preseason estimate from the published efficiency model. The range describes held-out model error, not a promise about the final score.
What this game analysis uses.
Read the forecast, historical workload, shot map and roster signals in separate columns. A model edition identifies the registered estimate; an internal receipt identifies the retained data edition. Missing or mismatched evidence stays visible as unavailable.
| Evidence | Coverage attached to this game | Edition / receipt | Captured / reviewed | How to learn from it |
|---|---|---|---|---|
| Published game scheduleUnavailable | Start time unconfirmed | Unavailable | — | The forecast remains available, but market checks stay withheld until the start is confirmed. Keep the canonical date separate from a confirmed source clock. |
| Forecast editionRegistered edition | basketball-efficiency-v2-ab7f181f3f19 | basketball-efficiency-v2-ab7f181f3f19 | Sep 23, 2026 | Use this ID and capture clock when comparing the forecast with a later result. |
| Team + player archiveRegistered edition | 6 exact player profiles · two team profiles | 2026-09-23T03:50:32.300000Z | Sep 17, 2026 | Historical workload describes the old sample; it does not establish current availability. |
| Shot coordinate archiveVerified source release | 6 exact joins · 2,102 matched attempts · 2,093 located | 411d4ea11dba7d6688d717e26b3a6807640ae7f3b615b054a775e6f814d5c672 | Sep 5, 2026 | Located attempts are a subset of matched attempts; missing coordinates stay missing. |
| Recruiting releaseVerified source release | 1/2 exact programs · 3 people · 1 reviewed sources | 6534ecd70b2b87befb22c2a5781c8b53dd9069e57a668d0409687c9f60d28a06 | Sep 21, 2026 | A dated announcement is evidence of an event, not proof of eligibility or a projected role. |
| Roster observationVerified source release | 23 listed rows · 2027 snapshot | ecf68bc15c3cb083dafa996b55b522bb578de7bf1f7aa5f1d99a726059da4774 | Sep 17, 2026 | Roster status is an observed listing label; it is not a lineup or eligibility ruling. |
This table documents provenance and joins. It does not turn a source listing into an availability decision, and it does not add a second forecast to the stored model.
How the projected score is built.
This table reconstructs the stored ridge model from its published coefficient arrays. Each efficiency term is points per 100 possessions; the final score is efficiency × projected pace ÷ 100. It is an explanation of the estimate, not an additional forecast.
| Term | Texas Tech | Duke |
|---|---|---|
| League baseline | 107.03 | 107.03 |
| Own offense effect | +14.38 | +18.33 |
| Opponent defense effect | -16.26 | -8.46 |
| Venue effect | +0.00 | +0.00 |
| Projected efficiency | 105.16 | 116.91 |
| Projected pace | 65.67 | 65.67 |
| Score from equation | 69.06 | 76.78 |
A neutral-site game has zero venue effect. A missing or edition-mismatched coefficient set suppresses this table rather than presenting stale arithmetic.
How much has this model missed?
These held-out results describe the forecast system behind this notebook. They are a calibration reference for the range, not a guarantee about this game and not evidence of a market edge.
Training seasons: 2023, 2024, 2025, 2026 · constant home-margin baseline MAE: 12.0 pts. The test season remains outside model fitting and calibration.
Turn the forecast into questions.
Read these in order before opening the deeper tables. Each row is arithmetic over the stored forecast, exact team ratings, matchup factors or matched roster scenario. It does not add a new model.
| Read | Finding | Stored evidence | Question to take to film |
|---|---|---|---|
| Step 1Start with the range | Both teams remain inside the 80% margin range | Duke is the baseline side by 7.7 points; the stored home-margin range is -8.2 to +23.6. | Which early matchup signal would make you update away from the baseline? |
| Step 2Find the pressure point | Texas Tech owns the largest stored factor edge | effective field-goal rate · 1.4 percentage points toward Texas Tech. | Which actions and lineups are creating that effective field-goal rate edge, and does it hold against the expected rotation? |
| Step 3Check the possession count | 65.7 projected possessions | -1.3 versus the two teams’ 67.0-possession historical tempo midpoint. | Which team can keep the game near that lower projected count, and what stops transition opportunities? |
| Step 4Test roster sensitivity | 2.3-point movement toward Texas Tech | Baseline +7.7 home · roster lens +5.4 home. | Which source-listed players account for that movement, and is there dated evidence for their current availability and role? |
Missing rows mean the exact supporting record did not pass the notebook’s identity or numeric checks; absence is not scored as a neutral signal.
