waist to chest from WNW at 10s; falling; SSW 4 kt, fairly manageable.
Small windows, sharp filters.
From Apr 22 through May 12, the nightly Campus Point / Sands handoff produced 378 forecast-window rows. The clean read: Sands had the better ceiling, dawn was the reliable window, and short-period west energy kept most days in the “maybe” band rather than true high-stoke territory.
Executive Read
What mattered
- Energy was not the bottleneck alone. The period field was short on 96 of 126 latest calls, which kept decent-looking west direction from turning into strong analogs.
- Sands won the ceiling. The top completed call was Sands Mid-morning on Apr 28: 10/10, waist to chest, WNW at 10s.
- Wind rarely gave the model a clean bonus. Manageable or favorable wind showed up often, but the report mostly lacked classic glassy/offshore tags.
- Campus needed tide help. Its better moments clustered around near-high/falling rather than low-tide exposure.
Completed-day rating pulse
Line shows each completed target day’s best available window. It reads as a low-to-mid consistency pattern with only a few clean spikes.
Three-Week Calendar
Each cell shows the best latest call for that target day across Campus Point and Sands. This is the simplest “should Greg have looked?” view. The live handoff also contains forward-looking rows for May 13, May 14; best pending look is Sands Mid-morning on May 13 at 7/10.
Spot × Window Infographic
Best Windows
waist to chest from WNW at 11s; rising; NE 0 kt, light offshore / favorable.
waist to chest from WNW at 12s; rising; W 6 kt, fairly manageable.
waist to chest from WNW at 10s; rising; WSW 6 kt, fairly manageable.
waist to chest from WNW at 5s; falling; SW 3 kt, fairly manageable.
waist to chest from WNW at 6s; falling; SSW 4 kt, fairly manageable.
waist to chest from WNW at 7s; rising; E 5 kt, light offshore / favorable.
waist to chest from WNW at 12s; near high; SW 4 kt, fairly manageable.
Condition DNA
Swell direction
Period band
Practical size
Tide state
Wind family
Rating distribution
Observed Buoy Backcheck
This layer uses cached observed rows from the Santa Barbara lead/entry buoys, not the generated forecast. It is a coarse water-state check, not a spot-level surf report.
Buoy summary
| Buoy lane | Coverage | Avg height | Avg dominant period | Peak observed pulse |
|---|---|---|---|---|
| Santa Maria lead | 19 days | 5.9 ft | 12s | 9.2 ft on May 1 |
| West Santa Barbara | 19 days | 5.3 ft | 12s | 8.2 ft on May 1 |
| Harvest entry | 19 days | 6.2 ft | 12s | 8.9 ft on May 1 |
Forecast Stability
Lead-time noise
Because each nightly handoff looks three days ahead, the same target window can be seen one, two, or three times. Average forecast swing across repeated completed windows was 1.3 rating points. That is useful: the model is stable enough for a nightly call, but big changes still deserve attention.
Biggest revisions
- Apr 28 Sands / Lunch moved 5→5 with a 5-point forecast range.
- May 4 Sands / Lunch moved 5→7 with a 5-point forecast range.
- May 4 Sands / Mid-morning moved 5→10 with a 5-point forecast range.
- Apr 29 Sands / Lunch moved 5→9 with a 4-point forecast range.
- May 1 Sands / Lunch moved 5→9 with a 4-point forecast range.
Historical Baseline
| Spot | Sessions | Avg quality | Worth-it share | Avg model score |
|---|---|---|---|---|
| Campus Point | 506 | 3.4 | 53% | 4.1 |
| Sands | 123 | 3.5 | 61% | 5.6 |
Campus Point historical good-session fingerprint
Sands historical good-session fingerprint
Operational Takeaways
How I’d use this tomorrow
- Keep the nightly report biased toward the single best target window, not three equal windows per day.
- Flag period upgrades more aggressively; short-period west was the recurring almost-but-not-quite pattern.
- Make Sands the first check when the call is high-5 or better and wind is manageable, because its recent ceiling beat Campus.
- For Campus, require a stronger tide/context justification before calling anything better than low-expectation.
Next analytics upgrade
- Add observed buoy deltas for each completed target day to show whether the actual water under- or over-performed the forecast.
- Keep a Greg feedback field: went / skipped / regretted / scored. That will turn this from forecast analytics into real decision analytics.
- Separate “fun social paddle” from “quality wave” in the target model; the history clearly has both signals mixed together.