By **Darkspoon** · VGC player since 2018 · 1500+ rated on Showdown · Top 32 at 3 Regional Championships
I've been reading tier lists for competitive Pokémon since 2015, and the thing that always frustrated me was the lack of transparency. A list appears, Pokémon are ranked S through D, and nobody explains what the ranking actually measures.
When I started building ChampionsVGC, I promised myself we'd do it differently. Every number on this site has a methodology behind it, and this page explains exactly what that methodology is.
Understanding how tier lists work helps you use ANY tier list more effectively, including the ones on Victory Road, Pokémon Showdown, and tournament coverage sites. The better you understand the data, the better you can use it to build winning teams.
Where the Base Data Comes From
The foundation of our data pipeline is community-maintained databases that reflect how the game actually works.
### Base Stats, Moves, and Types
All Pokémon base stats, move data, type matchups, and ability descriptions are normalized from **PokéAPI** and **Pokémon Showdown's open dex**. These are the authoritative sources for how the game mechanics function — they reflect the actual damage formulas, speed calculations, and type interactions that determine competitive outcomes.
This part of our data is close to ground truth. When we say Incineroar has base 60 Speed, that's not an editorial judgment — it's a fact from the game data.
### Competitive Context
The competitive layer — usage rates, win rates, tier placements — is where editorial judgment enters. ChampionsVGC is not a tournament operator. We don't run events or collect team sheets directly. Instead, we analyze publicly available data from multiple sources:
- **Tournament results** from Play! Pokémon events and regional organizers
- **Ladder data** from Pokémon Showdown and in-game ranked battles
- **Community analysis** from competitive players, coaches, and content creators
- **Meta trends** observed through team composition patterns across events
We synthesize these sources into estimated figures, not exact measurements. When you see "60% usage" on our site, that's our estimate of how often a Pokémon appears on teams within the modeled metagame — not a precise count from a single dataset.
How We Estimate Usage Rate
### What Usage Rate Measures
Our usage rate estimates how often a Pokémon appears on competitive teams in the current regulation. It's informed by observed team sheets from tournaments, ladder trends, and format context. Think of it as a directional signal: "this Pokémon shows up a lot" vs. "this Pokémon rarely shows up."
### What Usage Rate Doesn't Measure
Usage rate does NOT measure how good a Pokémon is. A Pokémon can have high usage because it's popular, not because it's powerful. Conversely, a Pokémon can have low usage because it's niche, not because it's weak.
Example: Incineroar has ~60% usage. That doesn't mean Incineroar is the "best" Pokémon — it means Incineroar is the most commonly chosen support because it fits almost every team structure. The "best" Pokémon might be Calyrex-Shadow, which has lower usage (~38%) because it's restricted and teams can only bring one restricted Pokémon.
### How We Calculate It
1. **Collect team data** from available tournament results and ladder snapshots
2. **Normalize the data** to account for differences in sample size and format
3. **Apply editorial weighting** to give more importance to recent tournament results
4. **Generate an estimated percentage** that represents the Pokémon's prevalence
The result is a directional indicator, not a precise measurement.
### The Confidence Problem
Every estimation has uncertainty. Our usage rates are more confident for Pokémon with very high or very low usage. The middle range is where uncertainty is highest — a Pokémon at 15% usage might actually be at 12% or 18% depending on which tournaments you include.
We could publish confidence intervals, but that would make the numbers harder to read without adding much practical value. Instead, we focus on the relative ordering.
How We Estimate Win Rate
### What Win Rate Measures
Our estimated win rate reflects how often a Pokémon tends to perform well across observed matchups. A Pokémon showing 55% win rate is trending as more consistently rewarded than one showing 48%.
### What Win Rate Doesn't Measure
Win rate does NOT predict your personal results. It's influenced by player skill, team composition, matchup variance, and format context.
### The Causation Trap
The biggest mistake people make with win rate is assuming causation. "Flutter Mane has 54% win rate, therefore Flutter Mane causes wins." That's wrong. Flutter Mane might have a high win rate because the best players tend to use it, not because Flutter Mane itself is overpowered.
### How We Calculate It
1. **Analyze match outcomes** from available tournament and ladder data
2. **Control for team composition** — isolate the Pokémon's contribution
3. **Apply recency weighting** — recent matches matter more
4. **Compare against a baseline** — the format average
How Tier Placement Combines Everything
Tier placement is where editorial judgment plays the biggest role. We don't just rank by usage or win rate — we combine multiple factors.
