Guides: getting the most out of PkDaTa

PkDaTa is three tools that share one workflow: decide who to bring, decide what they do, and decide how they're built. Each tool answers one of those questions with real match data instead of guesswork. If you are new here, this page explains the intended order of operations; the per-tool guides below walk through every control on each page.

The team-building workflow

Step 1 — pick your core (Win Rate Identifier). Start from the one or two Pokémon you already want to play. Enter them in the Win Rate Identifier and let "Completes the team" show you which partners historically raise the win rate of teams built around that core. Use "Discover cores" when you have no starting point at all and want to see which combinations are winning in the current regulation. By the end of this step you should have four to six names and a sense of how proven the combination is.

Step 2 — close your offensive gaps (Coverage Optimizer). Take the roster to the Coverage Optimizer, give each Pokémon the moves you plan to run, and look at the team coverage holes — the usage-weighted list of threats nothing on your team can currently knock out in two hits. The tool then ranks every legal move you could add by how much of the metagame it brings into KO range, so the last moveslot becomes a measured decision instead of a hunch.

Step 3 — finish the spreads (EV Optimizer). Send the team to the EV Optimizer (there is a hand-off button on the Win Rate Identifier) and set concrete benchmarks: survive a specific attack, guarantee a specific KO, outspeed a specific threat. The optimizer solves for the minimum stat-point spread that satisfies every benchmark at once, which frees up points you can spend elsewhere.

None of the steps is mandatory — each tool stands alone — but they are designed to hand off to each other in that order, and the numbers you see at every step come from the same underlying tournament and replay data.

Per-tool guides

• Win Rate Identifier guide — format rankings, partner suggestions, core discovery, and how to read win rates, lift, and sample sizes without fooling yourself.
• Coverage Optimizer guide — setting up your team and moves, what OHKO/2HKO reach means, how the usage weighting works, and how to choose between candidate moves.
• EV Optimizer guide — turning goals like "survive Flutter Mane's Moonblast" into benchmarks, solving for a spread, and fine-tuning the result.

Reference pages

• Glossary — plain-English definitions of the VGC and statistics terms used across the suite (win rate, lift, OHKO, EVs, Best-of-3, regulation, and more).
• FAQ — how fresh the data is, which formats are covered, why numbers here can differ from other sites, and how to report something that looks wrong.
• About — where the data comes from and how the statistics are computed.

One honest note before you start

Data narrows your choices; it does not make them for you. Most VGC metagames sit near equilibrium, so real, durable edges tend to be a few percentage points — the tools are built to find those points and to show you the sample size behind every claim. A suggestion backed by 300 games deserves more trust than one backed by 15, and both deserve testing in your own practice games before they go to a tournament.