The numbers behind the estimate.
Latest completed-season team rates carried into this forecast edition. They describe the inputs and context; they are not a claim about a current lineup.
| Metric | Texas Tech | Duke |
|---|---|---|
| Adj O | 121.4 | 125.4 |
| Adj D | 98.6 | 90.8 |
| NET | 22.8 | 34.6 |
| PACE | 67.1 | 66.8 |
| SOS | 14.6 | 11.8 |
| eFG% | 56.1% | 56.6% |
| TO% | 15.8% | 15.9% |
| ORB% | 33.2% | 38.4% |
| FTR | 27.7% | 38.2% |
What do the last five show?
Season and last-five observations come from the same retained team profiles. They are descriptive samples for film review; they are not a trend claim, a cause, or a replacement for the stored forecast baseline.
| Program / exact ID | Sample | Record | Pace | Offensive efficiency | Defensive efficiency | Effective FG% | Turnover rate | Offensive rebound rate | Free-throw attempt rate |
|---|---|---|---|---|---|---|---|---|---|
| Texas TechID 2641 | Season34 games | 23-11 | 67.9 | 117.8 | 107.2 | 56.1% | 15.8% | 33.2% | 27.7% |
| Texas TechID 2641 | Last five5 games | 1-4 | 64.8 | 108.0 | 120.6 | 53.6% | 16.7% | 27.9% | 24.6% |
| DukeID 150 | Season38 games | 35-3 | 66.8 | 122.2 | 95.2 | 56.6% | 15.9% | 38.4% | 38.2% |
| DukeID 150 | Last five5 games | 4-1 | 64.3 | 117.5 | 106.0 | 52.9% | 17.4% | 43.5% | 39.7% |
Scouting edition 2026-09-23T03:50:32.300000Z · model basketball-efficiency-v2-ab7f181f3f19 · captured Sep 17, 2026.
Who carried the old possessions?
The three highest-minute contributors in the latest completed season. These rows preserve recorded production for preparation; they are not a projected rotation or an availability decision.
What should the staff test first?
These role signals come from the same completed-season player records. Each question is attached to a recorded workload or rate field; missing denominators remain unavailable.
| Program / player | Recorded role signals | Film question |
|---|---|---|
| Christian AndersonTexas Tech · G | Usage 23.8%Team minutes 95.6%A/TO 2.243PA 260.0 | How does the defense force this high-usage role into lower-value decisions? |
| Donovan AtwellTexas Tech · G | Usage 15.1%Team minutes 86.4%A/TO 1.933PA 284.0 | How does the defense force this high-usage role into lower-value decisions? |
| Jaylen PettyTexas Tech · G | Usage 16.4%Team minutes 75.6%A/TO 2.473PA 184.0 | How does the defense force this high-usage role into lower-value decisions? |
| Cameron BoozerDuke · F | Usage 30.0%Team minutes 83.8%A/TO 1.643PA 138.0 | How does the defense force this high-usage role into lower-value decisions? |
| Isaiah EvansDuke · G | Usage 24.9%Team minutes 70.7%A/TO 1.123PA 280.0 | How does the defense force this high-usage role into lower-value decisions? |
| Dame SarrDuke · G | Usage 15.8%Team minutes 58.7%A/TO 1.053PA 133.0 | How does the defense force this high-usage role into lower-value decisions? |
Texas Tech
| Player | MIN | MPG | PPG | APG | TS% |
|---|---|---|---|---|---|
| Christian AndersonG | 1,267 | 38.4 | 18.5 | 7.4 | 62.6% |
| Donovan AtwellG | 1,179 | 34.7 | 13.5 | 0.8 | 68.3% |
| Jaylen PettyG | 1,002 | 30.4 | 9.9 | 2.2 | 55.5% |
Duke
| Player | MIN | MPG | PPG | APG | TS% |
|---|---|---|---|---|---|
| Cameron BoozerF | 1,274 | 33.5 | 22.5 | 4.1 | 65.3% |
| Isaiah EvansG | 1,075 | 28.3 | 15.0 | 1.3 | 59.0% |
| Dame SarrG | 892 | 23.5 | 6.4 | 1.1 | 51.4% |
Turn the factor edge into a film drill.
