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๐Ÿ—ฟโƒค๐Ÿท Bot Tom ๐Ÿ—ฟโƒค

๐Ÿ—ฟโƒค๐Ÿท Bot Tom ๐Ÿ—ฟโƒค โ€” CS2 Stats

NE76561199085726155[U:1:1125460427]Steam profile โ†—โœ“ No bans

854Tracked matches52%Win rate2022Tracked since
646Hours in CS
CSDB Rating5.5 SolidAll-Rounder
Premier CS Rating10,216Blue band ยท top ~53.8% of ranked players (population est.)
CSDB Leaderboard#186174 of 261531 tracked
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 11 Nov 2026 (3 days ago). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Rating over time

Premier CS Rating: 10,216 -2,179 11 Aug โ€“ 11 Nov ยท 38 days played
10,16412,886peak 12,88611 Aug11 Nov
12,886Peak Premier in tracked matches
42Days played since 2026-08-11

Premier CS Rating

  • 2,670 below peak (12,886)
  • -1,033 over 30 days ยท declining
  • -1,838 over 90 days
  • Next: Purple band at 15,000 โ€” 4,784 to go
  • Reached: Blue band ยท Light Blue band
  • Blue band first seen 2026-09-10
  • Light Blue band first seen 2026-09-10

Premier comes from this profileโ€™s tracked match history, so it reaches back as far as those matches do.

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 โ€” those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerBlue band medianPurple band medianvs Purple band
Headshot rate46.7%42.0%44.4%above
Shot accuracy9.5%9.6%11.9%2.4% short
Kill/death ratio0.910.981.030.12 short
Match win rate38.5%43.8%45.2%6.7% short

This profile matches the typical Purple band player on 1 of 4 comparable metrics.

Widest gap: Shot accuracy. That is the metric furthest from the Purple band median in relative terms โ€” not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GG๐Ÿ—ฟโƒค๐Ÿท Bot Tom ๐Ÿ—ฟโƒคPREMIER10,216 ยท Blue bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere โ€” it is generated in your browser when you click.

Performance scores

Aim68
Positioning61
Utility44

0โ€“100 skill scores via Leetify.

Recent form

STEADY42โ€“54โ€“4Last 10042%Win rateTLWLWLWWLL

Last 10 vs previous 10: 0pp win rate ยท โˆ’0.02 avg rating ยท โˆ’10.8pp headshot accuracy ยท +13ms reaction

Win rate 0pp across the last 10 against the 10 before โ€” within the normal variation of a 10-match window (ยฑ20pp), so no real shift yet.

Last 5 ยท 10 ยท 20 matches

Last 5

  • 2โ€“2โ€“1 ยท 40% win rate
  • Avg rating -0.03
  • Avg headshot accuracy 17%
  • Avg reaction 575ms

Last 10

  • 4โ€“5โ€“1 ยท 40% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 16%
  • Avg reaction 572ms

Last 20

  • 8โ€“11โ€“1 ยท 40% win rate
  • Avg rating 0.00
  • Avg headshot accuracy 22%
  • Avg reaction 565ms

Newest first, from the last 100 tracked matches. Each block is its own sample โ€” one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-Rounder โ€” No style dimension stands clear of the others in this profile.

Aim6.8
Utility4.4
Positioning6.1
Opening Duels6.4

Style profile from tracked-match aggregates โ€” 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 โ€” 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

s1mple

Plays most like s1mple 90% playstyle similarity

Most alike: opening-duel success, utility contribution.

Where you differ: lower positioning profile; lower aim profile.

Similarity of playstyle shape across shared dimensions โ€” it says how you play, not that you play at their level. Full comparison โ†’

Strengths & areas to improve

Areas to improve

Reaction time. 581ms from enemy-visible to first shot leaves fights decided before they start โ€” warmup routines move this number more than anything else.

Counter-strafing. Only 70% of shots are taken properly stopped โ€” moving-shot inaccuracy is quietly taxing every duel.

