西瓜 — CS2 Stats

76561198070274360[U:1:110008632]✓ No bans

1,558Tracked matches54%Win rate2024Tracked since
CSDB Rating5.1 DevelopingClutch Specialist
WingmanMaster Guardian I
Ladder ranks via Leetify

Performance scores

Aim50
Positioning53
Utility49

0–100 skill scores via Leetify.

Recent form

HOT44–42–14Last 10044%Win rateWLWWWWWLWW

Last 10 vs previous 10: +50pp win rate · −0.01 avg rating · +0.4pp headshot accuracy · −23ms reaction

Win rate up 50pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (−0.01), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 4–1 · 80% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 14%
  • Avg reaction 586ms

Last 10

  • 8–2 · 80% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 14%
  • Avg reaction 577ms

Last 20

  • 11–5–4 · 55% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 14%
  • Avg reaction 588ms

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: Clutch Specialist — Late-round 1vX conversion stands above the rest of this profile (+4.6 against its own average).

Aim5.0
Utility4.9
Positioning5.3
Opening Duels1.4
Clutch10.0

Reliable in 1v1s

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

iM

Plays most like iM 80% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower opening-duel success; 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

Reaction time. 578ms 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

Aim5.0
Positioning5.3
Utility4.9
Mechanics5.3
Opening Duels3.3
Win Impact6.3

Composite 5.1/10 (Developing), 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 rating-0.02−0.01
first ⅓ avg -0.01 → last ⅓ avg -0.02
Reaction time579ms−5ms
first ⅓ avg 583ms → last ⅓ avg 579ms
Headshot accuracy14.0%−1.6%
first ⅓ avg 15.6% → last ⅓ avg 14.0%

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

0.10Best match rating · 7–13 · inferno, 16 Sept →
32%Best headshot accuracy · 10–13 · vertigo, 2 Sept →
414msFastest reaction time · 12–12 · nuke, 2 Sept →
13–1Biggest win · vertigo, 28 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
4–5In matches decided by ≤2 rounds
1Overtime games

Map breakdown

vertigoBest map · 55% over 22infernoWeakest map · 33% over 24
MapGradePlayedRecordWin rateAvg rating
infernoD248–1633%-0.02
vertigoA2212–1055%-0.01
nukeB2111–1052%-0.02
mirageC167–944%-0.01
anubisB115–645%-0.02
cache—30–30%-0.00
train—10–10%-0.03
dust2—10–10%-0.01
overpass—11–0100%-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (33% over 24). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

6Matches
83%Win rate
1.47Avg K/D
69.1ADR
42%Headshot %

Clutches & streaks

100%1v1 clutch win
0%1v2 clutch win
3Longest win streak

Recent Faceit resultsWLWWW

MapMatchesWin rateAvg K/DAvg kills
Mirage250%2.2613.0
Nuke2100%1.0419.5
Anubis1100%1.7319.0
Inferno1100%0.479.0

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.

14.0%Headshot accuracy
36.4%Accuracy (enemy spotted)
35.3%Spray accuracy
73.8%Counter-strafing
13.5°Preaim
578msReaction time
47.3%T opening success
39.2%CT opening success
0.45Enemies flashed / flash
2.9%Flash assists
9.51HE damage / grenade
5.45Flashes / 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

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 13.5285° — above the 12° mark we flag

    Aim Training →
  2. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 14.0361% — below the 15% mark we flag

    Aim Training →
  3. 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 0.4514 — below the 0.5 mark we flag

    Grenade Lineups →
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.

