lead jerkoff researcher harvard

lead jerkoff researcher harvard — CS2 Stats

76561198317914401[U:1:357648673]Steam profile ↗

883Tracked matches52%Win rate2020Tracked since
1,617Hours in CS3Hrs last 2 wks
CSDB Rating5.0 DevelopingHybrid Rifler
FaceitLevel 5Top 67.6% of ranked FACEIT players
Ladder ranks via Leetify

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CSDB.GGlead jerkoff researcher h…FACEITLevel 5STANDINGTop 67.6% of rankedcsdb.gg/stats

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Performance scores

Aim66
Positioning47
Utility25

0–100 skill scores via Leetify.

Recent form

STEADY51427Last 10051%Win rateWLWLTLLWWW

Last 10 vs previous 10: +10pp win rate · -0.03 avg rating

Player DNA

Primary style: Hybrid RiflerAim-led profile without a single dominant tendency.

Aim6.6
Aggression5.7
Utility2.5
Positioning4.7
Opening Duels1.9
Clutch4.0

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.

Your pro match

NiKo

Plays most like NiKo 82% playstyle similarity

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

Where you differ: lower aim profile; 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.

Reaction time. 626ms 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

Aim6.6
Positioning4.7
Utility2.5
Mechanics6.1
Opening Duels1.9
Win Impact5.6

Composite 5.0/10 (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 -0.01 → last ⅓ avg -0.03
Reaction time620ms+25ms
first ⅓ avg 595ms → last ⅓ avg 620ms
Headshot accuracy19.1%+1.8%
first ⅓ avg 17.3% → last ⅓ avg 19.1%

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.

Highlights

0.11Best rating — nuke 13–5
133Biggest win — nuke
5Longest win streak
94In matches decided by ≤2 rounds

Map breakdown

anubisBest map · 67% over 9ancientWeakest map · 20% over 5
MapGradePlayedRecordWin rateAvg rating
dust2A2012860%-0.05
mirageA1710759%-0.02
nukeB115645%0.01
infernoA95456%-0.04
anubisS96367%0.01
cacheA95456%-0.01
trainC52340%-0.02
ancientD51420%-0.02
vertigoC52340%-0.02
office41325%-0.02
warden21150%0.02
fachwerk1010%-0.05
boulder1010%-0.03
overpass110100%0.01
alpine1010%0.05

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (20% over 5). Start with the 6 essential Ancient lineups, review the callouts, then spin up a practice server.

Lifetime stats

45,945Lifetime kills
1.06K/D · Top 50% of tracked players
2,181Matches
46.5%Match win rate · Top 50% of tracked players
33.3%Headshot %
9.3%Shot accuracy
4,259MVPs
905Hours (in match)
1,498Bombs planted
505Bombs defused

Most-used weapons

Lifetime map wins

3,336dust2
2,110nuke
2,048office
1,730train
1,289vertigo
1,282inferno
606cbble
173aztec

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

Faceit stats

Combat

158Matches
53%Win rate
0.84Avg K/D
68.5ADR
36%Headshot %

Clutches & streaks

40%1v1 clutch win
11%1v2 clutch win
7Longest win streak

Recent Faceit resultsLLLWW

MapMatchesWin rateAvg K/DAvg kills
Mirage956%0.9912.4
Dust2862%0.6110.4
Anubis580%0.9415.8
Nuke425%0.8412.5
Ancient333%0.9017.0
Inferno3100%0.8812.3
Overpass2100%1.3814.5
Train10%0.609.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

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

19.0%Headshot accuracy
31.0%Accuracy (enemy spotted)
42.3%Spray accuracy
77.7%Counter-strafing
9.5°Preaim
626msReaction time
42.0%T opening success
33.0%CT opening success
0.35Enemies flashed / flash
0.5%Flash assists
9.81HE damage / grenade
2.95Flashes / 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 0.346 — below the 0.5 mark we flag

    Grenade Lineups
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 32.9807% — below the 40% mark we flag

