Does StagSense work?
Updated October 10, 2026
StagSense has been tested against real deer data in 13 states, using four independent measures: hunter harvest, deer-vehicle collisions, GPS-collared deer, and a nationwide trail-camera sample. The score held up statistically in 9 of the 13 states, even after accounting for time of year. In 3 more it leaned the same way without being conclusive, and in Colorado it showed no relationship.
What we tested
We didn't just build StagSense on hunting theory. We tested it against real deer data in 13 states, using four completely different ways of measuring deer activity.
The most direct test is bowhunting harvest, which records real deer taken county by county and day by day: 133 counties and about 638,000 archery deer in Maryland, Virginia and Georgia over 10 seasons. We compared top-rated days only with low-rated days in the same county and the same month, so the calendar couldn't do the work. Top-rated days produced 1.4 to 1.8 times the archery harvest, and 1.3 to 1.5 times with a stricter model that also controls for season, weekday and firearm season. Maryland was strongest: about 1.8 times overall, and about 2 times for bucks. In all three states, buck harvest tracked the score more strongly than doe harvest.
The edge isn't only a rut story. Even outside the rut, top-rated days produced about 20 to 25% more archery harvest in all three states. It is sharpest during the rut.
Deer-vehicle collision records agree in 7 of the 11 states we tested, after accounting for time of year. Across all 13 states, the score held up statistically in 9.
More hunters go out on good-weather days, so harvest likely overstates the effect somewhat. That's why we also checked a nationwide trail-camera sample, which has no hunter or traffic bias. It agreed with the pattern too, modestly but consistently. GPS-collared does in western Virginia added a fourth: their movement tracked the score most closely during the pre-rut.
The four data sets
| Data set | What it measures | Coverage | Key finding |
|---|---|---|---|
| Archery harvest records: Maryland, Virginia, Georgia | Deer actually taken by bowhunters, county by county and day by day. Harvest also depends on how many hunters go out, and more go out on good-weather days, so it likely overstates the effect somewhat | 133 counties, 10 seasons (2016 to 2026), about 638,000 archery deer | Compared with low-rated days in the same county and month, top-rated days produced 1.4 to 1.8 times the archery harvest (Maryland 1.8x, Virginia 1.6x, Georgia 1.4x). Buck harvest tracked the score more strongly than doe harvest in all three states |
| Deer-vehicle collision records, 11 states (MI, WI, NY, TN, VA, NC, OH, IL, TX, FL, CO) | Deer actively crossing roads | State-level records, multi-year | Statistically significant in 7 of 11 after accounting for time of year (MI, NY, VA, OH, IL, TX, FL). Leaned positive but not conclusive in WI, TN, NC. No relationship in CO (mule-deer-dominant) |
| Trail-camera detections, nationwide sample | Deer detected on camera, no traffic or hunting-effort bias | 40 locations, 121,177 detections, August 2019 to December 2023 | Higher scores tracked with more detections (about 5% more per +10 score points, statistically significant). Modest but consistent |
| GPS collar research, western Virginia | GPS-tracked deer movement | 35 does in Highland County, Virginia, 559,831 hourly fixes | Movement tracked the score most closely during the pre-rut (r=0.331). Doe-only, so it under-represents rut movement |
Maryland, Virginia and Georgia harvest data came from state wildlife agency records (Maryland DNR by FOIA request, Virginia DWR by data request, Georgia DNR's public Game Check data). Collision data sourced from publicly available state records. Camera data drawn from the Snapshot USA nationwide detection dataset. GPS data from a doe-collar study in Highland County, Virginia. Statistical basis: negative-binomial regression models with calendar-month controls and clustered standard errors, corrected for testing many states at once; significance means a corrected p below 0.05 on the score. Not every sub-segment (individual rut phases, the doe-only cuts) clears that bar.
Top-rated days versus low-rated days
How the comparison works: take every top-rated day (score 70 or higher) and compare it with low-rated days (score under 40) in the same county and the same month. That keeps the calendar out of it: a November day is only compared with other November days in the same place.
| State | Whole season | Outside the rut | Bucks, whole season |
|---|---|---|---|
| Maryland | about 1.8x | about 1.25x | about 2x |
| Virginia | about 1.6x | about 1.2x | about 1.7x |
| Georgia | about 1.4x | about 1.25x | about 1.6x |
With a stricter model that also controls for season, weekday and firearm season, top-rated days still produced about 1.3 to 1.5 times the archery harvest (Maryland 1.5x, Virginia 1.3x, Georgia 1.4x).
More hunters go out on good-weather days, so harvest likely overstates the effect somewhat. That's why we also checked trail cameras, which have no hunter or traffic bias.
These figures describe the day as the score rates it, weather and rut phase together, compared within the same month. They are not a weather-only effect.
Where the edge is strongest
The edge is largest during the rut and smaller outside it, and it is present in both. Within the same county and month, top-rated rut days produced about 1.4 to 1.6 times the archery harvest of low-rated rut days across the three harvest states; outside the rut, about 1.2 to 1.25 times.
The honest part: StagSense is a ranking tool, not a guarantee. It tells you which days are your best bets. The edge is largest during the rut and smaller outside it. It does not claim to read your specific property.
Where it does not hold up
Where it doesn't hold up, we say so. In Colorado, where mule deer dominate, the score showed no relationship. Collision data in Wisconsin, Tennessee and North Carolina leaned positive but was not conclusive. StagSense is built and validated for whitetail deer.
Thirteen states. Four independent measures. Held up in 9, leaned the same way in 3 more, and we name the one with no effect.
Who did the analysis
All analysis was conducted independently by Bluetag Software using publicly available data. No university, government agency, or third party reviewed or endorsed these findings.
To see how the score itself is built, read How does StagSense score a day?
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