These links join the historical workload table to the retained national coordinate archive by exact player and team ID. The questions use recorded attempt denominators to choose film; they do not predict a current rotation or treat an archived shot map as availability.
| Program / player | Recorded shot evidence | Preparation question | Drill-down |
|---|---|---|---|
| Christian AndersonTexas Tech · G | 408 matched attempts · 407 with retained coordinates · 33 gamesExact archive name | 60% of recorded attempts are threes. How will the defense change the closeout without giving up the next action? | View court map ↗ |
| Donovan AtwellTexas Tech · G | 297 matched attempts · 297 with retained coordinates · 34 gamesExact archive name | 90% of recorded attempts are threes. How will the defense change the closeout without giving up the next action? | View court map ↗ |
| Jaylen PettyTexas Tech · G | 265 matched attempts · 263 with retained coordinates · 33 gamesExact archive name | 68% of recorded attempts are threes. How will the defense change the closeout without giving up the next action? | View court map ↗ |
| Cameron BoozerDuke · F | 512 matched attempts · 508 with retained coordinates · 38 gamesExact archive name | Where does the located sample cluster, and which coverage or transition rule should the staff test against those looks? | View court map ↗ |
| Isaiah EvansDuke · G | 422 matched attempts · 422 with retained coordinates · 38 gamesExact archive name | 65% of recorded attempts are threes. How will the defense change the closeout without giving up the next action? | View court map ↗ |
| Dame SarrDuke · G | 198 matched attempts · 196 with retained coordinates · 38 gamesExact archive name | 64% of recorded attempts are threes. How will the defense change the closeout without giving up the next action? | View court map ↗ |
Located coordinates are a subset of matched attempts; missing locations remain in the attempt denominator and are not imputed.
Who is listed today?
Exact-ID rows from the current roster snapshot, ordered by prior recorded minutes. Status is an observed listing label; it does not establish eligibility, availability, a commitment or a projected rotation.
| Program | Listed | Same program | Different program | New to dataset | Ambiguous / other | Prior stat profiles | Recorded prior minutes |
|---|---|---|---|---|---|---|---|
| Texas TechOpen exact roster observations → | 12 | 11 | 0 | 1 | 0 | 11 / 12 | 4,379 |
| DukeOpen exact roster observations → | 11 | 9 | 0 | 2 | 0 | 9 / 11 | 4,482 |
Same-program, different-program and new-to-dataset are exact retained roster observations. Recorded prior minutes sum only valid attached stat profiles; they do not establish current availability, eligibility or role.
Where is prior experience attached?
Source positions group each current listing as guard, forward, center or unreported. Minutes belong to retained prior-season stat profiles and stay separated by same-program, different-program and other observation status. They are context for film review, not a projected rotation.
| Program | Source role | Listed | Prior profiles | Prior minutes | Same-program minutes | Different-program minutes | Other-status minutes |
|---|---|---|---|---|---|---|---|
| Texas Tech | Guard | 6 | 6 | 1,976 | 1,976 | 0 | 0 |
| Texas Tech | Forward | 6 | 5 | 2,403 | 2,403 | 0 | 0 |
| Texas Tech | Center | 0 | 0 | 0 | 0 | 0 | 0 |
| Texas Tech | Unreported | 0 | 0 | 0 | 0 | 0 | 0 |
| Duke | Guard | 9 | 7 | 3,758 | 3,758 | 0 | 0 |
| Duke | Forward | 0 | 0 | 0 | 0 | 0 | 0 |
| Duke | Center | 2 | 2 | 724 | 724 | 0 | 0 |
| Duke | Unreported | 0 | 0 | 0 | 0 | 0 | 0 |
Roster season 2027 · receipt ecf68bc15c3cb083dafa996b55b522bb578de7bf1f7aa5f1d99a726059da4774 · captured Sep 17, 2026.
