a_name

a_name — CS2 Stats

DE76561199216714073[U:1:1256448345]Steam profile ↗✓ No bans

567Tracked matches54%Win rate2024Tracked since
846Hours in CS4Hrs last 2 wks
CSDB Rating4.5 DevelopingPositional Player
WingmanSilver III
Ladder ranks via Leetify

Performance scores

Aim42
Positioning52
Utility29

0–100 skill scores via Leetify.

Recent form

STEADY39–51–10Last 10039%Win rateLTLLWWLLWW

Last 10 vs previous 10: −20pp win rate · +0.00 avg rating · −4.5pp headshot accuracy · +49ms reaction

Win rate down 20pp 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 (+0.00), so results shifted more than performance did.

Last 5 · 10 · 20 matches

Last 5

  • 1–3–1 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 11%
  • Avg reaction 620ms

Last 10

  • 4–5–1 · 40% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 11%
  • Avg reaction 642ms

Last 20

  • 10–8–2 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 13%
  • Avg reaction 618ms

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 (+1.6 against its own average).

Aim4.2
Utility2.9
Positioning5.2
Opening Duels2.8

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

jL

Plays most like jL 81% playstyle similarity

Most alike: positioning profile, utility contribution.

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. 654ms 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

Aim4.2
Positioning5.2
Utility2.9
Mechanics6.1
Opening Duels2.4
Win Impact6.2

Composite 4.5/10 (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-0.00+0.02
first ⅓ avg -0.02 → last ⅓ avg -0.00
Reaction time643ms−75ms
first ⅓ avg 717ms → last ⅓ avg 643ms
Headshot accuracy12.6%−0.1%
first ⅓ avg 12.8% → last ⅓ avg 12.6%

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

0.16Best match rating · 8–2 · office, 24 Sept →
32%Best headshot accuracy · 3–7 · anubis, 24 Dec →
430msFastest reaction time · 9–5 · inferno, 3 Sept →
13–2Biggest win · dust2, 28 Mar →

Across the last 100 tracked matches.

Highlights

6Longest win streak
8–7In matches decided by ≤2 rounds
2Overtime games

Map breakdown

mirageBest map · 56% over 9nukeWeakest map · 18% over 11
MapGradePlayedRecordWin rateAvg rating
dust2B3417–1750%0.00
officeD124–833%0.05
nukeD112–918%-0.05
ancientD93–633%-0.02
mirageA95–456%-0.02
anubisC83–538%0.01
infernoC52–340%-0.03
vertigoC52–340%-0.04
poseidon—20–20%-0.00
train—20–20%-0.03
cache—20–20%-0.01
golden—11–0100%-0.06

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (18% over 11). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

16,109Lifetime kills
0.73K/D
1,313Matches
35.8%Match win rate
41.2%Headshot %
0.0%Shot accuracy
1,774MVPs
485Hours (in match)
899Bombs planted
203Bombs defused

Most-used weapons

Lifetime map wins

4,371dust2
899nuke
702inferno
381train
249vertigo
210office
25italy
10ar_shoots

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

Skill profile

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

12.9%Headshot accuracy
31.7%Accuracy (enemy spotted)
34.9%Spray accuracy
77.6%Counter-strafing
11.9°Preaim
654msReaction time
33.2%T opening success
46.1%CT opening success
0.38Enemies flashed / flash
9.9%Flash assists
8.98HE damage / grenade
2.90Flashes / 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 12.8518% — below the 15% mark we flag

    Aim Training →
  2. 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 0.3818 — below the 0.5 mark we flag

    Grenade Lineups →
  3. 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 33.1719% — below the 40% mark we flag

