TightSki

TightSki — CS2 Stats

US76561199532544884[U:1:1572279156]Steam profile ↗✓ No bans

387Tracked matches52%Win rate2023Tracked since
252Hours in CS
CSDB Rating4.5 DevelopingPositional Player
Premier CS Rating6,811Light Blue band · top ~70.1% of ranked players (population est.)
Ladder ranks via Leetify

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CSDB.GGTightSkiPREMIER6,811 · Light Blue bandcsdb.gg/stats

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Performance scores

Aim69
Positioning53
Utility22

0–100 skill scores via Leetify.

Recent form

STEADY44–54–2Last 10044%Win rateLWLLWWWWWL

Last 10 vs previous 10: +20pp win rate · +0.05 avg rating · −0.5pp headshot accuracy · −105ms reaction

Win rate up 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

  • 2–3 · 40% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 15%
  • Avg reaction 405ms

Last 10

  • 6–4 · 60% win rate
  • Avg rating 0.05
  • Avg headshot accuracy 14%
  • Avg reaction 438ms

Last 20

  • 10–10 · 50% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 14%
  • Avg reaction 491ms

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 (+1.1 against its own average).

Aim6.9
Utility2.2
Positioning5.3
Opening Duels5.2

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

s1mple

Plays most like s1mple 88% playstyle similarity

Most alike: aim profile, positioning profile.

Where you differ: lower opening-duel success; lower utility contribution.

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

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

Counter-strafing. Only 66% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim6.9
Positioning5.3
Utility2.2
Mechanics3.6
Opening Duels4.6
Win Impact5.6

Composite 4.5/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.02+0.08
first ⅓ avg -0.06 → last ⅓ avg 0.02
Reaction time497ms−192ms
first ⅓ avg 689ms → last ⅓ avg 497ms
Headshot accuracy11.9%+1.6%
first ⅓ avg 10.3% → last ⅓ avg 11.9%

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 · 13–3 · nuke, 12 Aug →
27%Best headshot accuracy · 7–13 · mirage, 9 Aug →
281msFastest reaction time · 8–13 · dust2, 17 Aug →
13–1Biggest win · mirage, 5 Aug →

Across the last 100 tracked matches.

Highlights

5Longest win streak
7–7In matches decided by ≤2 rounds
10Overtime games

Map breakdown

ancientBest map · 69% over 16infernoWeakest map · 25% over 12
MapGradePlayedRecordWin rateAvg rating
dust2B2512–1348%0.00
mirageC2510–1540%-0.01
ancientS1611–569%-0.03
nukeC156–940%-0.02
infernoD123–925%-0.06
anubisD62–433%-0.02
train—10–10%-0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 12). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Lifetime stats

8,246Lifetime kills
0.68K/D
734Matches
42.1%Match win rate
34.6%Headshot %
3.8%Shot accuracy
1,257MVPs
252Hours (in match)
621Bombs planted
57Bombs defused

Most-used weapons

Lifetime map wins

1,266dust2
974inferno
630nuke
390vertigo
58train
44office
8italy
5lake

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.

12.5%Headshot accuracy
33.8%Accuracy (enemy spotted)
33.3%Spray accuracy
66.3%Counter-strafing
6.1°Preaim
491msReaction time
46.2%T opening success
50.4%CT opening success
0.33Enemies flashed / flash
2.2%Flash assists
17.52HE damage / grenade
1.32Flashes / 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 12.4607% — 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 0.3342 — below the 0.5 mark we flag

    Grenade Lineups →
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.

