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Sergeant Reckless

Sergeant Reckless — CS2 Stats

ZA76561198984824516[U:1:1024558788]Steam profile ↗

1,269Tracked matches38%Win rate2020Tracked since
CSDB Rating2.2 Learning
Premier CS Rating3,327Grey band · top ~85.9% of ranked players (population est.)
CSDB Leaderboard#16530 of 21320 tracked
Ladder ranks via Leetify

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CSDB.GGSergeant RecklessPREMIER3,327 · Grey bandcsdb.gg/stats

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Performance scores

Aim37
Positioning33
Utility12

0–100 skill scores via Leetify.

Recent form

STEADY38–61–1Last 10038%Win rateWLLLLLWWWW

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating

Player DNA

Aim3.7
Aggression3.7
Utility1.2
Positioning3.3
Opening Duels0.5

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

NiKo

Plays most like NiKo 68% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower utility contribution; 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. 619ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 59% 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

Aim3.7
Positioning3.3
Utility1.2
Mechanics2.0
Opening Duels0.5
Win Impact1.0

Composite 2.2/10 (Learning), 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 rating-0.04−0.00
first ⅓ avg -0.04 → last ⅓ avg -0.04
Reaction time632ms−65ms
first ⅓ avg 696ms → last ⅓ avg 632ms
Headshot accuracy10.4%−2.0%
first ⅓ avg 12.4% → last ⅓ avg 10.4%

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.

Highlights

0.11Best rating — mirage 13–2
13–1Biggest win — cache
5Longest win streak
3–4In matches decided by ≤2 rounds
6Overtime games

Map breakdown

cacheBest map · 67% over 6infernoWeakest map · 25% over 16
MapGradePlayedRecordWin rateAvg rating
mirageB2210–1245%-0.03
dust2B2111–1052%-0.03
infernoD164–1225%-0.06
overpassD123–925%-0.04
nukeD82–625%-0.06
anubisD82–625%-0.04
ancientD72–529%-0.04
cacheS64–267%-0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (25% over 16). 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.

9.5%Headshot accuracy
35.7%Accuracy (enemy spotted)
41.9%Spray accuracy
59.1%Counter-strafing
12.1°Preaim
619msReaction time
32.7%T opening success
31.4%CT opening success
0.14Enemies flashed / flash
0.0%Flash assists
8.30HE damage / grenade
0.72Flashes / 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 12.091° — 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 9.5104% — below the 15% mark we flag

    Aim Training →
  3. 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 0.1432 — 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 16 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
inferno13–8-0.039%29 May →
inferno8–13-0.074%27 May →
inferno10–13-0.119%21 May →
dust26–13-0.056%21 May →
inferno6–13-0.032%15 May →
overpass9–13-0.0412%15 May →
mirage13–2-0.0315%15 May →
inferno13–9-0.0411%14 May →
cache13–30.006%9 May →
cache13–40.026%9 May →
cache11–13-0.0511%9 May →
cache13–10.038%9 May →
cache2–13-0.0810%9 May →
inferno10–13-0.044%9 May →
cache13–9-0.0214%7 May →
ancient4–13-0.0412%7 May →
inferno8–13-0.063%7 May →
mirage11–130.019%4 May →
mirage12–16-0.104%3 May →
dust213–7-0.0618%3 May →
nuke9–13-0.074%3 May →
anubis15–15-0.0317%27 Apr →
nuke6–13-0.070%24 Apr →
nuke6–13-0.074%24 Apr →
anubis5–130.0013%24 Apr →
mirage13–50.0119%24 Apr →
dust212–16-0.059%16 Apr →
dust213–90.0410%16 Apr →
anubis3–13-0.148%16 Apr →
mirage13–8-0.0728%12 Apr →
mirage13–10-0.038%12 Apr →
dust23–13-0.0335%11 Apr →
mirage13–11-0.0215%11 Apr →
dust213–2-0.024%10 Apr →
dust29–13-0.087%10 Apr →
nuke13–4-0.0212%6 Apr →
dust213–5-0.0211%5 Apr →
nuke2–13-0.050%5 Apr →
overpass13–90.0513%22 Mar →
overpass11–13-0.049%22 Mar →
mirage9–13-0.086%22 Mar →
dust213–8-0.0215%20 Mar →
anubis10–13-0.039%20 Mar →
overpass7–13-0.066%20 Mar →
ancient13–6-0.026%20 Mar →
overpass7–13-0.057%20 Mar →
overpass13–5-0.0220%20 Mar →
dust213–6-0.023%18 Mar →
inferno16–12-0.029%18 Mar →
inferno3–13-0.028%18 Mar →
mirage10–13-0.0212%16 Mar →
mirage4–13-0.070%13 Mar →
overpass4–13-0.046%13 Mar →
ancient8–13-0.0612%13 Mar →
overpass3–13-0.068%13 Mar →
mirage3–13-0.078%13 Mar →
mirage8–13-0.0216%13 Mar →
anubis3–13-0.053%13 Mar →
nuke10–13-0.060%13 Mar →
ancient8–13-0.0610%8 Mar →
overpass13–50.058%5 Mar →
overpass4–13-0.1212%5 Mar →
dust216–13-0.0121%2 Mar →
inferno7–13-0.1011%1 Mar →
mirage4–13-0.057%1 Mar →
nuke16–12-0.0510%1 Mar →
overpass9–13-0.087%28 Feb →
mirage13–11-0.050%28 Feb →
anubis13–8-0.057%28 Feb →
mirage13–8-0.0211%28 Feb →
ancient13–7-0.0117%28 Feb →
mirage13–10-0.0318%25 Feb →
mirage4–13-0.029%25 Feb →
inferno11–13-0.088%21 Feb →
dust23–13-0.0918%17 Feb →
ancient6–13-0.0414%17 Feb →
dust28–13-0.0813%16 Feb →
inferno8–13-0.067%16 Feb →
inferno13–6-0.0413%14 Feb →
dust25–13-0.0219%11 Feb →
inferno2–13-0.100%11 Feb →
inferno7–13-0.068%11 Feb →
inferno8–13-0.055%10 Feb →
ancient7–13-0.026%7 Feb →
nuke5–13-0.073%7 Feb →
dust213–1-0.0242%6 Feb →
mirage13–20.1112%5 Feb →
dust213–50.0914%3 Feb →
dust210–13-0.0715%3 Feb →
dust213–10-0.0817%1 Feb →
anubis5–13-0.007%1 Feb →
mirage5–13-0.054%1 Feb →
mirage8–13-0.0714%1 Feb →
anubis13–80.0117%1 Feb →
dust28–13-0.0713%31 Jan →
overpass8–13-0.0820%31 Jan →
dust28–13-0.085%31 Jan →
dust25–30.0232%31 Jan →
mirage6–13-0.0810%31 Jan →
mirage13–9-0.0113%31 Jan →

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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