Učinkovita uporaba statistike flashbang

Most stats we use measure a player’s performance in terms of their stopping power. A player’s kills, deaths, trades and so on on are all direct measurements of skill. But Counter-Strike is about more than clicking heads, and while it is not as obvious to use statistics to talk about indirect actions, they can be just as useful for developing narratives around a player’s skillset and value to their side.

Flashbangs are an obvious example. Watch any professional match, and one of the first things you notice is the utility. You and your friends might know a few ‘god flashes’, but it is nothing compared to the wealth of lineups available to be learnt by the pros.

Much of professional CS is about avoiding pure 50-50 gunfights. You can gain an edge with some elevation, a bit of movement, or, most effectively, having a teammate flash for you. This is not always possible, of course, and professional play has evolved to the point that players occupy ‘anti-flash’ positions — looking into a wall or the floor being the most common kind — as often as possible. Meta games have grown around this habit, such as throwing a bad flash to get an anti-flash opponent to turn around only for a second, good, flash to pop straight in their face.

To je komaj praskanje po površini - bliskoviti udarci so lahko prav tako odločilni kot oster strel s prvo kroglo v glavo. Torej, ali bi bilo treba vložiti več truda v merjenje tega vpliva in izročitev pohval igralcem, ki imajo največ? To je naš pogled v svet statistike flashbang.

Za začetek je tukaj osem igralcev z najvišjim številom asistenc na rundo v LAN-u letos v igrah med ekipami, uvrščenimi med 20 najboljših.

Na seznamu prevladujejo AWP-ji in IGL-ji, kar je logičen rezultat. AWP-ji običajno igrajo z zadnjega dela skupine in dajejo pripomočke, kot je flashbang, za podporo svojim strelcem, preden se sami aktivirajo, običajno kasneje v krogu. Tudi IGL-ji pogosto zavzamejo podporne položaje z AWP-ji, ki jim omogočajo, da se osredotočijo na radar in svoje klice namesto na nitni križec.

Združite obe vlogi in dobite Casper „AdcadiaN⁠“ Møller in Dzhami "⁠Jame⁠" Ali, dva AWP-IGL, ki sta dosledno elita v večini flash statistik. Ilya “⁠M0NESY⁠” Osipov je na četrtem mestu, kar ni presenečenje za tiste, ki so gledali njegov tok ali demo posnetke, kjer mladi AWPer vedno razkazuje nove trike za uporabnost, pa naj bo to še en enosmerni dim v oknu Mirage ali natančen pop-flash .

Vendar pomoč pri bliskavici ne pove celotne zgodbe. Pri kateri koli statistiki moramo vedno izenačiti priložnost, preden igralca primerjamo z nekom drugim. To se sliši zapleteno, vendar obstaja velika verjetnost, da to že storite.

In football, a striker is expected to score more goals than a defender, so to equate for a player’s opportunity to score goals, we would not take a striker scoring more goals than a defender as proof that the striker is a superior player. Ten goals for a defender is remarkable, but pretty average for a striker.

The same is true in CS. A support player’s 1.00 rating is actually pretty decent, but alarm bells should ring if your AWPer is around that range. Similarly, a 1.30 rating in a single map is pretty good, but a 1.30 rating over an entire year is a god-like level few have reached. So, there is a need to equate for opportunity, including ensuring similar sample sizes and the advantages a player’s role might give if we want to find out who throws the best flashbangs.

One answer is to go further than dividing a player’s flash assists by rounds, to instead divide it by total flashbangs thrown. Now, we can see what percentage of a player’s flashbangs directly lead to the death of an opponent. This makes it fairer, since a player who needs to buy an HE grenade every round (thus throwing fewer flashbangs) is still rewarded for having effective flashes relative to his role.

To je boljše, čeprav prinaša težave v meritvi, ki prej niso obstajale. Tako kot je ocena 1.30 na leto bolj impresivna kot na zemljevidu, je visok odstotek učinkovitih bliskov bolj impresiven, čim več flashbangov vrže igralec. Iz tega razloga bliskovne pomoči na met bliskavice ne bi smele v celoti nadomestiti bliskovitih asistenc na krog.

