WolverBean

WolverBean — CS2 Stats

GB76561198033905702[U:1:73639974]Steam profile ↗✓ No bans

260Tracked matches70%Win rate2021Tracked since
893Hours in CS
CSDB Rating7.1 StrongPositional Player
WingmanThe Global Elite
Ladder ranks via Leetify

Performance scores

Aim83
Positioning60
Utility52

0–100 skill scores via Leetify.

Recent form

STEADY67–32–1Last 10067%Win rateWWLLLWWWWL

Last 10 vs previous 10: −10pp win rate · −0.02 avg rating · −3.7pp headshot accuracy · +50ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 2–3 · 40% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 18%
  • Avg reaction 700ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 20%
  • Avg reaction 642ms

Last 20

  • 13–6–1 · 65% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 22%
  • Avg reaction 617ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: Positional Player — Positioning stands above the rest of this profile (+1.3 against its own average).

Aim8.3
Utility5.2
Positioning6.0
Opening Duels3.9
Clutch3.6

Excellent counter-strafingStrong CT-side opener

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

jL

Plays most like jL 97% playstyle similarity

Most alike: utility contribution, aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 56% on CT to 33% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 594ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim8.3
Positioning6.0
Utility5.2
Mechanics8.7
Opening Duels3.6
Win Impact10.0

Composite 7.1/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.02
first ⅓ avg 0.04 → last ⅓ avg 0.01
Reaction time607ms+0ms
first ⅓ avg 607ms → last ⅓ avg 607ms
Headshot accuracy21.7%+0.9%
first ⅓ avg 20.8% → last ⅓ avg 21.7%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.13Best match rating · 13–2 · inferno, 22 Oct →
44%Best headshot accuracy · 13–4 · dust2, 21 Nov →
406msFastest reaction time · 13–5 · mirage, 18 Feb →
13–1Biggest win · inferno, 25 Mar →

Across the last 100 tracked matches.

Highlights

8Longest win streak
W2Current streak
13–4In matches decided by ≤2 rounds
20Overtime games

Map breakdown

nukeBest map · 87% over 15anubisWeakest map · 55% over 11
MapGradePlayedRecordWin rateAvg rating
infernoS2920–969%0.02
nukeS1513–287%0.02
ancientA138–562%0.01
anubisA116–555%0.01
mirageA117–464%0.01
dust2A106–460%0.02
overpassS75–271%0.03
cache—21–150%0.02
office—10–10%0.02
train—11–0100%0.12

Across the last 100 tracked matches.

Anubis is currently your weakest sufficiently-sampled map (55% over 11). Start with the 6 essential Anubis lineups, review the callouts, then spin up a practice server.

Lifetime stats

43,810Lifetime kills
1.26K/D · Top 25% of tracked players
2,026Matches
47.6%Match win rate · Top 50% of tracked players
42.4%Headshot %
17.9%Shot accuracy · Top 10% of tracked players
5,638MVPs
893Hours (in match)
1,157Bombs planted
585Bombs defused

Most-used weapons

Lifetime map wins

4,285inferno
3,649dust2
2,003nuke
699office
574train
404cbble
123vertigo
31lake

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

279Matches
60%Win rate
1.18Avg K/D
89.0ADR
50%Headshot %

Clutches & streaks

38%1v1 clutch win
17%1v2 clutch win
8Longest win streak

Recent Faceit resultsWWLWW

MapMatchesWin rateAvg K/DAvg kills
Inferno4576%1.3618.8
Dust23456%1.1116.5
Nuke3168%1.1816.4
Mirage2832%1.1117.8
Ancient2458%1.1418.1
Overpass1060%1.1315.9
Anubis1060%1.2917.9
Train540%1.6122.2

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

22.1%Headshot accuracy
35.2%Accuracy (enemy spotted)
35.6%Spray accuracy
89.3%Counter-strafing
8.2°Preaim
594msReaction time
32.5%T opening success
56.0%CT opening success
0.62Enemies flashed / flash
4.1%Flash assists
11.99HE damage / grenade
7.02Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 32.5127% — below the 40% mark we flag