Generated by fixed rules over this profile's own numbers โ€” no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim6.8
Positioning6.1
Utility4.4
Mechanics4.4
Opening Duels6.6
Win Impact5.6

Composite 5.5/10 (Solid), a weighted mean of the bars with a small opposition adjustment (ร—0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.01+0.03
first โ…“ avg -0.01 โ†’ last โ…“ avg 0.01
Reaction time579msโˆ’11ms
first โ…“ avg 591ms โ†’ last โ…“ avg 579ms
Headshot accuracy22.4%+3.4%
first โ…“ avg 19.0% โ†’ last โ…“ avg 22.4%

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

0.15Best match rating ยท 13โ€“2 ยท nuke, 3 Oct โ†’
60%Best headshot accuracy ยท 8โ€“0 ยท mirage, 2 Sept โ†’
375msFastest reaction time ยท 3โ€“13 ยท inferno, 29 Sept โ†’
13โ€“1Biggest win ยท mirage, 1 Oct โ†’

Across the last 100 tracked matches.

Highlights

4Longest win streak
3โ€“4In matches decided by โ‰ค2 rounds
4Overtime games

Map breakdown

infernoBest map ยท 70% over 10cacheWeakest map ยท 29% over 7
MapGradePlayedRecordWin rateAvg rating
nukeD227โ€“1532%0.00
mirageC177โ€“1041%0.00
dust2B157โ€“847%0.01
anubisB115โ€“645%-0.01
infernoS107โ€“370%0.01
ancientC94โ€“544%-0.00
cacheD72โ€“529%-0.01
officeโ€”32โ€“167%-0.05
vertigoโ€”20โ€“20%-0.03
trainโ€”21โ€“150%-0.01
italyโ€”10โ€“10%-0.10
overpassโ€”10โ€“10%-0.03

Across the last 100 tracked matches.

Lifetime stats

28,642Lifetime kills
0.91K/D
1,969Matches
38.5%Match win rate
46.7%Headshot % ยท Top 50% of Blue band
9.5%Shot accuracy
3,382MVPs
646Hours (in match)
1,788Bombs planted
367Bombs defused

Most-used weapons

AK-477,973
M4A4 / M4A1-S5,021
AWP2,587
Desert Eagle1,873
P2000 / USP-S1,676
SSG 081,219
Glock-181,216
MP91,122
FAMAS918
Galil AR656

Lifetime map wins

2,237nuke
2,184dust2
1,756inferno
315vertigo
234office
153train
90lake
64cbble

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

Skill profile

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

22.8%Headshot accuracy
33.9%Accuracy (enemy spotted)
42.0%Spray accuracy
69.9%Counter-strafing
10.8ยฐPreaim
581msReaction time
54.3%T opening success
58.6%CT opening success
0.45Enemies flashed / flash
11.2%Flash assists
9.09HE damage / grenade
6.28Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag โ€” the measurement behind each one is shown, so you can disagree with it.

  1. 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 0.4506 โ€” below the 0.5 mark we flag

    Grenade Lineups โ†’
Spend your practice time on Cache

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

29% win rate across 7 tracked games โ€” your weakest map with enough games to be worth reading into.

Cache callouts & strategy โ†’

