hm hmm hmm hm

hm hmm hmm hm — CS2 Stats

FI76561198982181538[U:1:1021915810]Steam profile ↗✓ No bans

2,231Tracked matches50%Win rate2020Tracked since
CSDB Rating4.8 DevelopingPositional Player
CSDB Leaderboard#96800 of 232878 tracked
FaceitLevel 5 · 1,260 ELOTop 67.6% of ranked FACEIT players
Ladder ranks via Leetify
Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 50 days played since 13 Apr 2025. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 18,418 -2,010 13 Apr5 Jun · 10 days played
18,35920,428peak 20,42813 Apr5 Jun
20,428Peak Premier in tracked matches
1,260Highest Faceit ELO seen on CSDB
50Days played since 2025-04-13

Faceit ELO

  • At peak — 1,260
  • Next: Level 7 at 1,351 91 to go
  • Reached: Level 6 · Level 5 · Level 4 · Level 3

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

Share this profile

CSDB.GGhm hmm hmm hmFACEITLevel 5 · 1,260 ELOSTANDINGTop 67.6% of rankedPEAK ELO1,260csdb.gg/stats

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Performance scores

Aim67
Positioning54
Utility23

0–100 skill scores via Leetify.

Recent form

HOT46513Last 10046%Win rateLWWLWWWWWL

Last 10 vs previous 10: +40pp win rate · +0.03 avg rating · −1.5pp headshot accuracy · −24ms reaction

Win rate up 40pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

  • 32 · 60% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 23%
  • Avg reaction 623ms

Last 10

  • 73 · 70% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 21%
  • Avg reaction 616ms

Last 20

  • 1010 · 50% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 22%
  • Avg reaction 628ms

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 PlayerPositioning stands above the rest of this profile (+1.5 against its own average).

Aim6.7
Utility2.3
Positioning5.4
Opening Duels4.0
Clutch4.0

Limited utility dependence

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

s1mple

Plays most like s1mple 92% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower aim profile; lower opening-duel success.

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 49% on CT to 32% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 637ms 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

Aim6.7
Positioning5.4
Utility2.3
Mechanics7.5
Opening Duels2.6
Win Impact5.0

Composite 4.8/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.00+0.02
first ⅓ avg -0.02 → last ⅓ avg 0.00
Reaction time625ms−24ms
first ⅓ avg 649ms → last ⅓ avg 625ms
Headshot accuracy21.1%−1.4%
first ⅓ avg 22.5% → last ⅓ avg 21.1%

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

0.22Best match rating · 6–0 · mirage, 2 Mar
100%Best headshot accuracy · 0–3 · dust2, 10 Jan
453msFastest reaction time · 1–13 · dust2, 13 May
13–1Biggest win · overpass, 5 Jan

Across the last 100 tracked matches.

Highlights

5Longest win streak
69In matches decided by ≤2 rounds
11Overtime games

Map breakdown

anubisBest map · 83% over 6dust2Weakest map · 20% over 10
MapGradePlayedRecordWin rateAvg rating
mirageB35161946%-0.00
nukeA1610663%0.01
trainB115645%0.01
dust2D102820%-0.01
ancientD92722%-0.03
infernoD62433%-0.01
anubisS65183%0.01
overpass32167%0.06
cache21150%-0.01
vertigo110100%0.05
dogtown1010%0.08

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (20% over 10). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

428Matches
51%Win rate
0.88Avg K/D
79.5ADR
47%Headshot %

Clutches & streaks

40%1v1 clutch win
18%1v2 clutch win
10Longest win streak

Recent Faceit resultsWWWLW

MapMatchesWin rateAvg K/DAvg kills
Mirage12552%0.9314.4
Nuke5054%0.9415.6
Anubis2741%0.9014.2
Ancient2442%0.8413.0
Inferno2143%0.9515.0
Train1979%1.1717.5
Dust21942%1.0218.4
Cache425%0.7517.3

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.