Recent matches

MapScoreRatingHS%Date
anubis13–11-0.0218%22 Jun →
cache13–30.0120%12 May →
nuke5–13-0.0827%7 May →
inferno5–13-0.0810%18 Mar →
anubis8–13-0.0214%17 Mar →
inferno13–4-0.0023%15 Mar →
anubis13–110.0115%15 Mar →
inferno13–70.0819%12 Mar →
dust216–120.0630%27 Nov →
ancient10–13-0.0028%27 Nov →
dust213–40.1244%21 Nov →
mirage13–60.0521%15 Nov →
ancient13–110.0621%13 Nov →
inferno13–40.0634%13 Nov →
inferno19–17-0.0020%12 Nov →
ancient8–13-0.0219%12 Nov →
inferno8–8-0.0212%11 Nov →
nuke16–14-0.0223%10 Nov →
inferno7–13-0.0314%4 Nov →
nuke13–7-0.0032%3 Nov →
nuke13–70.0637%28 Oct →
inferno13–20.1320%22 Oct →
overpass13–80.0131%20 Oct →
inferno11–130.0716%15 Oct →
ancient13–50.1018%15 Oct →
inferno13–90.0527%15 Oct →
dust29–13-0.0420%15 Oct →
nuke16–14-0.0117%14 Oct →
mirage7–13-0.0329%14 Oct →
inferno16–13-0.0414%12 Oct →
ancient13–10-0.0116%12 Oct →
nuke16–12-0.0412%11 Oct →
dust216–19-0.0019%11 Oct →
overpass13–6-0.0113%11 Oct →
inferno13–100.0122%11 Oct →
nuke13–40.0018%10 Oct →
inferno13–11-0.0314%10 Oct →
overpass13–60.1126%10 Oct →
ancient16–130.0221%6 Oct →
overpass10–130.0024%6 Oct →
inferno13–60.0618%6 Oct →
inferno6–90.019%6 Oct →
inferno13–110.0313%4 Oct →
mirage13–6-0.0013%4 Oct →
ancient11–0-0.0320%4 Oct →
dust213–20.0216%2 Oct →
ancient13–80.0130%2 Oct →
mirage9–13-0.0216%2 Oct →
dust214–160.0135%2 Oct →
inferno13–110.0023%2 Oct →
mirage13–9-0.029%2 Oct →
overpass10–13-0.0220%2 Oct →
ancient13–7-0.027%24 Jun →
anubis13–9-0.0223%4 Apr →
anubis13–160.0118%2 Apr →
inferno13–8-0.0114%1 Apr →
inferno11–130.0213%1 Apr →
ancient8–13-0.0120%1 Apr →
mirage7–13-0.100%31 Mar →
nuke13–80.0726%31 Mar →
anubis10–130.0522%30 Mar →
nuke13–40.0516%30 Mar →
ancient7–130.0534%30 Mar →
inferno13–90.0625%30 Mar →
nuke6–13-0.019%30 Mar →
anubis6–13-0.0117%29 Mar →
anubis8–13-0.0216%29 Mar →
anubis13–30.0120%29 Mar →
nuke13–60.0125%29 Mar →
ancient16–19-0.0213%28 Mar →
inferno11–130.0316%28 Mar →
nuke16–140.0821%28 Mar →
nuke13–80.0715%25 Mar →
inferno13–10.1027%25 Mar →
anubis13–110.0813%25 Mar →
inferno13–110.0516%18 Mar →
dust213–80.0315%18 Mar →
cache19–220.0220%7 Mar →
mirage10–13-0.0810%6 Mar →
inferno13–80.0727%6 Mar →
inferno13–30.0424%5 Mar →
dust213–80.0212%5 Mar →
anubis13–60.0331%5 Mar →
nuke13–10.0535%4 Mar →
mirage13–30.0914%4 Mar →
dust213–90.0025%4 Mar →
ancient13–50.0122%4 Mar →
inferno13–160.0325%18 Feb →
office10–130.0227%20 Jan →
train13–100.1222%20 Nov →
mirage13–50.0641%18 Feb →
overpass13–100.0931%8 Feb →
inferno16–110.0022%5 Jun →
inferno7–16-0.0121%28 Apr →
inferno9–6-0.038%8 Apr →
mirage9–00.087%2 Mar →
nuke16–140.0420%25 Feb →
dust22–16-0.0525%19 Mar →
overpass16–60.0311%19 Sept →
mirage16–130.0827%15 Sept →

Match data via Leetify.

Recent teammates

Milestones

2K ELO100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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