Colonel Private Boboinski XIV

Colonel Private Boboinski XIV — CS2 Stats

RU76561198140443786[U:1:180178058]Steam profile ↗✓ No bans

659Tracked matches21%Win rate2020Tracked since
CSDB Rating4.5 DevelopingPositional Player
Ladder ranks via Leetify

Performance scores

Aim74
Positioning38
Utility35

0–100 skill scores via Leetify.

Recent form

COLD31–63–6Last 10031%Win rateLTLWLLLWLL

Last 10 vs previous 10: −10pp win rate · −0.00 avg rating · −1.0pp headshot accuracy · −14ms 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 -0.01
  • Avg headshot accuracy 38%
  • Avg reaction 636ms

Last 10

  • 2–7–1 · 20% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 32%
  • Avg reaction 621ms

Last 20

  • 5–14–1 · 25% win rate
  • Avg rating -0.02
  • Avg headshot accuracy 32%
  • Avg reaction 628ms

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 (+1.4 against its own average).

Aim7.4
Utility3.5
Positioning3.8
Opening Duels0.0

Strong CT-side opener

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

b1t

Plays most like b1t 96% playstyle similarity

Most alike: aim profile, utility contribution.

Where you differ: lower opening-duel success; lower positioning 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

Positioning. Positioning trails aim by 36 points — deaths here waste a strong aim profile.

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 34% on CT to 19% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 636ms 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

Aim7.4
Positioning3.8
Utility3.5
Mechanics6.2
Opening Duels0.5
Win Impact0.0

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-0.03−0.01
first ⅓ avg -0.02 → last ⅓ avg -0.03
Reaction time627ms+2ms
first ⅓ avg 624ms → last ⅓ avg 627ms
Headshot accuracy29.1%+4.0%
first ⅓ avg 25.2% → last ⅓ avg 29.1%

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

0.10Best match rating · 13–9 · cache, 9 May →
60%Best headshot accuracy · 6–13 · office, 7 Mar →
422msFastest reaction time · 5–13 · nuke, 22 Feb →
13–2Biggest win · office, 7 Mar →

Across the last 100 tracked matches.

Highlights

3Longest win streak
5–5In matches decided by ≤2 rounds

Map breakdown

cacheBest map · 57% over 7infernoWeakest map · 17% over 6
MapGradePlayedRecordWin rateAvg rating
nukeD4210–3224%-0.03
officeC125–742%-0.02
vertigoD102–820%-0.02
cacheA74–357%-0.02
infernoD61–517%-0.02
overpassD51–420%-0.02
train—41–325%-0.06
warden—42–250%-0.02
dust2—31–233%-0.04
italy—22–0100%0.07
mirage—21–150%-0.03
anubis—10–10%-0.03
ancient—10–10%-0.05
alpine—11–0100%-0.01

Across the last 100 tracked matches.

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

Skill profile

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

30.1%Headshot accuracy
32.3%Accuracy (enemy spotted)
41.5%Spray accuracy
78.1%Counter-strafing
11.5°Preaim
636msReaction time
19.0%T opening success
34.0%CT opening success
0.37Enemies flashed / flash
4.8%Flash assists
6.38HE damage / grenade
5.44Flashes / 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. 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 0.3741 — below the 0.5 mark we flag

    Grenade Lineups →
  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 19.0352% — 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.

17% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke5–130.0838%10 Oct →
nuke12–12-0.0335%10 Oct →
nuke8–13-0.0348%10 Oct →
nuke13–10-0.0927%4 Oct →
nuke8–130.0341%4 Oct →
nuke11–13-0.0725%4 Oct →
nuke6–130.0127%4 Oct →
nuke13–11-0.0426%2 Oct →
nuke10–13-0.0226%2 Oct →
nuke7–13-0.0724%2 Oct →
nuke6–13-0.0725%28 Sept →
office3–130.029%7 Jun →
italy13–90.1059%7 Jun →
vertigo4–13-0.0525%7 Jun →
nuke7–13-0.0444%5 Jun →
nuke1–13-0.0431%31 May →
nuke13–9-0.0032%31 May →
nuke9–13-0.0829%31 May →
nuke9–13-0.0321%25 May →
nuke13–3-0.0150%25 May →
nuke10–13-0.0331%25 May →
nuke9–13-0.0822%25 May →
nuke5–13-0.0344%25 May →
nuke10–13-0.0327%25 May →
nuke4–130.0132%25 May →
office7–13-0.0526%25 May →
vertigo1–13-0.1120%24 May →
cache11–13-0.0626%24 May →
nuke13–5-0.0122%20 May →
cache9–13-0.0612%20 May →
cache13–11-0.0612%16 May →
nuke2–13-0.0629%16 May →
vertigo10–130.0017%16 May →
vertigo3–13-0.0624%15 May →
nuke8–13-0.0525%15 May →
cache13–90.1026%9 May →
cache12–120.0112%9 May →
nuke6–13-0.0324%9 May →
cache13–10-0.0223%29 Apr →
cache13–4-0.0317%29 Apr →
nuke7–13-0.0535%25 Apr →
nuke2–13-0.0920%19 Apr →
nuke5–13-0.0457%18 Apr →
inferno4–13-0.0845%12 Apr →
nuke4–13-0.0620%2 Apr →
nuke8–13-0.0531%29 Mar →
nuke13–11-0.0442%29 Mar →
office5–13-0.0533%29 Mar →
nuke13–11-0.0644%29 Mar →
inferno12–12-0.0314%29 Mar →
dust213–8-0.0827%29 Mar →
nuke4–13-0.0116%28 Mar →
nuke3–13-0.0136%28 Mar →
train1–13-0.140%28 Mar →
office10–13-0.0337%28 Mar →
vertigo11–13-0.0421%16 Mar →
inferno7–13-0.0133%16 Mar →
inferno11–13-0.0048%16 Mar →
office13–80.0257%16 Mar →
office13–8-0.0453%16 Mar →
dust26–13-0.049%16 Mar →
office13–50.0846%16 Mar →
nuke12–120.0024%16 Mar →
overpass13–10-0.0627%12 Mar →
overpass4–13-0.0820%12 Mar →
overpass12–120.0419%12 Mar →
vertigo13–80.0223%12 Mar →
dust210–13-0.0116%12 Mar →
nuke2–13-0.0529%7 Mar →
warden3–13-0.0925%7 Mar →
mirage12–12-0.0733%7 Mar →
office6–13-0.0660%7 Mar →
anubis1–13-0.0326%7 Mar →
office13–2-0.0450%7 Mar →
nuke5–13-0.0812%22 Feb →
nuke13–6-0.1210%22 Feb →
nuke13–70.0420%22 Feb →
warden13–20.0213%22 Feb →
overpass9–130.0022%22 Feb →
vertigo6–120.0017%22 Feb →
inferno5–0-0.0125%22 Feb →
mirage13–100.0216%22 Feb →
office13–6-0.0141%22 Feb →
train11–13-0.0415%21 Feb →
italy13–70.0541%21 Feb →
office10–13-0.0332%21 Feb →
nuke13–110.0230%20 Feb →
ancient4–13-0.0523%20 Feb →
alpine13–9-0.0114%13 Feb →
vertigo13–30.0126%13 Feb →
warden9–13-0.0326%12 Feb →
warden13–50.0213%12 Feb →
overpass4–11-0.0123%12 Feb →
vertigo7–13-0.0130%8 Feb →
office8–13-0.0529%8 Feb →
inferno8–130.0238%8 Feb →
nuke4–13-0.0110%3 Jan →
train4–13-0.0314%3 Jan →
vertigo5–130.0131%3 Jan →
train13–6-0.0419%3 Jan →

Match data via Leetify.

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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