But, should we be using flash assists at all? HLTV’s flash assist statistic is more strict than Valve’s, with a scaling threshold based on how long a player was blinded for. This means that if a player was blinded for three seconds, any kill within those three seconds counts as a flash assist. This is useful in terms of accuracy, but it also means that flash assists are harder to get compared to in-game statistics.

Ko se nekaj zgodi le enkrat na vsakih deset rund - in ta številka je velikodušna, 0.10 bliskovitih asistenc na rundo je zelo impresivno - je težje ugotoviti razlike med igralci. Ista težava velja, ko gre za sklopke 1vX, zato je naš leaderboard za sklopke ne upošteva odigranih krogov.

Flash assists are also several steps divorced from the flashbang itself. A teammate can whiff on a completely blind player, netting you 0.00 flash assists per round. An opponent can get lucky and net a kill while fully blind. Your flash might fulfill a different purpose than a flash assist, perfectly delaying an enemy’s push for a crucial three seconds to allow a rotation to come in.

Flashes are versatile and their effectiveness is not completely covered by flash assists. Fortunately, it is not our only option: there is also the stat labelled as ‘opp flashed’ on our stran flashbang. This is the average time per round opponents were blinded by a player’s flashbang. So, it takes into account good flashes even if they do not result in a kill.

kadijaN je še vedno pri vrhu, a igralec kot Dmitry “⁠Sh1ro⁠” Sokolov izpade iz prve deseterice s samo 1.66s nasprotnikov. Tukaj lahko ti statistični podatki pomagajo pri pripovedih; sh1roje Cloud9 stran je bila na udaru kritik zaradi svojih slabih hitrih asistenc kot ekipa, ki so pogosto padle nizko v igri Lestvica FTU s samo 0.19 bliskovnimi asistencami na krog. Če to postavim v kontekst, kadijaN dobi bliskavico tako pogosto kot Cloud9‘s whole team gets two.

Kaj torej pojasnjuje to neskladje? Junak‘s proactive style, especially on CT-side, might put them in more situations where a popflash from kadijaN je uporaben v primerjavi z Cloud9‘s pragmatic, turtle-like approach to defence. But it also might be as simple as Cloud9 in sh1ro kupovanje manj bliskavic kot druge vrhunske ekipe — vsaka statistika potrebuje kontekst, da gre zraven.

One avenue here is to equate for opportunity even further, by only comparing a player to their teammates. Here are the players who provide the highest percentage of their team’s flash assists:

While interesting, this still doesn’t solve our problem. There is no single flashbang statistic that accounts for all of the issues raised in this piece. However, that isn’t that rare in stats. In fact, many a statistic needs to be presented in conjunction with another. We often do this automatically, like how 0.80 kills per round equals 24 kills in a 30 round game or how rating compiles several different metrics to make one easy-to-understand number.

Toda včasih je zbiranje več statističnih podatkov v eno številko manj vredno kot njihovo ločeno vodenje. Vsak statistični podatek vam lahko da košček konteksta, vendar le, če ga pogledate skupaj, dobite popolno sliko o tem, kako vsak statistični podatek vpliva na drugega.

To visualise this, here’s a scatterplot. On one axis is how many flashbangs each player throws per round, and the other shows how many seconds an opponent is blinded by that player’s flashbangs in each round.

Zdaj gledamo številke v ustreznem kontekstu. V zgornjem desnem kotu so prikazani igralci, ki so elitni z flashbangi, medtem ko so pod veliko večjim vzorcem, medtem ko igralci, kot so Marco “NaSnappi⁠” Pfeiffer in Lotan “PinSpinx⁠” Giladi are in a different zone for players who have very effective flashes but don’t throw too many.

To bi seveda lahko naredili za katero koli statistiko bliskavice; enako dragoceno bi bilo videti pomoč pri bliskanju v primerjavi s časom, ko so nasprotniki prejeli blisk, da bi videli, čigavi bliski so najpogosteje pretvorjeni.