33% win rate across 24 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–70.0117%4 Nov →
vertigo11–130.0519%4 Nov →
anubis13–10-0.089%4 Nov →
nuke13–7-0.0711%4 Nov →
mirage13–9-0.0015%28 Oct →
vertigo13–90.0813%28 Oct →
inferno13–8-0.0111%28 Oct →
nuke7–13-0.0619%28 Oct →
inferno13–8-0.0612%21 Oct →
nuke13–100.0217%21 Oct →
vertigo9–13-0.0413%21 Oct →
mirage10–13-0.0811%21 Oct →
vertigo13–9-0.0111%14 Oct →
mirage11–130.0421%14 Oct →
nuke12–120.008%14 Oct →
nuke12–12-0.0224%12 Oct →
mirage13–7-0.0113%12 Oct →
inferno12–120.0016%12 Oct →
vertigo12–120.036%12 Oct →
vertigo5–10.0217%11 Oct →
anubis13–8-0.0213%11 Oct →
nuke13–10-0.0220%11 Oct →
inferno9–13-0.0424%11 Oct →
inferno11–13-0.0514%9 Oct →
vertigo13–30.0817%9 Oct →
nuke9–13-0.069%9 Oct →
nuke9–13-0.029%7 Oct →
train7–13-0.035%7 Oct →
inferno5–13-0.086%7 Oct →
inferno5–13-0.0624%30 Sept →
vertigo13–9-0.117%30 Sept →
anubis13–8-0.0216%30 Sept →
mirage13–30.0816%30 Sept →
anubis8–13-0.1022%28 Sept →
nuke13–7-0.0123%28 Sept →
inferno8–13-0.0216%28 Sept →
vertigo13–10.0913%28 Sept →
anubis10–13-0.0514%26 Sept →
inferno12–12-0.0312%26 Sept →
nuke13–8-0.0413%26 Sept →
vertigo13–2-0.0113%26 Sept →
vertigo13–9-0.077%25 Sept →
nuke13–9-0.0511%25 Sept →
inferno13–70.0311%25 Sept →
mirage13–9-0.0510%25 Sept →
vertigo11–13-0.0219%23 Sept →
inferno13–80.0413%23 Sept →
mirage8–13-0.0717%23 Sept →
dust26–13-0.019%23 Sept →
inferno12–12-0.0219%21 Sept →
nuke5–13-0.129%21 Sept →
vertigo12–12-0.1019%21 Sept →
anubis6–13-0.0312%21 Sept →
vertigo7–13-0.068%19 Sept →
anubis13–80.0221%19 Sept →
nuke13–110.0118%19 Sept →
inferno13–50.0319%19 Sept →
nuke3–130.0411%17 Sept →
vertigo2–13-0.0110%17 Sept →
inferno13–110.0117%17 Sept →
vertigo10–130.0214%16 Sept →
inferno7–130.1022%16 Sept →
anubis7–13-0.095%16 Sept →
mirage5–13-0.0514%16 Sept →
inferno9–13-0.066%9 Sept →
anubis12–120.0210%9 Sept →
mirage8–13-0.0418%9 Sept →
overpass13–5-0.018%9 Sept →
inferno8–13-0.085%6 Sept →
mirage8–130.0013%6 Sept →
nuke13–80.0621%6 Sept →
vertigo13–11-0.0317%6 Sept →
nuke8–80.0016%6 Sept →
cache3–130.0219%4 Sept →
nuke6–13-0.032%4 Sept →
mirage13–9-0.077%4 Sept →
inferno16–130.0116%4 Sept →
inferno4–13-0.0515%2 Sept →
nuke12–120.0110%2 Sept →
vertigo10–13-0.0332%2 Sept →
cache6–130.0417%2 Sept →
mirage12–120.0514%2 Sept →
mirage7–13-0.0215%1 Sept →
nuke13–8-0.0414%1 Sept →
inferno6–13-0.0320%1 Sept →
anubis10–130.0125%1 Sept →
vertigo13–4-0.017%29 Aug →
inferno12–120.0426%29 Aug →
mirage13–60.0314%29 Aug →
nuke13–50.0110%29 Aug →
inferno12–12-0.067%27 Aug →
nuke5–7-0.0323%27 Aug →
vertigo2–13-0.0621%27 Aug →
anubis13–70.1016%27 Aug →
cache6–13-0.0613%27 Aug →
mirage11–130.0225%27 Aug →
vertigo13–8-0.0020%25 Aug →
mirage13–7-0.0112%25 Aug →
vertigo4–10.0418%25 Aug →
inferno12–12-0.0619%25 Aug →

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 →

This profile is built from public Steam data. If it is yours, you can remove it, or delete your CSDB account.