Recent matches

MapScoreRatingHS%Date
cache12โ€“12-0.0816%13 Nov โ†’
anubis7โ€“13-0.0721%11 Nov โ†’
inferno13โ€“40.0814%4 Nov โ†’
office9โ€“13-0.0517%3 Nov โ†’
office13โ€“5-0.0218%3 Nov โ†’
anubis3โ€“13-0.026%27 Oct โ†’
ancient13โ€“50.0116%27 Oct โ†’
cache13โ€“20.0515%23 Oct โ†’
anubis3โ€“13-0.0311%23 Oct โ†’
dust27โ€“40.0731%23 Oct โ†’
ancient11โ€“130.0620%16 Oct โ†’
nuke5โ€“130.0823%16 Oct โ†’
dust213โ€“5-0.0840%14 Oct โ†’
nuke5โ€“13-0.0450%14 Oct โ†’
cache7โ€“13-0.0321%13 Oct โ†’
dust29โ€“130.0125%11 Oct โ†’
anubis13โ€“50.007%10 Oct โ†’
dust26โ€“13-0.0836%4 Oct โ†’
dust213โ€“40.0933%3 Oct โ†’
nuke13โ€“20.1519%3 Oct โ†’
nuke6โ€“130.0221%2 Oct โ†’
anubis13โ€“30.0631%1 Oct โ†’
mirage13โ€“10.0728%1 Oct โ†’
nuke5โ€“130.0019%1 Oct โ†’
nuke13โ€“2-0.0810%1 Oct โ†’
dust213โ€“60.0519%30 Sept โ†’
dust213โ€“70.1237%30 Sept โ†’
inferno5โ€“13-0.0330%30 Sept โ†’
anubis13โ€“60.0432%29 Sept โ†’
inferno13โ€“40.0620%29 Sept โ†’
cache5โ€“130.0215%29 Sept โ†’
anubis6โ€“130.0818%29 Sept โ†’
inferno3โ€“13-0.0324%29 Sept โ†’
nuke7โ€“130.1515%29 Sept โ†’
mirage11โ€“13-0.0521%28 Sept โ†’
mirage15โ€“150.0917%28 Sept โ†’
nuke11โ€“5-0.0719%28 Sept โ†’
mirage7โ€“13-0.0225%28 Sept โ†’
dust213โ€“70.0320%27 Sept โ†’
anubis9โ€“130.0318%26 Sept โ†’
nuke6โ€“13-0.0615%26 Sept โ†’
nuke13โ€“160.0824%26 Sept โ†’
nuke13โ€“110.0113%26 Sept โ†’
dust27โ€“13-0.0219%25 Sept โ†’
italy2โ€“13-0.108%25 Sept โ†’
inferno5โ€“13-0.0216%25 Sept โ†’
vertigo9โ€“13-0.0317%23 Sept โ†’
vertigo10โ€“13-0.0419%23 Sept โ†’
nuke6โ€“90.0415%23 Sept โ†’
mirage13โ€“90.0326%23 Sept โ†’
mirage13โ€“9-0.0722%22 Sept โ†’
anubis13โ€“11-0.0327%22 Sept โ†’
nuke9โ€“130.0326%22 Sept โ†’
ancient9โ€“13-0.0416%21 Sept โ†’
nuke9โ€“130.0122%21 Sept โ†’
nuke13โ€“7-0.0125%21 Sept โ†’
nuke13โ€“30.0214%21 Sept โ†’
nuke3โ€“13-0.1015%20 Sept โ†’
mirage6โ€“130.0525%19 Sept โ†’
dust29โ€“13-0.069%18 Sept โ†’
ancient13โ€“8-0.0416%18 Sept โ†’
mirage12โ€“12-0.0430%18 Sept โ†’
mirage6โ€“13-0.0114%17 Sept โ†’
cache4โ€“13-0.0225%16 Sept โ†’
dust213โ€“90.0522%16 Sept โ†’
inferno13โ€“100.0419%14 Sept โ†’
mirage4โ€“13-0.010%14 Sept โ†’
mirage13โ€“70.0518%11 Sept โ†’
nuke1โ€“13-0.0823%11 Sept โ†’
dust22โ€“13-0.0710%11 Sept โ†’
nuke7โ€“13-0.124%11 Sept โ†’
inferno13โ€“10.0113%7 Sept โ†’
mirage13โ€“160.0125%7 Sept โ†’
cache8โ€“130.0216%5 Sept โ†’
ancient13โ€“9-0.0020%2 Sept โ†’
office13โ€“4-0.0731%2 Sept โ†’
cache13โ€“10-0.0220%2 Sept โ†’
mirage8โ€“00.0160%2 Sept โ†’
dust26โ€“13-0.0430%1 Sept โ†’
nuke12โ€“12-0.0510%1 Sept โ†’
nuke13โ€“40.1217%22 Aug โ†’
nuke10โ€“13-0.024%22 Aug โ†’
anubis16โ€“14-0.0317%22 Aug โ†’
inferno13โ€“90.0315%22 Aug โ†’
anubis0โ€“13-0.0831%21 Aug โ†’
dust27โ€“130.1129%21 Aug โ†’
ancient11โ€“130.0216%21 Aug โ†’
train3โ€“13-0.069%21 Aug โ†’
overpass11โ€“13-0.0314%21 Aug โ†’
dust213โ€“8-0.0213%21 Aug โ†’
mirage13โ€“10-0.0019%21 Aug โ†’
mirage13โ€“50.0420%21 Aug โ†’
ancient8โ€“130.0410%19 Aug โ†’
inferno13โ€“6-0.0614%17 Aug โ†’
inferno13โ€“80.0322%14 Aug โ†’
mirage4โ€“13-0.0710%14 Aug โ†’
train13โ€“40.0532%13 Aug โ†’
ancient8โ€“13-0.0214%13 Aug โ†’
ancient13โ€“5-0.0721%11 Aug โ†’
mirage10โ€“13-0.0622%11 Aug โ†’

Match data via Leetify.

Recent teammates

Milestones

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

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