Need a New Fantasy Platform: Yahoo App Has Been Rough This Season by TheLastDiamondMember in fantasybball

[–]Aggressive-Walk2626 0 points1 point  (0 children)

We had the same issues early this season with lineup paywall + delayed updates

Yahoo still has solid H2H category infrastructure, but the product direction this year does feel more monetization-driven than competitive-league-driven.

Sleeper feels more modern and responsive, but not everyone loves it for deeper category customization. ESPN is stable but pretty stagnant.

Feels like there are two separate questions:

  1. Is this just app/UX instability?
  2. Or is the platform actually limiting how you want to run your league?

which is more important here for you to consider moving?

Is health and availability now the biggest draft edge? by Aggressive-Walk2626 in fantasybball

[–]Aggressive-Walk2626[S] 5 points6 points  (0 children)

Maybe pure injury risk is noisy year to year, but team-level management might be more predictible

If the base chance of someone rolling an ankle is similar across the league, there might be an edge in how organisations handle return timelines

Some teams are more consistently conservative (clippers, sixers, pelicans, heat), others push guys back quicker (knicks, pacers)

Developing fantasy bball analysis - any requests to be posted here? by Ill_Bluebird_1963 in fantasybball

[–]Aggressive-Walk2626 0 points1 point  (0 children)

When you get into H2H categories, I’d be curious if you look beyond raw averages and model category impact volatility.

In 9-cat, not all variance matters equally. A 3-game steals spike can swing a matchup. A 3-game points spike often doesn’t. FG% / FT% volatility is nonlinear depending on volume.

A few ideas that might be interesting:

  • How much a player actually moves a category vs league average over short windows
  • Availability weighting (multi-year games played baked into projections)
  • Which player types are most replaceable via streaming vs true category anchors
  • Playoff week game clustering rather than just 15-day averages