bumar-iwnl-

bumar-iwnl- — CS2 Stats

76561198325588809[U:1:365323081]Steam profile ↗✓ No bans

2,095Tracked matches63%Win rate2020Tracked since
8,037Hours in CS13Hrs last 2 wks
CSDB Rating7.4 StrongPositional Player
FaceitLevel 10 · 2,610 ELOTop 12.4% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGbumar-iwnl-FACEITLevel 10 · 2,610 ELOSTANDINGTop 12.4% of rankedcsdb.gg/stats

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Performance scores

Aim83
Positioning63
Utility50

0–100 skill scores via Leetify.

Recent form

STEADY69–31Last 10069%Win rateWLLWWLWWLW

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · −0.9pp headshot accuracy · −70ms 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

  • 3–2 · 60% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 20%
  • Avg reaction 547ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 23%
  • Avg reaction 570ms

Last 20

  • 13–7 · 65% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 23%
  • Avg reaction 606ms

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
Utility5.0
Positioning6.3
Opening Duels5.0
Clutch3.8

Excellent counter-strafing

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

donk

Plays most like donk 92% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower 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.

Reaction time. 626ms 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
Positioning6.3
Utility5.0
Mechanics8.8
Opening Duels4.5
Win Impact9.4

Composite 7.4/10 (Strong), a weighted mean of the bars with a small opposition adjustment (×1.02 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.03+0.01
first ⅓ avg 0.02 → last ⅓ avg 0.03
Reaction time627ms−26ms
first ⅓ avg 653ms → last ⅓ avg 627ms
Headshot accuracy23.1%+1.9%
first ⅓ avg 21.2% → last ⅓ avg 23.1%

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

0.24Best match rating · 13–7 · inferno, 28 Oct →
56%Best headshot accuracy · 2–10 · inferno, 23 Oct →
445msFastest reaction time · 13–7 · mirage, 1 Nov →
13–0Biggest win · inferno, 17 May →

Across the last 100 tracked matches.

Highlights

11Longest win streak
9–5In matches decided by ≤2 rounds
12Overtime games

Map breakdown

mirageBest map · 79% over 19infernoWeakest map · 45% over 11
MapGradePlayedRecordWin rateAvg rating
ancientA2214–864%0.03
mirageS1915–479%0.02
anubisS1712–571%0.03
infernoB115–645%0.03
nukeS107–370%0.07
dust2A95–456%0.02
overpass—44–0100%0.04
vertigo—33–0100%-0.01
train—32–167%-0.01
cache—22–0100%0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (45% over 11). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

243,994Lifetime kills
1.13K/D
7,187Matches
48.5%Match win rate
47.4%Headshot %
18.9%Shot accuracy
32,001MVPs
6,694Hours (in match)
6,021Bombs planted
3,442Bombs defused

Most-used weapons

AK-47110,400
AWP17,817
SCAR-204,202
Knife4,090
AUG3,493
FAMAS2,870

Lifetime map wins

12,412dust2
11,544inferno
3,382vertigo
2,926train
2,445nuke
1,864cbble
1,530office
1,167italy

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

Faceit stats

Combat

3,490Matches
52%Win rate
1.12Avg K/D
79.8ADR
45%Headshot %

Clutches & streaks

39%1v1 clutch win
23%1v2 clutch win
13Longest win streak

Recent Faceit resultsWWWLW

MapMatchesWin rateAvg K/DAvg kills
Mirage26155%1.1516.7
Anubis15650%1.1015.6
Ancient14756%1.1216.4
Vertigo6837%1.0515.7
Dust25345%1.0315.9
Inferno4349%1.2815.6
Nuke3145%1.1216.7
Overpass1258%1.1819.3

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.

