1000 Bees

1000 Bees — CS2 Stats

CA76561197960429047[U:1:163319]Steam profile ↗✓ No bans

499Tracked matches41%Win rate2021Tracked since
365Hours in CS
CSDB Rating2.6 LearningPositional Player
Ladder ranks via Leetify

Performance scores

Aim19
Positioning34
Utility27

0–100 skill scores via Leetify.

Recent form

COLD41–49–10Last 10041%Win rateTLWLLTLLLW

Last 10 vs previous 10: −10pp win rate · −0.00 avg rating · +0.1pp headshot accuracy · +20ms 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

  • 1–3–1 · 20% win rate
  • Avg rating -0.06
  • Avg headshot accuracy 8%
  • Avg reaction 663ms

Last 10

  • 2–6–2 · 20% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 10%
  • Avg reaction 669ms

Last 20

  • 5–13–2 · 25% win rate
  • Avg rating -0.04
  • Avg headshot accuracy 10%
  • Avg reaction 659ms

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 (+1.2 against its own average).

Aim1.9
Utility2.7
Positioning3.4
Opening Duels0.5

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

donk

Plays most like donk 70% 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. 660ms 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
Utility2.7
Mechanics5.0
Opening Duels0.4
Win Impact1.9

Composite 2.6/10 (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-0.04−0.02
first ⅓ avg -0.02 → last ⅓ avg -0.04
Reaction time665ms−4ms
first ⅓ avg 669ms → last ⅓ avg 665ms
Headshot accuracy9.7%−1.9%
first ⅓ avg 11.7% → last ⅓ avg 9.7%

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 · 13–4 · dust2, 10 Oct →
29%Best headshot accuracy · 13–9 · dust2, 6 Nov →
422msFastest reaction time · 13–4 · dust2, 10 Nov →
13–1Biggest win · nuke, 17 May →

Across the last 100 tracked matches.

Highlights

7Longest win streak
12–8In matches decided by ≤2 rounds

Map breakdown

nukeBest map · 63% over 8dust2Weakest map · 37% over 71
MapGradePlayedRecordWin rateAvg rating
dust2C7126–4537%-0.03
nukeA85–363%-0.00
ancientA53–260%-0.03
anubis—42–250%-0.04
mirage—31–233%-0.06
inferno—32–167%-0.05
basalt—21–150%-0.04
train—21–150%-0.04
cache—10–10%-0.09
edin—10–10%-0.11

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (37% over 71). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

12,596Lifetime kills
0.75K/D
1,087Matches
39.7%Match win rate
33.6%Headshot %
4.2%Shot accuracy
1,217MVPs
365Hours (in match)
692Bombs planted
137Bombs defused

Most-used weapons

AK-472,400
MP7687
P90661
AWP442
P250431
AUG365

Lifetime map wins

3,245dust2
1,238nuke
1,093inferno
433vertigo
57train
48bank
36office
34safehouse

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.

10.0%Headshot accuracy
26.7%Accuracy (enemy spotted)
28.9%Spray accuracy
72.5%Counter-strafing
13.6°Preaim
660msReaction time
33.0%T opening success
30.2%CT opening success
0.73Enemies flashed / flash
3.9%Flash assists
9.54HE damage / grenade
5.58Flashes / 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 13.5854° — 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 10.0283% — below the 15% 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.

37% win rate across 71 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
dust212–12-0.029%10 Jun →
cache6–13-0.096%10 Jun →
nuke13–1-0.033%17 May →
dust28–13-0.0615%16 May →
dust29–13-0.097%21 Jan →
mirage12–12-0.0815%18 Jan →
anubis9–130.0214%13 May →
ancient6–13-0.096%6 Apr →
dust27–130.0212%6 Apr →
inferno13–11-0.0513%31 Mar →
basalt3–13-0.046%30 Mar →
dust22–13-0.093%30 Mar →
edin3–13-0.1114%30 Mar →
basalt13–9-0.046%30 Mar →
nuke10–13-0.0117%30 Mar →
mirage7–13-0.055%28 Mar →
ancient2–13-0.0612%26 Mar →
nuke11–130.0410%16 Mar →
dust213–11-0.076%17 Feb →
dust213–30.0119%17 Feb →
nuke13–11-0.0212%3 Feb →
inferno13–7-0.039%3 Feb →
dust213–110.019%22 Jan →
dust22–13-0.0315%17 Jan →
nuke13–60.029%17 Jan →
train13–5-0.034%9 Jan →
dust213–3-0.018%9 Jan →
train5–13-0.0610%7 Jan →
inferno11–13-0.0612%7 Jan →
dust212–12-0.0211%7 Jan →
ancient13–8-0.036%5 Jan →
nuke13–10.0210%5 Jan →
mirage13–6-0.058%5 Jan →
ancient13–2-0.0121%31 Dec →
dust213–4-0.028%20 Dec →
dust213–11-0.0512%20 Dec →
dust213–11-0.0213%23 Nov →
dust29–13-0.1110%22 Nov →
dust26–13-0.0811%16 Nov →
dust24–13-0.083%16 Nov →
dust212–120.0418%16 Nov →
dust212–12-0.025%15 Nov →
dust212–12-0.0116%13 Nov →
dust28–13-0.078%13 Nov →
dust25–130.0110%10 Nov →
dust213–4-0.028%10 Nov →
ancient13–50.058%9 Nov →
anubis13–11-0.115%9 Nov →
dust24–13-0.114%9 Nov →
dust212–12-0.0310%7 Nov →
dust213–9-0.0229%6 Nov →
dust210–13-0.0811%6 Nov →
dust211–13-0.038%6 Nov →
dust213–2-0.0510%5 Nov →
dust26–13-0.015%4 Nov →
dust28–13-0.0315%4 Nov →
dust213–5-0.016%3 Nov →
dust28–130.0210%3 Nov →
dust213–70.049%3 Nov →
dust213–10-0.0414%1 Nov →
dust213–5-0.0111%1 Nov →
dust213–7-0.0117%30 Oct →
dust211–13-0.0710%30 Oct →
dust211–13-0.089%30 Oct →
dust29–13-0.0416%25 Oct →
dust23–13-0.075%22 Oct →
dust28–13-0.049%22 Oct →
dust213–110.048%20 Oct →
dust26–13-0.129%20 Oct →
dust213–90.036%16 Oct →
dust29–130.0211%16 Oct →
dust213–6-0.035%14 Oct →
dust26–13-0.0728%14 Oct →
dust22–13-0.0515%14 Oct →
dust213–11-0.0218%14 Oct →
dust212–12-0.0511%13 Oct →
dust26–13-0.065%12 Oct →
dust213–11-0.069%12 Oct →
dust27–130.048%11 Oct →
dust213–40.1010%10 Oct →
dust26–13-0.0811%10 Oct →
dust213–110.098%5 Oct →
dust21–13-0.0623%5 Oct →
dust213–50.0116%3 Oct →
dust212–12-0.0122%26 Sept →
anubis6–13-0.0512%26 Sept →
dust24–13-0.0910%25 Sept →
anubis13–11-0.0410%25 Sept →
nuke13–9-0.049%24 Sept →
dust213–50.058%22 Sept →
dust213–100.0015%22 Sept →
nuke4–5-0.020%21 Sept →
dust211–130.0217%21 Sept →
dust27–13-0.0712%18 Sept →
dust212–12-0.0713%17 Sept →
dust26–130.0310%17 Sept →
dust26–130.029%17 Sept →
dust26–13-0.0915%14 Sept →
dust211–13-0.046%13 Sept →
dust213–40.0318%12 Sept →

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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