A typical trade analyzer gives you a single number: "Team A wins by 7.2." That number is almost always generated by summing per-player season-long value, which is useful exactly when nothing else on your roster matters. A trade changes your roster, in your league, with your schedule. Our analyzer treats it that way.
The impact tree, not the impact number
Trade evaluation should consider category impact, roster fit, and the schedule rather than only a summed player value. Pick Pilot's beta uses rolling form and available schedule context, not an active licensed rest-of-season projection feed. Longer-horizon estimates depend on those inputs and their stated assumptions; they do not establish either manager's future record.
League-native, not global
Most public tools weight categories uniformly. Yours are weighted by how close the category is in your standings. If you're tied in rebounds and blocks but 40 clear in points, a trade that improves your points by 12% may matter less than a trade that nudges rebounds by 3%. Review the available category standings and roster context rather than relying on one player-value total.
Review trades with hindsight
Review completed trades using the latest available player ratings. These grades are a look back, not a reconstruction of what you knew when you accepted, and they do not prove who won the trade. Use them to revisit your reasoning about roster fit and the categories you needed.
Refusals are a feature
Sometimes the available inputs cannot support a single verdict. A rolling-form improvement can conflict with playoff-week schedule needs. Review the result's limitations and confidence rather than treating either estimate as a guaranteed outcome or assuming a universal refusal threshold.