General Information
About Us
We're a group of poker fans who have documented TV cash games like it's never been done before. Our current leading tool is our extensive Livestream Poker Tracker Database with exclusive data on all of the major televised cash game shows.
In the future, we'll be listening closely to user feedback on what poker tools they would like to see from us next! Most of the poker applications in our current industry are convoluted, difficult to use, and have ancient looking user interfaces. We believe that the poker community deserves better.
This section of the website is where you can find answers to commonly asked questions, as well as methods to contact the Highroll Poker team.
Contact Us
If you're interested in submitting an inquiry regarding partnerships, feel free to reach out to our email: [email protected]
For all other matters related to user support or to report errors on our site, please email us at: [email protected]
Tracker Database FAQ
What is Highroll Poker Tracker?
Highroll Poker Tracker records and organizes results data from broadcasted cash games from most of the major poker broadcasts. We're always looking for new data to include in our site, so our database will continously be evolving.
Highroll Poker does not track Sit-N-Goes (SNGs) or Tournaments. Our database only tracks televised and livestreamed cash games.
For a full list of the locations we offer, please visit our Livestream Leaderboards page.
I'm a player and I want to revise my profile information.
We're always open to requested changes by those who have profiles on our site! This may include information changes as well as requests to replace profile pictures.
NOTE: For profile picture changes, any image must be sent from the original intellectual property owner of the image. If you are unable to prove you are the owner of the image, we cannot use it.
Please feel free to send us an email at: [email protected]
I found an error! Who do I contact?
We actively monitor emails for users who report discrepancies or errors in the data we collect.
NOTE: The purpose of our site is to display results from what aired on the shows, and not to display data of hands that happened on the film set, but never reached the air. We are aware that off-camera there are large pots that can occur that never reach the viewing public. It is simply not practical to attempt to document this.
However, if you spot an error please feel free to email us: [email protected]
We appreciate your help in keeping our site accurate and up to date!
How we handle currency conversions
In order to simplify figure calculations in our database, we display all amounts in the U.S. dollar. However, this simplification carries some complications.
For example, on September 8, 2018, Triton Poker released Episode 2 of their Montenegro Short Deck cash game.
The blinds were 2000EUR/4000EUR. Utilizing currency conversion on date of broadcast, the blinds in USD were $2360/$4721. We simplify conversions for blinds to the nearest rounded figure to ease user access in filtering for different stake levels in our database. In this case, we rounded to $2500/$5000 post-conversion.
The currency conversion on this date was 1 EUR = 1.18 USD.
Player net winnings were then converted from EUR to USD using this exact conversion rate.
Why simplify stake levels?
We do this because if we don't simplify stake levels to the nearest rounded figure, our database (which allows for filtering of stake levels) would have a near infinite amount of stakes to categorize. This is not sustainable or user friendly. We are choosing to sacrifice marginal levels of accuracy in BB/hour calculations for the sake of a better user experience.
Can we make statistical conclusions on the data?
For the vast majority of players in our database, the answer is no.
Short term luck plays a massive role in determining the outcome of players at the table on these televised cash game episodes.
Over the long term, however, the better player(s) at the table will begin to demonstrate their positive expected value (+EV) by displaying potentially massive cumulative profits in their recorded session history over many hours of play.
However, when we say "long term" we might have a different definition in mind than what many may assume. In live poker, your typical winning player will have anywhere from a 1-5 BB/hour win rate. Assuming 20 hands per hour, 2BB/hour equates to 10BB/100 (read as: 10 big blinds won on average per 100 hands played).
Using the Primedope variance model below, we'll show you just how nasty luck can really be over relatively small sample sizes in poker:
Above are the inputted metrics: ~ 10 BB/100 (2BB/hour equivalent). ~ 120 Standard Deviation (on the higher side of variance, but more representative of livestream poker) ~ 2,500 hands (roughly 125 hours of live poker equivalent)
Above is 1,000 trials ran over the variance model inputs. Each line represents a potential outcome for the player assuming that the inputted win rates are actually true win rates.
Above are the variance model results and confidence intervals ran on the expected values of players winning at 10BB/100 (2BB/hour live poker equivalent) over 2,500 hands (125 hours of live poker play).
For this player who is winning at a rate of 2BB/hour, there is a 66.15% chance that they will actually show a profit after playing 2,500 hands (125 hours of live poker equivalent), and a 33.85% chance that they will actually lose money.
According to this simulation, the worst case scenario for this player is losing over 1,800 big blinds!
The above tables are derived from a simulation of 100 million hands. The table titled "Downswing extents" shows how often the player faced a downswing for at least the amount of BB (big blinds) in the associated row description. The table titled "Downswing stretches" shows how prolonged the downswings were for the amount of hands in the row item.
NOTE: The Primedope team clarifies that the above shown downswing simulation tends to underestimate the likelihood and extent of downswings. Our explanation for this is that human emotions often come into play during downswings which can greatly affect the quality of play of that player. A player on a downswing is more likely to play worse than their average quality of play, resulting in prolonged downswings even worse than what is simulated above compared to what a uniformly perfect player would experience.
Overall, we encourage you to try out Primedope's variance tool as it can be an eye-opener for how much luck is involved in poker over small to medium sample sizes of hands played. In general, the more hands that are played in a given sample size, the more we are able to make statistical conclusions from the data.
If you're a live poker player, use the following formula to convert your BB/hour winrate to BB/100 for the model input:
BB/100 = (BB/hour) * (100 / avg. # hands per hour played)