slicer

slicer — CS2 Stats

IS76561198052051581[U:1:91785853]Steam profile ↗✓ No bans

756Tracked matches53%Win rate2020Tracked since
808Hours in CS
CSDB Rating5.0 DevelopingPositional Player
Premier CS Rating12,617Blue band · top ~41% of ranked players (population est.)
WingmanDistinguished Master Guardian
Ladder ranks via Leetify

How this compares with the same rank

Median values for Blue band among CSDB-tracked players (n=21,222), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerBlue band medianPurple band medianvs Purple band
Headshot rate42.0%42.0%44.4%2.4% short
Shot accuracy12.8%9.6%11.9%above
Kill/death ratio1.160.981.03above
Match win rate45.6%43.8%45.2%meets

This profile matches the typical Purple band player on 3 of 4 comparable metrics.

Widest gap: Headshot rate. That is the metric furthest from the Purple band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

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CSDB.GGslicerPREMIER12,617 · Blue bandcsdb.gg/stats

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Performance scores

Aim51
Positioning58
Utility45

0–100 skill scores via Leetify.

Recent form

STEADY54–46Last 10054%Win rateLLWWWWLWLL

Last 10 vs previous 10: −10pp win rate · −0.05 avg rating · +2.2pp headshot accuracy · −57ms 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 -0.02
  • Avg headshot accuracy 13%
  • Avg reaction 561ms

Last 10

  • 5–5 · 50% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 14%
  • Avg reaction 554ms

Last 20

  • 11–9 · 55% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 13%
  • Avg reaction 583ms

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).

Aim5.1
Utility4.5
Positioning5.8
Opening Duels4.2
Clutch3.4

Effective flashes

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 84% 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

Strengths

Flashes. 0.79 enemies blinded per flash — utility that consistently lands.

Areas to improve

Reaction time. 588ms 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

Aim5.1
Positioning5.8
Utility4.5
Mechanics6.3
Opening Duels3.3
Win Impact6.1

Composite 5.0/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01−0.00
first ⅓ avg 0.01 → last ⅓ avg 0.01
Reaction time592ms−8ms
first ⅓ avg 601ms → last ⅓ avg 592ms
Headshot accuracy12.1%−1.8%
first ⅓ avg 13.9% → last ⅓ avg 12.1%

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 · 10–13 · nuke, 24 Jan →
29%Best headshot accuracy · 13–2 · nuke, 16 Oct →
438msFastest reaction time · 13–8 · nuke, 27 Sept →
13–1Biggest win · ancient, 21 Jan →

Across the last 100 tracked matches.

Highlights

5Longest win streak
L2Current streak
9–11In matches decided by ≤2 rounds
14Overtime games

Map breakdown

mirageBest map · 69% over 13infernoWeakest map · 35% over 17
MapGradePlayedRecordWin rateAvg rating
dust2A2113–862%0.01
nukeA1811–761%0.05
infernoC176–1135%0.02
mirageS139–469%0.03
ancientB137–654%0.04
anubisC73–443%-0.00
train—42–250%-0.01
overpass—32–167%-0.01
cache—20–20%-0.03
vertigo—21–150%-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (35% over 17). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

34,228Lifetime kills
1.16K/D · Top 25% of Blue band
1,475Matches
45.6%Match win rate · Top 50% of Blue band
42.0%Headshot %
12.8%Shot accuracy · Top 50% of Blue band
4,089MVPs
808Hours (in match)
1,701Bombs planted
676Bombs defused

Most-used weapons

Lifetime map wins

3,531inferno
3,193nuke
3,131dust2
774train
370vertigo
41cbble
20ar_shoots
18ar_baggage

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

Faceit stats

Combat

633Matches
50%Win rate
1.09Avg K/D
79.9ADR
37%Headshot %

Clutches & streaks

37%1v1 clutch win
23%1v2 clutch win
7Longest win streak

Recent Faceit resultsWLWWL

MapMatchesWin rateAvg K/DAvg kills
Dust29852%1.0014.8
Inferno7841%1.0315.2
Ancient6343%1.0415.4
Nuke6265%1.2015.4
Mirage5343%1.0715.6
Anubis2650%1.0616.4
Train1250%0.9316.8
Overpass580%1.0813.2

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.

12.4%Headshot accuracy
33.0%Accuracy (enemy spotted)
33.8%Spray accuracy
78.4%Counter-strafing
11.4°Preaim
588msReaction time
38.6%T opening success
47.5%CT opening success
0.79Enemies flashed / flash
7.9%Flash assists
10.69HE damage / grenade
13.59Flashes / 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. 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 12.4266% — below the 15% mark we flag

    Aim Training →
  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 38.5549% — below the 40% mark we flag

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.

