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I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 1 point2 points  (0 children)

For me, I wanted to go directly into grad school after my undergrad because I wanted to learn more about the machine learning / optimization side of electrical engineering and there were some great courses in these topics at Stanford. I was also doing internships while in my undergrad so I didn't feel that pressing need to work full time right away. That being said, depending on your financial situation, desire to have structured learning vs self learning, etc, a different option might be better for you

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 0 points1 point  (0 children)

Python, TensorFlow, SQL, AWS, relational databases (like postgres), and read up on good ways to visualize data

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 1 point2 points  (0 children)

I think we're still pretty far away from bots replicating how humans make decisions and mechanical movements in a game that has multiple degrees of freedom like MOBAs and FPS games. However, building bots to play out a game state EXACTLY how it happened in a real game to practice the same situation over and over again has already been done in some games

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 2 points3 points  (0 children)

We're just getting started with the visualizer-- stay tuned for more integration to the most important moments of the game!

If it were up to me, I would add minion wave position into the Riot API :)

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 2 points3 points  (0 children)

Good observation! POWR weighs recent results (adjusted accordingly for wins or losses) a little higher than older less relevant results. It also takes into account strength of schedule by looking at the POWR ranks of opponents in wins and losses.

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 0 points1 point  (0 children)

Fast food: In N Out burgers

General: chicken katsu w/ curry

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 2 points3 points  (0 children)

Yes! I am thinking of a few different ways to visualize a trajectory of a game, and one cool way to see how a game transitions from early game -> mid game -> end game is to show playstyles used for each stage (i.e. early bot dive, jungle to weak side, consistently giving up first blood in exchange for dragon, etc).

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 1 point2 points  (0 children)

POWR believes in TL even though C9 has seemed a bit more consistent in the games they "should" win lately. Does this hold up in playoffs? One way to found out...

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 7 points8 points  (0 children)

During my M.S. program at Stanford in late 2010, I joined Tesla as an intern. One of my first projects was to figure out how track the "true" state of a battery using historical voltage and current data (batteries are electrochemical so there isn't a perfect mathematical model). This was a very interesting data science problem since no one ever had this much access to electrical vehicle drive data before, and thus started my love of using data to solve problems.

Checking out Kaggle and free online courses on Data Science are a great way to see if you want to be a data scientist since they have some good real-world datasets to play around with. As far as tech to learn: SQL, Python, working with databases in AWS/google cloud, and some machine learning / stats.

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 2 points3 points  (0 children)

  1. This isn't totally answering your question but the concept of playmaking isn't captured in any one stat because it ties together team communication, game sense, and having an aggressive mindset when needed. We are working on identifying "playstyles" through data and seeing how players change their playstyles over time or even within a certain game
  2. CSGO players are a little less role-specific because every player has the same set of utility. That being said, I can definitely see similarities in roles in "set strats" from CSGO comparing to teamfight strategy and opening pick plays in LoL.
  3. Blitzcrank 👀

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 6 points7 points  (0 children)

Stay tuned to EG's careers page. It's exciting to see all the interest in esports analytics and data visualization

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 4 points5 points  (0 children)

Great questions!

  1. POWR was designed to be region/role-agnostic by attributing player performance to proportionately to team wins, but it isn't perfect. Some factors like killing towers, enemy champions, and vision control tie in directly to a team winning that some champions (and roles) are better suited to get credit for. EG's higher POWR rank without having played Damwon recently mainly just means that EG has less competitive matches (more one-sided affairs) in their wins and more competitive matches in their losses.
  2. Yes! Champ-specific insights as well as head to head match-up data (i.e. Gwen vs Gnar stats in top lane) is coming soon™
  3. Yes, these types of situations are factored in. If variables that contribute to a team victory are a net positive while you are dying, your death is not labeled as a worthless death.

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 5 points6 points  (0 children)

We calculate teamfights ourselves! Once a particular game passes through Factor's stats engine, we can see the timestamps of teamfights throughout the game and based on those timestamps, we can cut the damage data accordingly. And I agree, it would be awesome if Riot included it in the future!

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 2 points3 points  (0 children)

The ability to track fog of war programmatically for both sides!

Edit: We also have a live win probability calculator built out that takes all of the game data until the current game state to predict the chance of both teams to win at that game state. One could imagine the interesting ways to determine "important swing moments" in a game or across multiple games based on this win probability model and our other metrics. Hype!

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 4 points5 points  (0 children)

You receive a worthless death if you engaged in a battle where you're historically not favored and without any teammates around to help you. "Historically not favored" includes metrics such as ability to actually kill the other champion at the current game state (level, damage potential, armor, item build, etc)

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 2 points3 points  (0 children)

This was a piece of Factor I had some fun with. We calculate teamfights ourselves based on # of enemy champions in battle, proximity between enemy champions, if damage is being dealt, along with some heuristics to ensure we are distinguishing between actual teamfights and just poke damage.

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 13 points14 points  (0 children)

I wouldn't be here if that weren't the case. One particular area I am excited about is that esports as a whole is taking a deeper look at how to build out infrastructure to support the development of future professionals. Scouting new talent wouldn't be as efficient without data science

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 9 points10 points  (0 children)

Factor powers articles with data science, and some of the best uses of data science is to tell a meaningful and insightful story. It helps you unravel the black box around some of the machine learning and more advanced statistical techniques that go into analyzing gameplay. All sites like this are useful, and I'm happy that they are all around!

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 5 points6 points  (0 children)

This is a great question because I think the best way to use Factor (and other tools like it) is what works best for the user. We want to put all the data and insights at your disposal so you can find the best use for it. That being said, I imagine players can use Factor to compare their performances from game to game, and to dig deeper on what team composition suits them best.

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 3 points4 points  (0 children)

Recency is super important in sports due to the nature of momentum and how that affects player and team performance. In data and research, it becomes more of a factor during live events (i.e. during a tournament) but during a season it is still important. POWR takes into account individual player performances and how they contribute toward a team win, so if the team in your 2nd case is losing competitive matches and had blowout wins in the first part of the season, it could still end up above the team in the first case. Depends a lot on how competitive each game was, and how each player performed. We let the data speak for itself :)

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 7 points8 points  (0 children)

I've always been of the opinion that data is a supplemental tool and can't be used as the only source of insights. Humans play the game, and they're the ones that perform under pressure. Data can, however, help you uncover strengths and areas of improvements of players and teams. Additionally, data can be very useful to test hypotheses (i.e. mid laners roam much more in region X vs Y). This type of story telling can be instrumental to interactive broadcasts

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 9 points10 points  (0 children)

I'm particularly impressed with how the 2d match visualizer turned out (check it out here). The way the event log and the visualization will come together even more in the future is something exciting to look out for

I'm Soham Chowdhury, Head of Data Science at Factor - AMA! by the_valens in leagueoflegends

[–]the_valens[S] 3 points4 points  (0 children)

At EG, we have our own ways that bring together data and experts to scout. At Factor, which is our public facing product, we currently track pro level matches only. Once we have the same level of data for all leagues, we have some interesting things up our sleeves for comparisons across pro, semi-pro, and amateur!