Spend your practice time on Ancient

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

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
dust213–11-0.0618%18 Aug
mirage9–130.0419%15 Aug
office13–6-0.000%15 Aug
inferno4–13-0.0818%15 Aug
dust212–12-0.087%15 Aug
train3–13-0.1323%15 Aug
anubis8–130.0219%10 Aug
nuke13–6-0.0226%10 Aug
mirage13–6-0.0714%10 Aug
dust213–8-0.0620%10 Aug
inferno12–120.0117%3 Aug
cache13–9-0.0122%3 Aug
dust210–13-0.0715%29 Jul
office5–13-0.0624%29 Jul
inferno13–50.1112%29 Jul
anubis13–70.009%29 Jul
train5–13-0.0319%29 Jul
mirage13–5-0.0312%29 Jul
train12–120.0218%28 Jul
dust26–13-0.0432%28 Jul
cache13–10-0.0023%28 Jul
nuke13–100.0223%24 Jul
anubis13–60.0327%22 Jul
dust213–9-0.0621%22 Jul
mirage2–13-0.0619%22 Jul
fachwerk4–13-0.0522%13 Jul
boulder5–13-0.0315%13 Jul
ancient7–13-0.0437%12 Jul
inferno5–13-0.0814%12 Jul
cache13–11-0.0024%12 Jul
anubis11–130.0114%12 Jul
cache12–120.0120%6 Jul
mirage13–7-0.0324%6 Jul
dust213–4-0.0929%6 Jul
inferno13–100.0221%8 Jun
dust22–5-0.0613%8 Jun
ancient12–12-0.0819%8 Jun
mirage13–7-0.0620%7 Jun
anubis9–13-0.0234%7 Jun
train13–100.0353%7 Jun
inferno11–13-0.0912%4 Jun
nuke13–50.1131%4 Jun
dust210–13-0.0616%1 Jun
train13–11-0.0117%26 May
vertigo9–130.0326%25 May
nuke9–13-0.0028%25 May
anubis13–8-0.014%20 May
mirage13–90.0220%19 May
inferno13–11-0.039%18 May
dust213–8-0.0112%18 May
mirage12–12-0.0322%16 May
dust29–13-0.0919%15 May
nuke5–130.0221%15 May
office9–13-0.0011%15 May
cache9–13-0.0118%15 May
mirage13–7-0.028%9 May
cache13–11-0.0111%9 May
office5–130.0128%4 May
mirage5–130.0120%4 May
nuke10–130.0218%3 May
cache2–13-0.0411%3 May
inferno13–11-0.1123%3 May
dust213–4-0.0624%3 May
cache8–13-0.0517%3 May
cache13–4-0.0116%2 May
ancient9–13-0.0326%22 Apr
dust27–13-0.0129%22 Apr
mirage13–11-0.0111%21 Apr
vertigo13–40.0113%17 Apr
mirage11–13-0.0216%15 Apr
overpass13–60.0121%15 Apr
mirage13–9-0.0015%13 Apr
dust213–11-0.0416%13 Apr
inferno13–10-0.0823%13 Apr
mirage7–13-0.087%10 Apr
anubis13–11-0.0116%10 Apr
mirage13–8-0.0110%9 Apr
nuke13–30.0318%9 Apr
ancient13–90.0728%8 Apr
warden1–5-0.0025%8 Apr
vertigo10–13-0.0325%8 Apr
warden13–70.0412%7 Apr
anubis13–90.0414%7 Apr
dust213–3-0.0427%7 Apr
nuke10–130.0112%7 Apr
vertigo6–13-0.0719%7 Apr
dust213–10-0.0222%7 Apr
vertigo13–8-0.0217%6 Apr
nuke8–13-0.0419%6 Apr
dust213–6-0.1024%6 Apr
mirage8–0-0.0314%6 Apr
nuke13–5-0.0113%3 Apr
dust213–7-0.0217%3 Apr
anubis13–3-0.0113%3 Apr
dust212–12-0.0124%2 Apr
dust212–50.0526%1 Apr
nuke1–13-0.0712%31 Mar
ancient10–13-0.0315%31 Mar
mirage11–130.0413%30 Mar
alpine9–130.0516%30 Mar

Match data via Leetify.

Recent teammates

Milestones

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