Texas Tech
| Player | Status | MIN | MPG | PPG | TS% |
|---|---|---|---|---|---|
| Jaylen PettyG | same program | 1,002 | 30.4 | 9.9 | 55.5% |
| LeJuan WattsF | same program | 902 | 27.3 | 11.8 | 53.3% |
| JT ToppinF | same program | 871 | 34.8 | 21.8 | 57.1% |
| Tyeree BryanG | same program | 564 | 17.1 | 3.5 | 47.1% |
| Luke BamgboyeF | same program | 347 | 16.5 | 4.5 | 57.1% |
| Leon HornerG | same program | 206 | 9.0 | 2.8 | 55.0% |
| Josiah MoseleyF | same program | 194 | 13.9 | 5.5 | 68.5% |
| Nolan GrovesG | same program | 134 | 6.4 | 1.0 | 39.3% |
Duke
| Player | Status | MIN | MPG | PPG | TS% |
|---|---|---|---|---|---|
| Dame SarrG | same program | 892 | 23.5 | 6.4 | 51.4% |
| Cayden BoozerG | same program | 866 | 22.8 | 7.7 | 59.2% |
| Caleb FosterG | same program | 821 | 24.9 | 8.3 | 54.1% |
| Nikolas KhameniaG | same program | 748 | 19.7 | 5.7 | 56.7% |
| Patrick Ngongba IIC | same program | 702 | 21.9 | 10.1 | 64.5% |
| Darren HarrisG | same program | 347 | 9.6 | 3.3 | 54.3% |
| Cameron SheffieldG | same program | 44 | 2.9 | 0.5 | 33.3% |
| Jack ScottG | same program | 40 | 2.9 | 0.6 | 66.7% |
Variance belongs in the story.
The nominal home-margin range covers 31.8 points, so the forecast is a starting point for preparation rather than a script. Identify which lineup and shot-quality questions could move this game toward either edge.
Questions for the next check
- Which lineup combination gives the underdog its clearest path toward the top of the range?
- Can the projected favorite reproduce its best Four Factor possession against this opponent?
- Which current roster or availability source should be checked before publication?
Why the baseline leans.
| Factor | Home attack | Away defense | Away attack | Home defense | Edge |
|---|---|---|---|---|---|
| Shot quality | 57.1% | 48.0% | 55.9% | 45.4% | Away 1.4 pts |
| Ball security | 15.7% | 16.9% | 15.6% | 17.6% | Away 0.9 pts |
| Second chances | 36.2% | 27.6% | 33.3% | 25.1% | Home 0.4 pts |
| Free-throw pressure | 37.0% | 31.5% | 31.7% | 26.0% | Away 0.2 pts |
These are the stored matchup-factor estimates for this edition. They identify a film starting point; they do not establish a tactical result or a player availability decision.
Check the line beside this forecast.
The notebook refreshes the exact game and current forecast edition before showing any qualifying market comparison. A missing quote stays unavailable; no line or edge is inferred.
Checking the current forecast edition and its qualifying market observations…
Keep the evidence chain open.
- Confirm current availability and the expected rotation from a dated update.
- Use the roster and player archives to identify the personnel behind each factor.
- Read the interval before treating a close projection as a decisive edge.
Follow the record.
The schedule ID, model edition and captured forecast remain attached to this notebook. A missing market observation is unavailable evidence, not a zero.
No verified pregame market line is attached to this edition.