19.8%Headshot accuracy
31.8%Accuracy (enemy spotted)
31.9%Spray accuracy
83.6%Counter-strafing
8.2°Preaim
637msReaction time
31.9%T opening success
49.2%CT opening success
0.42Enemies flashed / flash
1.2%Flash assists
7.56HE damage / grenade
1.21Flashes / 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. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4176 — below the 0.5 mark we flag

    Grenade Lineups
  2. 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 31.9411% — below the 40% mark we flag

Spend your practice time on Dust 2

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

20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategyDust 2 grenade lineups

Recent matches

MapScoreRatingHS%Date
nuke11–130.0227%13 Sept
nuke13–5-0.0223%12 Sept
mirage13–70.0815%2 Sept
inferno4–13-0.0137%2 Sept
nuke13–70.0415%1 Sept
mirage13–7-0.0311%31 Aug
mirage13–6-0.0114%19 Aug
nuke13–60.0424%14 Jul
anubis16–140.0122%8 Jun
mirage5–130.0229%8 Jun
ancient1–13-0.0635%8 Jun
inferno6–13-0.0518%4 Jun
mirage13–8-0.0115%3 Jun
ancient11–13-0.0219%26 May
inferno13–70.0127%13 May
cache13–90.0336%13 May
dust21–13-0.0622%13 May
dust23–130.0619%13 May
cache4–13-0.0424%13 May
mirage9–13-0.0315%13 May
mirage13–110.0218%11 May
mirage13–11-0.0114%27 Apr
vertigo13–80.0521%27 Apr
train13–6-0.0324%17 Apr
dust210–13-0.038%14 Apr
mirage14–160.0216%14 Apr
ancient16–13-0.0114%1 Apr
mirage7–130.0127%31 Mar
dust214–16-0.0112%30 Mar
ancient7–13-0.0113%18 Mar
anubis13–10-0.0111%18 Mar
mirage10–130.0123%17 Mar
dust213–20.0350%2 Mar
mirage6–00.220%2 Mar
overpass13–110.0324%2 Mar
mirage13–16-0.0424%18 Feb
nuke13–60.0925%4 Feb
anubis13–80.019%4 Feb
mirage13–16-0.0122%20 Jan
inferno8–12-0.0021%11 Jan
nuke9–13-0.0118%10 Jan
dust25–13-0.0325%10 Jan
dust20–3-0.00100%10 Jan
train14–16-0.0336%10 Jan
overpass11–13-0.0315%10 Jan
nuke16–120.0219%9 Jan
train13–100.0017%9 Jan
ancient2–13-0.0418%9 Jan
nuke13–8-0.0320%9 Jan
train13–60.0229%9 Jan
train7–130.0021%8 Jan
mirage13–30.0328%8 Jan
nuke12–16-0.0224%7 Jan
train13–10-0.0236%7 Jan
mirage16–13-0.0521%7 Jan
ancient13–40.0223%6 Jan
mirage13–30.0321%6 Jan
mirage11–13-0.057%5 Jan
mirage15–15-0.0419%5 Jan
nuke13–100.0415%5 Jan
nuke13–80.0730%5 Jan
inferno13–80.0124%5 Jan
dust213–50.0724%5 Jan
train12–120.0436%5 Jan
overpass13–10.1829%5 Jan
mirage12–120.0328%5 Jan
train13–40.1841%4 Jan
mirage13–50.0316%4 Jan
mirage6–130.0133%4 Jan
mirage10–13-0.0714%22 Nov
mirage9–130.0026%19 Nov
ancient10–13-0.0422%11 Nov
ancient7–13-0.0516%6 Jun
mirage13–50.0411%6 Jun
ancient6–13-0.0516%5 Jun
mirage13–8-0.0322%4 Jun
mirage10–13-0.0621%31 May
mirage11–13-0.0710%31 May
anubis13–110.0112%30 May
nuke8–13-0.0315%30 May
mirage6–13-0.0020%29 May
nuke7–13-0.0216%29 May
dust210–13-0.0017%29 May
mirage13–11-0.0613%29 May
dogtown7–90.0826%28 May
nuke13–9-0.0930%23 May
mirage10–13-0.0314%23 May
train3–13-0.0139%23 May
nuke4–13-0.0337%23 May
inferno2–13-0.0113%15 May
mirage13–90.0343%15 May
dust24–13-0.1132%9 May
mirage3–13-0.0429%7 May
anubis8–130.0118%7 May
nuke13–100.0229%7 May
train7–130.0044%5 May
train8–13-0.0438%3 May
mirage13–60.0117%3 May
anubis13–100.0126%3 May
mirage8–130.0112%13 Apr

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →