How Good Is Good Enough?

Back in December’s “Why Not Rebuy?” article, I mentioned having trolled online tournament data to get an estimate of what the cashing percentage—more commonly referred to as in the money (ITM)—was for a good tournament player. Looking at the top ten players in a major PokerStars event ($10,300 buy-in) with 56,000 games between them, the ITMs were in the range of 13-17%.

Those kinds of statistics aren’t—so far as I’m aware—available anywhere for live tournament play. The venerable Hendon Mob poker database keeps fantastic records of poker cashes, but not all entries. Some interesting databases have come to my attention in the past couple of weeks, however, and I’d like to share what I’ve been able to glean from them.

WSOPdb.com has buy-in data gleaned from the PDF event lists posted on WSOP.com (available under the Reports tab for each event). It does a decent job of collating the data for each event and producing a list—searchable by player name—that shows entries for both 2011 and 2012, separated by year (events are automatically entered when the entrants list is available).

The Quad Jacks WSOP Database goes even farther, with a database searchable by event and player. Want to see the names of everyone who cashed in (or entered) the 2011 Event #5 Seven Card Stud competition? Want to see how much Phil Hellmuth has paid for buy-ins and how much he’s won this year and last? Easy-peasy.

Note: There are a few incongruities in both databases, which is only to be expected, considering that they’re generated by computer from documents that are themselves imperfect. There are some duplicate entries, there are some players with the same names and same home towns, there are players who listed (for whatever reasons) different home towns in different events, and players who cashed with no entries. I’ve tried to account for anomalies in the sample used for my analysis below.

You can see from the chart above that Hellmuth entered 28 events in 2011 and cashed five times (three of the listings and three of the cashes are from 2012). He was guaranteed to be cash-positive for the series after a second-place finish in the 2-7 Draw Lowball Championship, and his ITM for the series was 17.85%.

To determine a baseline for how well top players do in live tournament play, I decided to collate cashing and entry data from the Quad Jacks database (QJDB) and cross-check it with WSOPdb (I began my work before the 2012 WSOP began, which both were still undergoing some modifications, originally, I had to count the number of tournaments entered and cashed by hand).

My overall sample set consisted of every player who made the top nine in a 2011 WSOP event. Collation was done by “hand”, requiring a look at each of the 58 tournament pages in the QJDB and a count of cashes and wins from the player page for each of the top nine players in the tournament (unless the player was already in the database). This phase produced a list of 462 unique players who were in the top nine players of at least one event.

As a group, these 461 players entered 5,642 events and cashed in 1,059, for an aggregate ITM of 18.8%. The median ITM was 21.4%, however, because nearly a quarter of the players in the sample played fewer than five events. Players who managed to get to the final nine in an event usually made enough money that they could afford to buy their way into other tournaments or the Main Event, and many did. Even if they lost a chunk of their winnings (an eighth-place cash in a Limit Hold’em event might pay only about three times the buy-in for the Main Event), their ITM would be at least 25%.

I was mostly interested in statistics for top tournament players, folks who got lucky in a tournament or players moving up the tournament ladder who were making their annual stab at the WSOP with a smaller bankroll weren’t the “top of the field,” even if they were good players. To limit the sample set to only top players, I added another requirement: the player had to have entered 20 or more tournaments during the 2011 WSOP. This meant they needed to be successful enough to have a bankroll (or backing) that could absorb a minimum of $30,000 of entries (assuming all they entered were $1,000 and $1,500 events) and that they were serious enough players that they were at the WSOP for a minimum of three weeks.

97 players made the cut. It’s a group with famous names like Tom Dwan and Bertrand Grospellier in it (and infamous names like Allen Kessler). Maria Ho, Phil Collins, John Racener, Eli Elezra, Chris Moorman. They’re all there (although I believe Ho and Odette Tremblay, who took 9th in a $1,000 NLHE event, are the only women).