Spend your practice time on Nuke

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

18% win rate across 11 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno7–9-0.103%7 Oct →
poseidon8–80.0211%7 Oct →
inferno2–90.056%7 Oct →
nuke5–13-0.0712%7 Oct →
dust213–80.0125%24 Sept →
office8–20.1620%24 Sept →
dust211–130.019%21 Sept →
dust27–13-0.027%17 Sept →
ancient13–11-0.059%17 Sept →
ancient12–30.088%17 Sept →
dust213–80.0318%17 Sept →
dust213–110.0313%15 Sept →
dust213–50.046%10 Sept →
nuke6–13-0.0527%4 Sept →
office8–130.0318%3 Sept →
poseidon7–9-0.039%3 Sept →
inferno9–5-0.0912%3 Sept →
anubis13–60.0213%3 Sept →
vertigo13–80.0224%3 Sept →
ancient12–120.0813%28 Aug →
train5–13-0.0924%28 Aug →
office4–13-0.0212%28 Aug →
dust29–13-0.0517%10 Aug →
dust213–90.0812%9 Aug →
dust213–11-0.006%19 Jul →
dust212–120.037%16 Jul →
anubis11–130.018%16 Jul →
dust213–9-0.0523%10 Jul →
dust213–11-0.0313%9 Jul →
anubis5–120.0611%9 Jul →
dust213–100.0311%7 Jul →
nuke7–13-0.106%19 Jun →
vertigo11–13-0.065%18 Jun →
mirage13–5-0.079%18 Jun →
dust28–13-0.008%11 Jun →
dust210–13-0.0231%4 Jun →
nuke5–13-0.0310%22 May →
dust25–130.028%22 May →
cache12–12-0.0420%7 May →
cache12–120.0217%2 May →
office2–130.0214%2 May →
office13–10-0.038%27 Apr →
office10–130.0714%27 Apr →
ancient12–12-0.029%23 Apr →
office8–13-0.0117%22 Apr →
nuke0–13-0.090%16 Apr →
ancient5–130.0415%16 Apr →
dust212–120.0216%13 Apr →
office10–130.0110%13 Apr →
vertigo13–4-0.026%13 Apr →
vertigo2–13-0.0513%8 Apr →
mirage7–13-0.0426%7 Apr →
nuke2–13-0.080%7 Apr →
vertigo3–13-0.084%7 Apr →
dust213–80.0216%3 Apr →
inferno13–80.0128%3 Apr →
dust213–30.038%1 Apr →
anubis13–10-0.0810%1 Apr →
anubis13–80.0411%1 Apr →
dust213–100.0421%28 Mar →
office1–100.0924%28 Mar →
dust213–20.0718%28 Mar →
office2–80.1121%28 Mar →
nuke4–13-0.024%28 Mar →
train7–130.046%28 Mar →
dust212–120.1116%26 Mar →
nuke4–13-0.0111%26 Mar →
office13–40.028%24 Mar →
ancient6–13-0.1113%20 Mar →
dust26–13-0.109%20 Mar →
nuke13–11-0.0515%18 Mar →
dust213–100.0210%15 Mar →
ancient13–10-0.0210%8 Mar →
dust213–3-0.0419%8 Mar →
dust213–7-0.0116%6 Mar →
nuke2–110.0224%5 Mar →
inferno5–13-0.0427%3 Mar →
mirage11–13-0.026%3 Mar →
anubis12–12-0.0213%3 Mar →
mirage5–130.0517%26 Feb →
office13–80.127%27 Jan →
nuke13–9-0.067%22 Jan →
dust211–130.0515%18 Jan →
dust210–13-0.0214%16 Jan →
ancient13–16-0.0610%28 Dec →
mirage16–14-0.055%25 Dec →
mirage9–1-0.054%25 Dec →
anubis3–7-0.0332%24 Dec →
dust22–13-0.0319%24 Dec →
mirage10–130.0110%23 Dec →
mirage13–3-0.004%23 Dec →
dust25–13-0.0415%22 Dec →
dust25–13-0.0511%18 Dec →
ancient7–13-0.106%11 Dec →
dust26–13-0.0410%11 Dec →
anubis12–120.0514%11 Dec →
dust210–130.0113%9 Dec →
golden13–11-0.067%9 Dec →
dust213–90.0118%9 Dec →
mirage13–11-0.0313%6 Dec →

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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