We build a database, which means we spend a lot of time pointing it at datasets and asking increasingly difficult questions. Usually that ends in a benchmark. This time we pointed it at Dota 2 instead.

The result is Serene WYL, short for Why You Lost: a tool that takes a finished match and explains what happened from one player's point of view.

A scoreboard can tell you that you died six times, finished an item late or lost the last fight. It cannot tell you which of those things actually mattered, what led to them or what you could have done differently. WYL is built for that second set of questions.

Paste a match link, choose which of the ten players is you and start with the big picture. From there you can go as deep as you want.

From the match overview to individual decisions​

Serene WYL presents the same match at several levels.

Move from the match overview into draft, fights and build analysis.

The general analysis gives you a quick account of the game: how it developed, where momentum shifted and which parts of the match deserve a closer look. It is the place to start when you want to understand the game without watching the whole replay again.

The deep analysis looks at the decisions behind the result. It finds moments that changed your chances of winning, explains why they mattered and gives you a more useful answer than a list of end-of-match statistics. You can inspect the parts that matter to you and skip the rest.

The interactive 2D replay connects the analysis back to the match itself. Fights are collected in one timeline, and you can jump directly to any of them to see positions, movement and health change second by second. It is a compact way to reconstruct a game while keeping the important moments in context.

Jump between fights and inspect the match on an interactive 2D map.

WYL also reviews picks, builds and other match decisions in the context in which they were made. The goal is not to hand out universal rules. It is to show what made sense in this particular game and offer alternatives for similar situations.

How it works​

The flow is deliberately simple:

1. Paste a link to a finished match.
2. Select your player.
3. Read the overview, open the deeper analysis and jump into the replay wherever you want more context.

The conclusions come from the events in the match and patterns across real games. This is not an AI coach generating plausible-sounding advice. Every comparison is grounded in match data, and WYL shows the sample size next to the numbers so you can judge the evidence for yourself.

That matters because Dota is situational. A decision can be good in one match and terrible in another depending on the draft, timing, map and nine other players. Looking at one isolated number removes that context. Looking at many similar situations puts some of it back.

Why we built it​

SereneDB combines search and analytics in one database. A Dota match is a fun way to show what that means: a long stream of events, ten players making decisions at once and a simple result hiding a complicated story.

Serene WYL turns that stream into something you can explore at different depths. The overview summarizes the match, the deeper layers find the moments worth examining and the replay lets you return to the original context. It is the same basic problem we work on with other kinds of data: find what matters, measure it and make the result understandable.

The current version is a draft, and we already have many more metrics we want to add. We are running it in test mode for seven days during The International 2026. If players find it useful, we will keep it online longer and turn it into a deeper analytics platform.

Try Serene WYL, then tell us what it got right, what it missed and which analysis you want next. If you want to help us keep building experiments like this, star SereneDB on GitHub.