# pydfs-lineup-optimizer Normal Randomness Repo-Grounded Packet

Generated: 2026-06-20 16:32:22 JST
Offer page: https://jaxassistant55.github.io/jax-micro-offer-studio/pydfs-normal-randomness-strategy-sprint.html
Public repo: https://github.com/DimaKudosh/pydfs-lineup-optimizer
Local checkout: `/Users/jax/autonomous_earning_run_2026-06-09/non_bounty/pydfs-lineup-optimizer`
Local patch file: `/Users/jax/autonomous_earning_run_2026-06-09/non_bounty/pydfs_normal_randomness_strategy.patch`
Local test output: `/Users/jax/autonomous_earning_run_2026-06-09/non_bounty/pydfs_normal_randomness_test_output.txt`
Inspected commit: `429db96`
Paid-help issue: https://github.com/DimaKudosh/pydfs-lineup-optimizer/issues/367
Fixed first sprint: $100
Confirmed money: $0

## Issue state

The issue is open and asks for normal distribution randomness while doing each lineup. It also says the requester would be happy to pay for the work to be written into their code. Existing comments contain ad hoc snippets, but no upstream PR exists and the thread still has users asking how to integrate the strategy cleanly.

## Files changed in the prepared local patch

1. `pydfs_lineup_optimizer/fantasy_points_strategy.py`
   - Adds `NormalFantasyPointsStrategy`.
   - Uses Python's `random.gauss`.
   - Uses player `max_deviation` when available.
   - Falls back to constructor `default_deviation`.
   - Clamps to `fppg_floor` and `fppg_ceil` when present.

2. `pydfs_lineup_optimizer/__init__.py`
   - Exports `NormalFantasyPointsStrategy` for `from pydfs_lineup_optimizer import NormalFantasyPointsStrategy`.

3. `tests/test_fantasy_points_strategy.py`
   - Adds deterministic mock-based tests for normal sampling and floor/ceiling clamps.

4. `docs/usage.rst`
   - Adds a normal-distribution randomness usage section.

## Verification

```text
collected 5 items
=============================== warnings summary ===============================
======================== 5 passed, 36 warnings in 0.07s ========================
```

Full local test output is stored at:

`/Users/jax/autonomous_earning_run_2026-06-09/non_bounty/pydfs_normal_randomness_test_output.txt`

## Exact user steps to claim this lane

1. Open the live offer page: https://jaxassistant55.github.io/jax-micro-offer-studio/pydfs-normal-randomness-strategy-sprint.html
2. Open the source issue: https://github.com/DimaKudosh/pydfs-lineup-optimizer/issues/367
3. Review the local patch file: `/Users/jax/autonomous_earning_run_2026-06-09/non_bounty/pydfs_normal_randomness_strategy.patch`
4. Review focused test output: `/Users/jax/autonomous_earning_run_2026-06-09/non_bounty/pydfs_normal_randomness_test_output.txt`
5. Add only a seller-owned checkout, invoice, marketplace order, funded milestone, or payment-request URL.
6. Do not post a comment, send email, open a PR, or send the patch unless you approve the external action.
7. Require this exact acceptance before payment:

   I accept the pydfs-lineup-optimizer Normal Randomness Strategy Sprint fixed-scope terms at $100. I understand work starts only after seller-owned external payment proof exists; I will provide only public or buyer-authorized code and non-sensitive requirements; the deliverable is limited to the prepared normal-distribution fantasy points strategy patch, package export wiring, docs usage note, focused tests, and apply instructions; and private user data, credentials, payment data, sports betting account data, private projections, proprietary contest files, public posting, pull requests, or ongoing revisions are not included unless separately agreed before payment.

8. Deliver the patch only after external payment proof or after you explicitly decide to publish it as unpaid open-source work.
9. Capture proof: buyer URL/message, exact accepted scope, payment reference, amount, fees, refund/hold state, delivery URL or PR URL, buyer/platform acceptance if required, payout/payable/cleared status, and date.
10. Count $0 until posted, released, funded, payable, cleared, credited, or verified net money exists.

## Draft response, still not posted

I prepared a small tested patch for normal-distribution randomness in pydfs-lineup-optimizer. It adds `NormalFantasyPointsStrategy`, exports it from the package API, documents usage with `optimizer.set_fantasy_points_strategy(...)`, and covers player-level deviation plus floor/ceiling clamps in deterministic tests. The focused test file passes locally. I can hand over the patch or adapt it to your fork/private code after fixed-scope acceptance and external payment proof.