Sharpshooters — team report

A total-cost-of-ownership comparison of three hypothetical bench-player acquisitions, with salary projected forward rather than held flat — using a decay curve fit from 15 real players' actual season-by-season salary histories.

The three options modeled:

• A — $800/wk, $40,000 acquisition, starting age 32
• B — $250/wk, $100,000 acquisition, starting age 50
• C — $2,000/wk, $1,000 acquisition, starting age 30

Calculated A is cheapest from season 3 onward, indefinitely. Both A and B eventually hit the $200 floor — A by season 16, B already by season 3 — and once both are floored, the gap between them (B's larger acquisition price) never closes. C is only competitive in the first two seasons, on the strength of its near-zero acquisition price alone; its high starting salary catches up fast once decay hasn't yet had time to bite.

Payback/surplus analysis of the real, already-executed $205,800 arena expansion, using this report's own live arena data.

Cumulative surplus (cumulative incremental revenue − $205,800), assuming revenue grows at a flat annual rate:

Calculated The expansion pays for itself within its second season in every scenario tested. Growth rate barely moves the payback timing (it's a near-term, low-compounding effect at that horizon) but compounds long-run surplus substantially — the 20-season gap between 0% and 10% growth is roughly 3x the baseline surplus itself.

[Inference] Growth rates (0/3/5/8/10%) are illustrative, not verified against any real trend. Two of the four current price tiers are already near their game-imposed ceiling, which caps how much of that growth could plausibly come from further price increases rather than attendance/demand growth.

Every point in a skill costs a different amount in weekly salary. Ground-truth curves pulled from buzzer-manager.com's salary estimator (each of the 12 rated skills queried at every rating 1–20, holding age/nationality/potential and the other 11 skills fixed at 10) — cross-validated against a separate 266-player real-market regression, which independently ranked the same skills the same way. Full data: salary-model/skill-curves-reference.md and salary-model/formula-history.md in the GitHub repo.

Calculated Every skill except Stamina/Free Throw follows the same two-regime shape — a nearly flat "low regime" up to a per-skill breakpoint, then a much steeper "high regime" for the rest of the range (not a smooth power law). Baseline weekly salary with everything at rating 10 is $17,609 — every curve passes through that exact value, confirming the isolated-skill queries are internally consistent.

[Inference] Stamina and Free Throw training is essentially "free" salary-wise — push those to the 6–8 / 7+ targets already in this team's training doctrine without hesitation. Jump Shot and Rebounding are the two skills where a big push has the largest, most convex salary consequence — worth being deliberate about timing (e.g. concentrated pushes rather than a slow drip once past each skill's breakpoint). The separate 266-player market regression (pooled model, R²=0.891) found Age has no real effect on salary once current skills are controlled for — BuzzerBeater recalculates salary once per season from current skills only, so an apparent "age discount" on a young, still-training player is really just salary that hasn't been recalculated since their last training gains, not a market age premium.

336 Brazil teams scraped from public buzzerbeater.com pages (Liga Nacional + Div II + all 16 Div III conferences) — Sharpshooters' actual peer group, not a top-division benchmark. Full data and scripts: arena-model/ in the GitHub repo (brazil_leagues_all.csv, brazil_league_analysis.py, sharpshooters_arena_optimizer.py).

[Inference] A same-snapshot check across all 336 teams found win% and fill rate negatively correlated (−0.17 to −0.18) — losing teams (win% ≤ 0.4) average 90.3% fill vs. 84.5% for winning teams (win% ≥ 0.6), a −5.9 point gap. Plausible confound: winning teams tend to run bigger arenas that are harder to fill 100%, while many bottom-table teams sit at the 6,000-seat capacity floor and sell out easily regardless of form. Fill rate alone is not a clean price-demand signal without controlling for capacity and form.

Calculated Ranked expansion scenarios by budget, from the optimizer's own recommendation engine:

[Inference] Price-change and expansion estimates assume a flat −0.4 elasticity (not fitted from real data) and, for the percentile comparisons, use the closer 256-team Division III comp set rather than the top-division benchmark used earlier in this guide's arena-expansion payback analysis above. Re-run sharpshooters_arena_optimizer.py / brazil_league_analysis.py periodically — prices, capacity, and the comp set all drift as the season progresses.