Return on Investment
The most important statistic for tournament poker results is return on investment. It’s a simple figure for how much you are expected to make on average per tournament, expressed as a percentage of the average buy in. So imagine you had played 100 tournaments with a £100 + £10 buy in and your total winnings was £15,000; your return on investment, or ROI would be:
£110 x 100 = £11,000 [total investment]
£15,000 – £11,000 = £4,000 [gross win]
£4000 / 100 = £40 [average win]
£40 / £110 = 36.4% [ROI]
Just how many tournaments one needs to play to get a reliable ROI figure is moot, but it’s certainly in the thousands. This is a bit of a shame because very few players will ever play that many live tournaments in their lifetime. Hence, reliable ROI figures are – especially for live play – difficult to estimate.
Nevertheless, I’m going to try to give that a go in this article. There are several reasons for wanting to know what the ROIs of winning players. First, it creates a good cross comparison for players who already know their (more reliable) win rates for cash games, and second, it means that players wanting to stake others can get an idea of (quite literally) the return on their investment. Many a player has been flamed on an internet forum for charging a premium to stakers which is actually – so the flamers claim – in excess of their ROI.
As I’ve detailed in other articles, a player’s ROI is determined by several factors, mainly how much better they are than their opposition, how many runners there are in the tournament, and how the prize pool is distributed. These factors also affect the reliability of the ROI figure.
It should be noted that there’s an inherent bias in the ROIs I’m going to look at. I’m interested here in the ROIs of the best players out there: the Chris Moormans and Sam Tricketts of this world. It stands to reason that these players will have good ROIs because of their outstanding tournament resumes. Remember that in other universes there are Jake Codys who didn’t win the triple crown in under 18 months – and their ROIs will be lower. Hence, the figures I come up with will be optimistic.
There’s actually an abundance of information out there for online tournament results. There are online tournament rankings such as Pocketfives.com as well as websites such as Bluff’s own thepokerdb which gives geeks like me a whole host of information – most importantly, a record of the tournaments each player has entered as well as their winnings.
To get a flavour of what a great ROI is for an online player, I’m just going to select a few well known players and query their results for both Stars and Full Tilt (FTP). Although the latter has been defunct for some months now, it was by some distance the second biggest tournament website after Stars, so we should get some big sample sizes from there too. These figures were all taken from Bluff.com’s thepokerdb.
Let’s start with a player who currently sits in 8th place on the Pocket Fives rankings and is recognised as one of the best online MTT players in the UK: Toby Lewis. On Stars Toby (as “810ofclubs”) has played 4,433 MTTs with an average buy in of $178 and has won $1.3m. His ROI there is 52.4%. On FTP he played 2,231 MTTs winning $0.5m for an ROI of 18.7%.
Even though Toby’s played thousands of MTTs, the variance in his results is such that his ROI on Stars is almost triple that of FTP. Is Stars a fishier site? Certainly, the maths dictate that even a few thousand MTTs would not be enough to overcome the effects of variance. Don’t forget that most of these tournaments have thousands of runners; hence, the difference between binking a win for anything up to a 1,000 buy in pay day rather than coming 9th for about a tenth of that would register significantly over such a “small” sample size. Let’s have a look at a couple of other players before leaping to a conclusion.
At present the Pocket Fives leaderboard is topped by Griffin “Flush_Entity” Benger. He has played almost 7,000 MTTs each on Stars and FTP, so perhaps his two ROI figures are more consistent? He’s played 6,730 MTTs on Stars for an ROI of 52.9%. On FTP he’s played another 6,984 MTTs for a considerably smaller ROI of 28.6%. Evidently 7,000 MTTs is not enough to reach the long run when the field sizes are this big . . .
Last but not least, we turn to the mother of all MTT players. The online phenom who many would claim is the best ever – Chris Moorman. With over $7.5m in online winnings, and having played upwards of 25,000 MTTs online, his figures will surely be the most reliable. Chris (“MoormanI”) has played 11,691 MTTs on FTP for an ROI of 56.7%. On Stars (“Moorman1”) he’s played a whacking 12,779 MTTs for an ROI of 33.0%. First, this dispels any thoughts we may have had about on site being fishier than the other – Moorman has actually been more successful on FTP than Stars. Second, it shows that, rather dauntingly, when fields of thousands of runners are concerned, and even given the clear edge that a player of Moorman’s pedigree must have, even 12,000 MTTs is not enough to give a reliable ROI figure.