23.2%Headshot accuracy
36.4%Accuracy (enemy spotted)
39.8%Spray accuracy
89.6%Counter-strafing
9.3°Preaim
626msReaction time
42.9%T opening success
53.3%CT opening success
0.64Enemies flashed / flash
6.3%Flash assists
7.01HE damage / grenade
12.30Flashes / match

Recommended for you

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

45% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
ancient13–90.0621%7 Nov →
ancient7–13-0.0117%13 Oct →
ancient4–13-0.0424%22 Sept →
anubis13–6-0.0219%22 Sept →
dust213–80.0220%22 Sept →
nuke9–13-0.0237%21 Sept →
ancient13–80.0220%1 Sept →
cache13–8-0.0118%1 Sept →
mirage8–13-0.0421%17 Aug →
ancient13–100.1230%15 Aug →
vertigo13–110.0129%11 Aug →
cache13–90.0920%17 May →
inferno13–00.1824%17 May →
overpass13–60.0622%21 Feb →
nuke13–5-0.0035%7 Feb →
overpass13–11-0.0618%25 Aug →
train13–10-0.0413%13 Aug →
dust22–13-0.0423%13 Aug →
inferno14–160.0031%8 Aug →
dust28–13-0.0322%4 Aug →
overpass11–20.1138%2 Aug →
mirage13–40.0421%2 Aug →
mirage13–30.0218%18 May →
mirage13–20.0716%26 Feb →
mirage11–130.0324%26 Feb →
anubis8–130.0817%23 Feb →
anubis13–90.0735%22 Feb →
dust213–20.1324%21 Feb →
dust29–130.0327%14 Jan →
mirage6–130.029%14 Jan →
ancient16–120.0219%7 Jan →
train13–100.0627%31 Dec →
nuke13–30.0023%15 Dec →
anubis7–13-0.0217%12 Dec →
train10–13-0.0633%16 Nov →
inferno16–19-0.0420%5 Nov →
ancient13–11-0.0226%4 Nov →
anubis13–60.1516%3 Nov →
dust28–13-0.0113%1 Nov →
mirage13–7-0.0218%1 Nov →
inferno0–6-0.0920%1 Nov →
anubis13–80.0328%30 Oct →
ancient13–4-0.0322%29 Oct →
nuke13–40.0932%29 Oct →
inferno13–70.2417%28 Oct →
nuke13–40.0927%28 Oct →
anubis13–20.1725%28 Oct →
anubis13–110.0418%28 Oct →
ancient13–10-0.0018%28 Oct →
ancient9–13-0.0217%23 Oct →
inferno2–10-0.0956%23 Oct →
ancient13–20.0315%21 Oct →
ancient13–00.136%21 Oct →
mirage13–80.0314%21 Oct →
dust213–10-0.0229%21 Oct →
mirage13–110.0820%20 Oct →
dust216–120.0325%20 Oct →
mirage13–8-0.0425%20 Oct →
mirage16–14-0.0114%19 Oct →
ancient13–80.0327%19 Oct →
inferno16–140.0420%19 Oct →
ancient16–130.0626%19 Oct →
mirage10–13-0.0218%18 Oct →
ancient13–20.1522%17 Oct →
anubis13–00.1418%16 Oct →
inferno16–19-0.0120%15 Oct →
nuke13–50.1736%15 Oct →
nuke13–16-0.0418%14 Oct →
mirage13–110.1228%14 Oct →
ancient8–13-0.0226%14 Oct →
mirage13–00.0615%14 Oct →
vertigo13–11-0.0227%12 Oct →
mirage16–13-0.0329%8 Oct →
anubis13–9-0.0324%7 Oct →
dust213–80.0318%5 Oct →
mirage13–10-0.0218%4 Oct →
anubis13–9-0.0215%2 Oct →
nuke14–160.0622%1 Oct →
mirage13–20.049%30 Sept →
anubis10–13-0.0026%25 Sept →
anubis10–130.1222%24 Sept →
ancient13–90.0934%23 Sept →
anubis13–70.0132%23 Sept →
vertigo13–3-0.0121%18 Sept →
inferno13–50.0527%18 Sept →
nuke13–40.0929%18 Sept →
ancient13–10.0717%14 Sept →
nuke13–20.2418%14 Sept →
anubis8–0-0.0117%14 Sept →
inferno13–80.0519%6 Jun →
ancient5–13-0.0123%12 May →
ancient11–13-0.1014%9 May →
anubis13–9-0.0425%7 May →
anubis6–13-0.0726%4 May →
inferno9–130.0327%4 May →
mirage13–80.0517%2 May →
mirage13–7-0.0211%26 Apr →
ancient11–130.0316%18 Apr →
ancient10–15-0.0013%17 Mar →
overpass13–100.0317%13 Mar →

Match data via Leetify.

Recent teammates

Milestones

Faceit Level 102.5K ELO1,000 Matches11-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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