Esports analytics, in depth
The Workshop exists because data without explanation is noise. A HLTV rating of 1.15 means nothing to a reader who does not understand how kills, deaths, assists, first kills, and clutch wins are weighted into the composite number. An economy round win rate of 18.4% tells no story until you understand that the average is 12.1% and the difference compounds over a best-of-three series. Every metric on Krontiv is supported by methodology documentation that explains what it measures, how it is calculated, and what its limitations are.
This section contains explainer articles, methodology deep-dives, and an FAQ for readers who want to understand the analytical foundations of esports data. Whether you are a casual viewer trying to make sense of broadcast statistics or a data professional evaluating our methodology, The Workshop is designed to meet you where you are.
Analysis pipeline
Collection
Match data from tournament organisers, broadcast feeds, HLTV, VLR, Liquipedia. Cross-referenced against multiple sources before entry.
Normalisation
Raw data standardised across titles. Rating systems aligned where methodology allows. Cross-title comparisons flagged with confidence intervals.
Analysis
Statistical models applied: weighted rankings, trend detection, map meta analysis, player performance profiling. Every model documented.
Editorial
Analysts write context and narrative around the data. No table without editorial framing. No stat without explanation.
Explainers
What Is HLTV Rating 2.0?
A composite CS2 player metric weighting kills, deaths, assists, first kills, clutch wins, and flash assists into a single number centred on 1.00.
Understanding ADR
Average Damage per Round: total damage dealt divided by rounds played. An ADR of 80 means nearly one kill’s worth of damage per round.
Map Veto Analysis
The game before the game: how teams ban and pick maps, what veto patterns reveal, and how historical data predicts map outcomes.
ACS Explained
Average Combat Score: Valorant’s primary individual performance metric, calculated from damage, kills, first bloods, and multi-kills.
Economy Rounds
The mathematics of saving and spending: expected value of buy decisions, loss bonus mechanics, and the decision tree of CS2’s economy system.
Cross-Title Rating
Can you compare CS2 and Valorant players? The methodological challenges, normalisation approach, and honest limitations of cross-title comparison.
Deep-dive articles
How CS2’s Economy System Creates Drama from Mathematics
Every CS2 round begins with a spending decision. The economy system creates a mathematical framework that generates narrative tension.
The International: 12 Years of Prize Pool Data
From USD 1.6 million in 2011 to USD 40 million in 2023 — tracing every year of crowd-funded prize pool data.
First Blood Wins: Opening Duels in Valorant
The team that gets first blood wins the round 68% of the time. Decomposed by agent, map, and position.
Methodology note
All statistical models used on Krontiv are documented in the methodology section of the database. We publish our data sources, weighting algorithms, normalisation methods, and known limitations. Where confidence intervals apply, they are stated. Where cross-title comparisons are methodologically risky, we say so. Transparency about methodology is not a feature of the platform — it is the foundation.
Frequently asked questions
“The HLTV Rating 2.0 explainer should be required reading. I’d been citing the stat for years without fully understanding how clutch wins weighted into it.”
— X.
“The map veto analysis piece taught me more about competitive CS2 than a year of watching broadcasts. The data behind ban patterns is fascinating.”
— Y.