Gaijin determines BR changes based on aggregate performance statistics across all players. This methodology has a critical flaw: it doesn’t separate player skill tiers.
The Leopard 1A5 Example:
The Leopard 1A5 at 9.3 BR is being proposed for a buff to 9.0. I say this as someone who genuinely loves these vehicles. I own handmade models of them. This isn’t competitive frustration. It’s concern that a vehicle I care about is being misrepresented by flawed data.
Here’s what those statistics don’t show:
- Experienced players perform excellently with Leopard 1A5 because they understand its playstyle: long range sniping, mobility-based flanking, avoiding direct brawling
- Inexperienced players consistently misuse it as a brawler, dying repeatedly to vehicles it was never designed to fight head-on
- The aggregate stat combines both groups, producing misleading “poor performance” data
The Real Issue
War Thunder’s player population includes:
- Veterans who understand vehicle-specific playstyles
- Players who skipped the learning curve through premium vehicles
- New players who haven’t developed playstyle awareness yet
- Players who watched a 2-minute YouTube video on how Leopard tanks actually work vs. those who haven’t
When a Leopard 1A5 player uses it as a brawler against T-72s instead of a long-range sniper, the resulting death isn’t a vehicle performance issue. It’s a playstyle issue.
Gaijin’s statistics can’t distinguish between these two scenarios.
As someone with a background in sociology and data analysis, the misuse of aggregate statistics without controlling for skill variables is a well-documented methodological flaw. It produces misleading conclusions regardless of the field it’s applied to. War Thunder’s BR decisions are no exception
The Cascade Effect
This creates a predictable and documented cycle:
- Aggregate stats show poor performance (due to misuse)
- Gaijin interprets this as vehicle underperforming
- BR buffed to lower bracket
- Skilled players immediately exploit the now-undertiered vehicle
- Gaijin panics and reverses or overcompensates
- Russian/other nation vehicles get compensatory BR changes
- The whole BR ecosystem shifts based on one flawed decision
We’ve seen this pattern repeatedly: vehicles get buffed, get exploited, get nerfed, trigger compensatory changes elsewhere. The root cause is always the same: aggregate data without skill filtering.
What Gaijin Already Has
Gaijin stores detailed player statistics in profiles: K/D ratios, win rates, vehicle-specific performance, match scores. The data to separate skilled from unskilled players already exists. It’s allegedly just not being applied to BR decisions.
Why This Matters
Bad BR decisions based on flawed methodology affect everyone:
- Skilled players get their vehicles undertiered then overtiered repeatedly
- New players face vehicles that were buffed for wrong reasons
- Other nations get compensatory changes based on flawed premises
- The BR ecosystem becomes increasingly unstable
I may submit this as a formal Suggestion. Community discussion and additional examples welcome.
(Please read the post fully before answering)
- Yes, separate all player tiers for BR evaluation
- Yes, but only for vehicles with complex playstyle requirements
- Yes, but use different tier criteria (explain below)
- No, aggregate stats are sufficient (please explain)
- I don’t know / I don’t care