Parsed from the export · 90 games · 20 May – 30 Jul
When Hennur actually plays
The note claimed the chat already knows when to schedule. Here is the whole dataset behind that line: every roster paste carries ticks, and read per game, per slot, per weekday they become a demand grid. 68 of 90 games parsed cleanly.
01 · The grid
Weekdays fill late. Weekends fill early. The dead zones are inverted.
Cell = average tick-fill of games actually played in that slot. After-work demand (8–9:30 PM) rules Mon–Fri; weekends flip to 5–7:30 PM, before plans, not after work.
Tue 9:30 (97%) · Fri 9:30 (100%) · all of Sunday. Schedule these blind.
Traps
Monday anything (76%, 2 collapses) · Thursday after 9:30 (53%) · Wednesday before 9 (64%).
Unexplored
Weekday early + Sat night are untested, not dead. Sat 9:30 PM is the most promising blank cell, Friday's 100% suggests weekend-late works.
02 · Two findings hiding in one grid
Wednesday and Thursday are mirror images.
Wednesday isn't weak. Early Wednesday is.
Wed 7:30–9:00 PM3 games
64%
Wed 9:30 PM3 games
98%
Poll receipt · 24 Jun · "Game today!!" 10:30–12:00 AM 9v9, 6 votes · 8:30–9:30 PM 7v7, 3 votes
Rule: never schedule Wednesday before 9 PM. Same people, same turf, 34 points of fill between the slots.
Thursday flips it. Work tomorrow wins.
Thu 7:30–9:00 PM6 games
85%
Thu 9:30 PM +2 games
53%
Poll receipt · 4 Jun (Thu) · 11 PM game? INNN, 3 votes · "Out I have work tomorrow", 5 votes
Rule: Thursday plays at 8, sleeps by 10. The weekend-eve energy doesn't arrive until Friday.
03 · Demand over the ten weeks
Confirmed players per week: 82 → 140.
Sum of paid ticks across each week's games. Growth of +71% in ten weeks, with two dips, both explained by the chat, both preventable.
8218 MAY
2525 MAY
821 JUN
1228 JUN
11515 JUN
9822 JUN
9629 JUN
976 JUL
14013 JUL
13520 JUL
3327 JUL*
25 May dip: the cancellation spiral, two games killed by late dropouts, fill crashed to 46%. This is the week the safety-rule + waitlist automation is designed for.29 Jun dip: monsoon week, rain cancels on 29, 30 Jun & 2, 3 Jul.13 Jul peak: 9 games, 98% fill, 140 paid spots ≈ ₹26k in the week. *Last bar is a part-week (export ends Thu 30 Jul).
04 · Format
9v9 is the product. 7v7 is the filler. 11v11 is the event.
9v9 · the workhorse41 games
87% fill
7v7 · the weekday filler24 games
91% fill
11v11 · the Sunday event3 games
94% fill
7v7 fills a hair better, it needs 4 fewer bodies. But when asked directly, the group wants the bigger game:
Read: schedule 9v9 wherever fill history allows; drop to 7v7 on risky slots (Mon, Thu-late) where 18 bodies is a stretch.
05 · So: the ideal week
What the data would schedule.
MONRest / test7v7 · 8 PM if any76% fill · weakest day 2 of 6 collapses
TUE9v99:30 – 11 PM97% · banker
WED9v99:30 – 11 PM98% late never before 9
THU9v98:00 – 9:30 PM85% · avoid 9:30+ (53%)
FRI · DOUBLE7v7 + 9v98 PM · then 9:30 PM91% + 100% · biggest day (14 games)
SAT7v76:00 – 7:30 PM94% · early lane test: 9:30 PM slot
SUN · SHOWCASE9v9 + 11v116 PM · then 10 PM98% + 100% · the 11v11 is the most-hyped game in the export (51 pastes)
That's 9 games/week ≈ 150+ paid spots ≈ ₹28k/week from this one community, before adding the untested cells.
Today this took a script and an export. It should be a tab on Trisha's dashboard.
Every fill %, poll and dip above was dug out of copy pasted text messages. Run the loop in software and this is recorded as structured data by default: demand curves, slot tests and pricing become a glance, not an archaeology project. That is the whole note, evidenced. The summary sits one click back, and the test costs one Wednesday.