Anni

Anni — CS2 Stats

DE76561198045340142[U:1:85074414]Steam profile ↗✓ No bans

115Tracked matches37%Win rate2021Tracked since
895Hours in CS
CSDB Rating2.5 LearningPositional Player
Ladder ranks via Leetify

Rating over time

Premier CS Rating: 5,914 +411 26 Nov – 4 Jan · 6 days played
5,0436,266peak 6,26626 Nov4 Jan
6,368Peak Premier in tracked matches
36Days played since 2021-08-20

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

Performance scores

Aim19
Positioning34
Utility32

0–100 skill scores via Leetify.

Recent form

COLD32–47–2Last 8140%Win rateLLLLLLWLWL

Last 10 vs previous 10: −20pp win rate · −0.01 avg rating · +0.8pp headshot accuracy · −76ms reaction

Win rate down 20pp 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

  • 0–5 · 0% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 12%
  • Avg reaction 735ms

Last 10

  • 2–8 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 12%
  • Avg reaction 669ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 12%
  • Avg reaction 707ms

Newest first, from the last 81 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 against its own average).

Aim1.9
Utility3.2
Positioning3.4
Opening Duels0.7

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 65% 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. 704ms 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

Aim1.9
Positioning3.4
Utility3.2
Mechanics4.6
Opening Duels0.0
Win Impact0.6

Composite 2.5/10 (Learning), 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 -0.02 → last ⅓ avg -0.02
Reaction time689ms+15ms
first ⅓ avg 675ms → last ⅓ avg 689ms
Headshot accuracy11.0%−0.0%
first ⅓ avg 11.0% → last ⅓ avg 11.0%

Rolling 5-match average across the last 81 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.11Best match rating · 13–3 · dust2, 2 Aug →
29%Best headshot accuracy · 13–4 · mirage, 14 Jun →
500msFastest reaction time · 6–13 · inferno, 21 Nov →
16–1Biggest win · cache, 10 Sept →

Across the last 81 tracked matches.

Highlights

5Longest win streak
L6Current streak
3–7In matches decided by ≤2 rounds
12Overtime games

Map breakdown

trainBest map · 67% over 6dust2Weakest map · 14% over 7
MapGradePlayedRecordWin rateAvg rating
ancientD165–1131%-0.03
infernoA149–564%-0.03
overpassD134–931%-0.03
dust2D71–614%-0.03
trainS64–267%-0.03
mirageB63–350%-0.04
cacheB63–350%-0.01
nuke—40–40%-0.05
vertigo—31–233%-0.04
italy—20–20%-0.03
anubis—21–150%-0.08
office—21–150%0.02

Across the last 81 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (14% over 7). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

37,251Lifetime kills
0.96K/D
2,730Matches
46.6%Match win rate · Top 50% of tracked players
32.4%Headshot %
19.7%Shot accuracy · Top 5% of tracked players
3,056MVPs
895Hours (in match)
824Bombs planted
296Bombs defused

Most-used weapons

Lifetime map wins

3,699dust2
2,339inferno
932cbble
860office
745train
697nuke
220vertigo
32aztec

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

Faceit stats

Combat

16Matches
38%Win rate
0.78Avg K/D
—ADR
34%Headshot %

Clutches & streaks

—1v1 clutch win
—1v2 clutch win
2Longest win streak

Recent Faceit resultsWLWLW

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.

10.3%Headshot accuracy
29.2%Accuracy (enemy spotted)
32.4%Spray accuracy
70.6%Counter-strafing
13.6°Preaim
704msReaction time
27.0%T opening success
29.9%CT opening success
0.43Enemies flashed / flash
1.4%Flash assists
6.96HE 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. Advanced Mechanics

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

    Preaim 13.6358° — 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 10.2558% — below the 15% mark we flag

    Aim Training →
  3. Best CS2 Settings

    Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.

    Reaction time 703.9362ms — above the 700ms mark we flag

    Aim Training →
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.

14% win rate across 7 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategy →Dust 2 grenade lineups →

Recent matches

MapScoreRatingHS%Date
train2–13-0.0520%3 Oct →
mirage4–13-0.004%15 Aug →
nuke1–13-0.1013%15 Aug →
cache4–130.0413%15 Aug →
ancient6–13-0.0111%15 Aug →
italy3–12-0.0915%15 Aug →
inferno13–10-0.058%15 Aug →
train8–13-0.036%2 Aug →
dust213–30.1112%2 Aug →
dust29–13-0.0122%1 Aug →
cache13–3-0.0114%1 Aug →
dust24–13-0.046%1 Aug →
vertigo13–5-0.039%1 Aug →
mirage13–9-0.048%1 Aug →
mirage2–130.0219%1 Aug →
inferno13–90.009%1 Aug →
inferno9–130.0613%1 Aug →
vertigo11–13-0.069%1 Aug →
italy6–130.027%1 Aug →
dust29–13-0.0621%1 Aug →
cache13–60.063%1 Aug →
overpass5–30.0425%1 Aug →
ancient13–6-0.038%1 Aug →
train13–3-0.0212%1 Aug →
anubis13–9-0.063%1 Aug →
ancient7–13-0.045%31 Jul →
dust24–13-0.090%19 Jul →
dust211–13-0.088%19 Jul →
ancient8–13-0.069%21 Mar →
overpass9–13-0.068%4 Jan →
train13–6-0.043%4 Jan →
overpass1–13-0.103%10 Dec →
inferno13–10-0.077%7 Dec →
inferno12–16-0.079%1 Dec →
nuke4–110.037%1 Dec →
ancient13–3-0.006%1 Dec →
ancient8–13-0.0415%29 Nov →
ancient5–13-0.069%29 Nov →
nuke9–13-0.098%29 Nov →
overpass12–16-0.028%29 Nov →
train16–12-0.0212%26 Nov →
inferno13–11-0.085%26 Nov →
train13–6-0.007%26 Nov →
ancient13–2-0.053%26 Nov →
mirage8–13-0.097%26 Nov →
dust210–13-0.0313%23 Nov →
overpass11–13-0.088%23 Nov →
overpass15–15-0.049%23 Nov →
overpass5–13-0.0417%23 Nov →
inferno5–13-0.0817%22 Nov →
overpass14–16-0.0110%21 Nov →
ancient13–70.053%21 Nov →
overpass11–13-0.039%21 Nov →
inferno6–13-0.0423%21 Nov →
overpass13–10.057%21 Nov →
ancient2–13-0.058%19 Nov →
ancient11–13-0.019%19 Nov →
ancient5–13-0.0810%9 Nov →
ancient7–13-0.0110%9 Nov →
ancient13–16-0.007%8 Nov →
mirage13–4-0.0629%14 Jun →
ancient6–13-0.070%18 Jul →
inferno13–50.0620%18 Jul →
office13–10.087%4 May →
inferno1–13-0.1121%1 Jan →
ancient13–8-0.066%28 Sept →
inferno13–40.0222%28 Sept →
inferno16–13-0.0218%28 Sept →
overpass5–13-0.059%22 Sept →
anubis7–13-0.1110%16 Sept →
cache8–8-0.065%27 Aug →
overpass9–4-0.0119%18 Aug →
inferno9–6-0.018%18 Aug →
vertigo1–9-0.029%12 May →
nuke7–9-0.0115%19 Feb →
cache10–16-0.079%18 Feb →
mirage9–7-0.067%26 Jun →
cache16–1-0.003%10 Sept →
inferno16–120.0215%6 Sept →
overpass16–90.037%29 Aug →
office3–16-0.057%20 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

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