25% win rate across 12 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust28–130.0016%26 Aug →
dust213–80.0422%17 Aug →
dust28–13-0.0613%17 Aug →
mirage7–130.0316%17 Aug →
nuke13–30.157%12 Aug →
anubis13–90.025%11 Aug →
dust213–80.0016%11 Aug →
dust213–60.0212%11 Aug →
dust213–50.1513%10 Aug →
dust214–160.1016%10 Aug →
dust29–130.0422%10 Aug →
anubis13–70.0113%10 Aug →
mirage13–110.025%10 Aug →
mirage7–130.0927%9 Aug →
dust213–110.0318%9 Aug →
nuke10–13-0.0312%9 Aug →
dust213–70.0515%7 Aug →
anubis3–13-0.118%6 Aug →
dust211–13-0.008%6 Aug →
nuke4–13-0.1012%6 Aug →
dust23–13-0.0415%6 Aug →
mirage4–13-0.078%6 Aug →
mirage13–10.0513%5 Aug →
dust213–70.018%5 Aug →
mirage15–150.106%5 Aug →
mirage9–13-0.0614%4 Aug →
ancient13–16-0.0515%4 Aug →
dust216–120.058%4 Aug →
mirage13–40.102%4 Aug →
mirage13–20.117%4 Aug →
dust24–130.019%4 Aug →
mirage13–110.0612%4 Aug →
nuke13–1-0.010%4 Aug →
ancient13–4-0.027%4 Aug →
nuke13–50.064%4 Aug →
dust26–130.017%4 Aug →
mirage11–130.0613%4 Aug →
nuke13–90.1010%3 Aug →
anubis11–130.1310%3 Aug →
dust213–20.049%3 Aug →
inferno11–130.047%3 Aug →
mirage13–9-0.0112%3 Aug →
ancient13–20.0211%3 Aug →
mirage6–00.0315%3 Aug →
nuke13–9-0.016%3 Aug →
ancient10–130.047%3 Aug →
ancient13–90.0412%3 Aug →
mirage13–100.0311%3 Aug →
mirage13–11-0.016%3 Aug →
inferno9–13-0.058%2 Aug →
dust26–2-0.0223%2 Aug →
dust216–14-0.0012%2 Aug →
dust214–16-0.079%2 Aug →
ancient6–13-0.0710%1 Aug →
nuke6–13-0.0219%31 Jul →
inferno13–16-0.066%29 Jul →
ancient13–11-0.0619%29 Jul →
ancient9–13-0.070%28 Jul →
ancient13–8-0.0116%28 Jul →
dust24–13-0.0513%28 Jul →
mirage6–13-0.1113%27 Jul →
inferno9–13-0.1115%27 Jul →
nuke0–13-0.100%26 Jul →
nuke9–13-0.0410%25 Jul →
nuke9–13-0.0912%25 Jul →
dust25–13-0.0612%25 Jul →
inferno3–13-0.0817%25 Jul →
ancient13–11-0.0418%25 Jul →
mirage7–13-0.130%25 Jul →
ancient13–9-0.075%24 Jul →
inferno7–13-0.077%24 Jul →
nuke7–13-0.0925%24 Jul →
dust213–20.0019%24 Jul →
ancient13–7-0.0712%24 Jul →
anubis4–13-0.0521%24 Jul →
mirage6–13-0.049%24 Jul →
mirage14–16-0.1217%22 Jul →
inferno13–6-0.0419%14 Jul →
mirage6–13-0.109%13 Jul →
inferno3–13-0.100%5 Jun →
nuke10–13-0.069%25 Jan →
mirage2–13-0.0611%25 Jan →
inferno3–13-0.093%25 Jan →
mirage5–13-0.066%25 Jan →
anubis7–13-0.140%25 Jan →
inferno4–13-0.057%3 Jan →
mirage5–13-0.046%27 Dec →
dust22–13-0.1122%30 Nov →
mirage10–13-0.0811%30 Nov →
ancient16–12-0.078%30 Nov →
nuke4–13-0.0410%30 Nov →
inferno13–9-0.084%30 Nov →
ancient13–70.0112%29 Nov →
nuke13–5-0.032%29 Nov →
mirage13–4-0.0410%29 Nov →
inferno13–90.008%29 Nov →
train6–13-0.015%28 Nov →
ancient13–10-0.0411%28 Nov →
dust27–13-0.0523%28 Nov →
ancient15–15-0.018%28 Nov →

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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