35% win rate across 17 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
mirage4–13-0.0618%19 May →
cache5–13-0.0422%8 May →
mirage13–70.0311%8 May →
inferno13–9-0.024%8 May →
dust213–9-0.0011%4 May →
mirage13–90.0110%4 May →
cache10–13-0.0112%4 May →
ancient19–16-0.0316%28 Mar →
overpass11–13-0.0014%28 Mar →
nuke14–160.0018%2 Jan →
overpass13–40.0315%28 Jul →
dust216–120.0610%28 Jul →
mirage11–130.0610%19 Jun →
nuke13–30.0914%18 Jun →
inferno11–13-0.027%18 Jun →
nuke13–9-0.028%18 Jun →
dust213–80.1211%17 Jun →
ancient9–130.058%17 Jun →
dust213–9-0.0114%17 Jun →
inferno9–130.0518%17 Jun →
inferno6–13-0.0518%1 May →
inferno11–13-0.0311%21 Apr →
nuke13–90.0313%21 Apr →
dust27–13-0.0513%26 Mar →
ancient13–80.046%26 Mar →
anubis28–25-0.039%22 Mar →
inferno11–13-0.0112%21 Mar →
train13–9-0.037%18 Mar →
dust219–170.0419%14 Mar →
nuke14–160.0314%2 Mar →
ancient13–6-0.008%22 Feb →
inferno11–13-0.0214%21 Feb →
nuke13–60.053%16 Feb →
inferno10–13-0.0510%8 Feb →
train6–130.026%8 Feb →
inferno5–130.029%7 Feb →
nuke10–130.2213%24 Jan →
mirage13–90.169%24 Jan →
inferno13–90.2013%24 Jan →
nuke6–130.1411%24 Jan →
dust213–50.1714%24 Jan →
inferno13–80.1313%24 Jan →
train13–4-0.086%21 Jan →
overpass13–7-0.050%21 Jan →
ancient13–10.0919%21 Jan →
anubis8–13-0.0210%16 Jan →
mirage0–13-0.0722%16 Jan →
dust213–8-0.0111%16 Jan →
mirage13–90.0319%13 Jan →
anubis10–13-0.0116%1 Jan →
ancient11–130.0514%27 Dec →
dust213–100.0419%26 Dec →
anubis10–13-0.0214%22 Nov →
inferno8–130.0411%18 Nov →
anubis13–90.0412%18 Nov →
train10–130.0421%18 Nov →
nuke9–13-0.0019%10 Nov →
anubis9–130.0411%9 Nov →
mirage13–30.0211%23 Oct →
dust216–14-0.0216%23 Oct →
inferno13–30.129%23 Oct →
ancient13–80.1113%23 Oct →
dust218–22-0.053%19 Oct →
mirage13–160.037%16 Oct →
ancient13–80.0819%16 Oct →
nuke13–20.1229%16 Oct →
mirage17–130.0613%15 Oct →
ancient3–13-0.0223%14 Oct →
nuke13–11-0.0112%14 Oct →
dust25–130.058%14 Oct →
dust211–130.0415%6 Oct →
inferno9–130.0712%6 Oct →
nuke13–50.0311%6 Oct →
ancient11–130.0711%6 Oct →
mirage13–80.0916%30 Sept →
nuke16–140.0411%30 Sept →
dust213–11-0.0414%30 Sept →
dust213–100.0213%27 Sept →
ancient10–130.0412%27 Sept →
nuke13–8-0.0114%27 Sept →
nuke12–16-0.0318%27 Sept →
inferno13–11-0.0224%26 Sept →
dust27–130.0519%26 Sept →
dust213–11-0.0013%25 Sept →
nuke4–13-0.0811%25 Sept →
inferno6–13-0.037%25 Sept →
dust210–13-0.0412%24 Sept →
mirage19–160.0317%24 Sept →
inferno13–90.0318%23 Sept →
ancient8–13-0.0311%23 Sept →
dust25–13-0.0621%23 Sept →
anubis13–7-0.0112%20 Sept →
dust23–13-0.0412%20 Sept →
nuke13–40.1718%20 Sept →
nuke13–10.0911%18 Sept →
ancient13–110.0211%18 Sept →
dust213–11-0.0826%18 Sept →
vertigo8–13-0.0112%16 Sept →
vertigo16–13-0.038%16 Sept →
mirage13–100.0111%29 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

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