Upajmo, da smo ponazorili razliko med gledanjem statistike ločeno in z ustreznim kontekstom. Preden zaključimo članek, dodamo še eno opozorilo: še vedno ne moremo statistično ugotoviti, kdo meče najboljše flashbange. Omenili smo že omejitve, ko gre za AWP-je in podporne, zadnja stran paketa, igralci, ki lahko vržejo več flashbangov.

But we are also missing a key part of the puzzle: Who found the lineup for the flashbang? Who designed the execute that the flash is part of? While it is often an IGL, coaches and analysts deserve credit for their team’s and player’s flashbang statistics too.

Igralec kot kadijaN se pojavlja pri vseh meritvah, tako da očitno dela nekaj drugega drugim igralcem. Toda od zunaj ne moremo biti 100-odstotno prepričani, da prednost ne krepijo analitiki, slog in nešteti drugi dejavniki.

To pomeni, da bi moralo biti pravičneje primerjati ekipe kot igralce, ko gre za bliskovito statistiko. Le da so ekipe, ki dosegajo visoke rezultate v hitrih asistencah, le redko najboljše ekipe na svetu.

In fact, there is a weak negative correlation between a team’s flash assists and round win percentage. Of the eight FTU stats (mutli-kills, opening kills, etc.) flash assists is the only one where our trend line slopes downwards.

Ekipe všeč Cloud9 imeli dosledno slabe bliskavice in prva razpršena diagrama je pokazala, kako FaZe‘s players actually seem to waste a lot of flashes, with Robin “⁠Ropz⁠” Kool, Finn "⁠Karrigan⁠" Andersenin Russel „WTwistzz⁠“ Van Dulken vse v rumenem kvadrantu. To nas pripelje do razpotja: Ali je najboljša ekipa na svetu slaba s svojimi udarci? Ali pa nam kaj manjka?

Slednji odgovor se zdi verjetnejši. FaZe so mednarodna ekipa z eksplozivnim slogom. Njihovi krogi so precej kratki, zato jim ostane manj časa za nanizane popolne božje bliske. FaZe, narisani proti vsaki ekipi, so pravzaprav precej povprečni za hitre asistence; blestijo v več ubijanjih, pretvorbi 5v4 in pretvorbi 4v5.

This is an important caveat to acknowledge before the final part of the article, where we take everything into account to create a ‘flash rating’ akin to opening kill rating, impact rating, and rating 2.0. Flashbang statistics, at the moment, cannot include all the necessary context.

Ekipe ne želijo, da bi vsak udarec, ki ga vržejo, oslepil sovražnika za tri sekunde ali dobil pomoč; granata je del mačke in miši, fake-heavy, meta. Torej, to ni dokončen seznam najboljših metalcev bliskov, niti ne poskuša biti. To je le zbirka igralcev, ki so dosledno odlični po teh treh merilih:

— Vrženi bliskavice na rundo
— Povprečni čas, ko so bili nasprotniki prikazani na rundo
— Flash asistence na krog

Kljub temu formula nekoliko prispeva k slikanju splošne slike o tem, kako dobro igralec uporablja svoje bliskavice, z igralci, kot so kadijaN, Jamesin Gabriel “AlleFalleN⁠” Toledo še enkrat nagrajen. Ponovno je viden naš trend AWP-IGL, na končnem seznamu pa je pet IGL in šest AWP. Vendar ne pozabite, da vpliv številnih bliskov ni vključen v to oceno.

Torej, ali bi morali bolj uporabljati statistiko flashbang? Morda; igralcem všeč kadijaN očitno imate spretnost z granato za 200 $ in si zaslužite priznanje za to. Toda njihov namen mora ostati pokazatelj stila: ti statistični podatki nam to povedo kadijaN uporablja svoje bliskavice, da dobi asistence in zaslepi svoje nasprotnike, vendar to ni edina možna uporaba. Nizka ocena ne pomeni, da igralec nepravilno uporablja svoje flashbange. Kot vsaka statistika je kontekst ključen. In to je lekcija, ki jo je mogoče uporabiti pri vseh meritvah, ne le pri tistih, ki zadevajo bliskavice.