That said, we can say with a degree of certainty that a great ROI for high stakes online tournaments is around the 40%+ mark. With the average buy in being around $200, it means that Moorman’s average expectation per tournament is around $70-$100. Given that these players usually play in the region of a dozen MTTs at once, that’s a pretty decent hourly rate. One might well post a better ROI if one was playing fewer tournaments, but the hourly rate would definitely suffer.
A decent player can have a much larger edge in a live tournament. When the drunk guy in the nice shirt sits at your table, you can get to work on him right from the first hand. And when you see them in the flesh, you can get a lot more information about the players behind you when you’re considering flatting a raise from a loose player in early position. Gaining information for these situations will take much longer online, if it happens at all.
If we struggled to get a reliable ROI figure from a sample size of 12,000 online MTTs, we may well give up before we’ve started for live tournaments. There may be players out there who play 300 tournaments a year (though not major tournaments as it would involve too many day 2s and too much travelling). Such a player could manage 10,000 live MTTs in a lifetime – and maybe that’s enough to reach the “long run”, but we’d have to take their word for it as to what their ROI was.
The best we can do is combine the results of a number of players and hope that their collective results represent a decent enough sample size. This won’t be reliable at all, but it may give us a ball park figure.
The only database I know for live results which includes tournament entries as well as cashes is Sharkscope.com’s live events database. Sharkscope has recorded all WSOP entries since 2010, the entire history of the WPT, as well as the odd poker tour such as the Aussie Millions 100k, the PPT and so on. The resulting database is still pitifully small in terms of sample size, but it does make for some great reading.
As a benchmark, for each of Daniel Negreanu, Phil Ivey, John Juanda, Phil Hellmuth and Barry Greenstein, it has about 150-200 entries recorded. Three of these players have ROIs of around 80% and two of them around 200%. Don’t forget the sample is tiny and, much more importantly, it is a tremendously biased sample. We’re querying the results of players who have already proven to be successful. We can’t say for certain whether it was luck or skill – for that we’d need to be a bit more scientific by making some predictions for future results. Nonetheless, it’s a start.
For the next exercise, I took the top twenty players on the England all time live MTTs rankings on Hendon Mob. I queried their results using Sharkscope. Without naming names, some have positive ROIs (in this particular dataset) and some have negative. Summing all their results together yields a dataset of 666 live MTTs entered and an ROI of 258%. Once again this is an incredibly biased dataset – these guys are at the top of the ranking list precisely because their results have been good. For example, if we were to remove the player with the highest ROI in this dataset (Praz Bansi – who having won a bracelet in a large field event in 2010 has a massive ROI of 1369%!), the combined ROI of our sample drops to 212%.
I would imagine that to get a decent sample size would take tens of thousands of MTTs – certainly if we are to include big field events such as EPTs and WSOPs in the sample. That’s a shame because no player can achieve that in a lifetime. Hence we can only guess as the ROIs of some of these winning players.
While I think it can be argued that certain great players have ROIs of 200% or more, I personally don’t believe it. My best guess is that good live players can expect to have ROIs of around 50%-100% and the odd truly great player (I’m talking Ivey, Negreanu, Mercier) can be pushing 150%. In terms of hourly rate, this is still great. A $5k WSOP for example should yield a profit of $5k for a 100% ROI player. Subtract a daily rate for hotels, travel and other expenses, and we’re still talking over $1k per day win rate.
Whenever I’ve considered this in the past, I’ve always come to the same conclusion: unless you’re a poker god with a great ROI and a bankroll big enough for you to be comfortable in the big (£1000+) events, live tournament poker might be best viewed as a bit of a laugh, a chance to get out and meet people, rather than a solid investment of your time.
As for online, the costs are obviously much smaller, but then so are the ROIs of the true greats. But do remember: if the sample size that Chris Moorman has posted in his MTT career isn’t that accurate, then don’t be posting any ROI figures on the internet just yet.
This article first appeared in Bluff Europe magazine.