### The Factors We Consider
1. **Estimated usage** — How often does this Pokémon appear?
2. **Estimated win rate** — How well does it perform?
3. **Top Cut presence** — How often in tournament Top Cuts?
4. **Role uniqueness** — Does it fill a role few others can?
5. **Format influence** — Does it shape how teams are built?
### The Editorial Decision
A Pokémon can sit in a high tier without high usage if it fills a role few others do — and a heavily-used Pokémon isn't automatically top-tier if that usage doesn't translate into results.
Example: Amoonguss has moderate usage (~20%) but sits in A-tier because it's the primary enabler of Trick Room teams. Without Amoonguss, Trick Room as an archetype doesn't function. That role uniqueness elevates its tier placement beyond what usage alone would suggest.
### The Tier Definitions
**S-Tier:** Format-defining. These Pokémon shape how teams are built. You need a plan for these.
**A-Tier:** Excellent and commonly used. Strong in most team compositions.
**B-Tier:** Good and viable. Used in specific archetypes or as tech choices.
**C-Tier:** Situational. Can work in specific matchups but isn't reliable for general play.
**D-Tier:** Niche or underperforming. May have theoretical value but struggles in the current format.
What These Numbers Are — and Aren't
### What They Are
- Directional indicators of the current competitive landscape
- Trend estimates based on available data and editorial analysis
- Starting points for your own team building and testing
- Transparent assessments with published methodology
### What They Aren't
- Predictions of your personal results
- Exact measurements from a single authoritative source
- Guarantees of competitive success
- Permanent rankings — the meta evolves constantly
### The Honest Disclaimer
Every figure on ChampionsVGC is an estimate based on available data. Matchups are situational: team composition, player skill, and game state all matter more than any single tier placement. Use our tier list as a starting point for research, then test everything yourself with the [Damage Calculator](/en/damage-calculator), [Team Builder](/en/team-builder), and [Matchup Analyzer](/en/matchups).
The best tier list is the one you understand well enough to know when to ignore it.
How We Monitor and Update
### The Data Pipeline
ChampionsVGC runs a scheduled monitor that checks official sources, trusted community outlets, and our own internal datasets every 10 minutes. The pipeline detects changes, deduplicates entries, scores relevance, and generates editorial content only when a real novelty appears.
### Update Frequency
- **Usage rates:** Updated weekly based on latest tournament and ladder data
- **Win rates:** Updated weekly with recency weighting
- **Tier placements:** Reviewed each update cycle, may shift as the meta evolves
- **News articles:** Published as events happen, with editorial review
### The Feedback Loop
We monitor how our estimates compare against actual tournament results. If our usage rates consistently overestimate or underestimate, we adjust. This is an ongoing process.
How to Use This Information for Team Building
1. **Don't blindly copy S-Tier teams.** S-Tier Pokémon are popular, which means opponents have practice against them. Sometimes an A-Tier Pokémon that opponents are less familiar with is a better choice.
2. **Look at the ROLE, not just the tier.** If you need speed control, look at which Pokémon provide it — regardless of tier.
3. **Check the win rate trend, not just the current number.** A rising win rate might indicate an undervalued Pokémon.
4. **Use the tools.** The tier list tells you what's popular. The [Damage Calculator](/en/damage-calculator) tells you what works. The [Matchup Analyzer](/en/matchups) tells you what beats what.
5. **Test everything.** No tier list replaces hands-on testing. Build a team, play 20 games, and let results guide decisions.
Frequently Asked Questions
**Does ChampionsVGC track real tournament results directly?**
No — we don't operate tournaments. Our figures are estimates informed by observed team sheets, ladder trends, and format context.
**Why does the site keep saying "estimated"?**
Because it's accurate. We'd rather be clear these are directional trends than imply precision the data doesn't support.
**How often is the tier list updated?**
Usage and win rates update weekly. Tier placements reviewed each cycle. Major meta shifts trigger immediate reviews.
**What's the difference from other tier lists?**
Transparency. We publish our methodology and honestly state what numbers do and don't mean.
**Can I use this data in my own content?**
Yes, with attribution. Link back and note the source. Free for non-commercial use.