Although they’re just over 20% of the total number of players in the original sample, the 97 players with twenty or more entries played a combined total of 2,521 tournaments, nearly 45% of all the tournament entries for the complete sample. They cashed a combined 332 times, for an ITM of 13.2%, and the median ITM was 13.6%.

Why look at an aggregate value rather than individual statistics? It’s well-known that tournament play is notoriously variable. Players can do phenomenally well one year and brick out the next. Raw numbers can be incredibly deceptive, as well. The two players at the top of the list in sheer volume of events entered are George Lind (2/39, ITM: 5.1%) and Justin Smith (2/40, ITM: 5.0%). Lind played in the pricey ($25,000) Heads-Up NLHE tournament to start with and didn’t have any luck until Event #11, when he took second in an the $10,000 Omaha 8 Championship for $287,554. He spent another $130,000 on entries between that win and Event #55, the $50,000 Poker Players Championship, when he scored big again with a sixth-place finish for $300,441, ending up about $345,000 in the black for the series. Smith, on the other hand, with exactly the same ITM as Lind, didn’t have a profitable series. The number of events he played meant that he was in many of the same games Lind was in, so his outlay was similar, but his two cashes were a sixth-place in the $10,000 Limit HE ($71,897) and 116th in a $1,500 NLHE event (only $3,684), so he ended the series with a loss of over $166,000. So I feel it would be a mistake to make assumptions based on a single player—or even a small group of players—who had cashed in the WSOP.

The criteria I have established for this sample: players who have reached the top rungs of their peer group at least once by making what is essentially the final table of an event at least once and who have been tested repeatedly against the best of their peers by entering more than a third of the events at the poker world’s premier contest, should be rigorous enough for us to make some generalizations about the group, however. First, it should be pointed out that having a tournament ITM in the range of the top players in the world doesn’t necessarily make you profitable. If you’re spending a significant portion of your winnings from one tournament on the buy-in for a larger tournament, then your tournament play by itself probably isn’t profitable. A number of the players on the list fall into that category. They might have made up for losses in the WSOP during the year by other tournaments or cash play, but the series itself was a loser. In fact, of the 97 players in the study group, 40 booked losses for the series despite having one or more cashes. Of the 57 players in the group who finished the series in the black, most of them (33) were profitable only because of their largest win; Take it away and they fall into a hole of red ink. Two players were profitable, but just barely, in the black for probably (far) less than their expenses for food and/or accommodation.

One trend that was obvious throughout the work I did to collate this data was the influence of large buy-in events like The Poker Players Championship ($50,000), the Heads-Up Championship ($25,000), and the ten $10,000 Championship events culminating in the Main Event. Many of the players on the losing side of the study would have been in the black (or at least a lot closer to even) had they not played several of those events. Doubtless, many of them could afford to, because they could make up the money elsewhere, but it looking through the individual player statistics does provide an object lesson in bankroll management for those of us inclined to take a shot at a big game. Over and over.

A final note: These are only players who entered twenty or more events and made the top nine positions in an event. Undoubtedly, there are many more players who entered twenty events and had profitable years without making the top nine of an event (72nd place in the Main Event paid more than first place in the $1,500 2-7 Draw Lowball event). There are undoubtedly players who lost more than the players in the sample, as well, not having gotten one of the top prizes in an event during the year. But I think this group provides as good a look into the statistics of top poker players as I’m likely to get without access to the entire WSOP database.

Below is the sample of players who entered 20 or more events during the 2011 WSOP and placed in the top nine positions of at least one event, sorted by the number of events entered and the number of cashes.

Player Name Entries Cashes ITM
Justin Smith 40 2 5.0%
George Lind 39 2 5.1%
Roland Israelashvili 38 6 15.8%
Jason Mercier 38 5 13.2%
Tom Dwan 37 3 8.1%
Michael Mizrachi 37 1 2.7%
David Benyamine 37 1 2.7%
Ali Eslami 35 5 14.3%
Stephen Chidwick 35 4 11.4%
Phil Laak 35 3 8.6%
Bill Chen 35 3 8.6%
Scott Clements 33 3 9.1%
David ‘Bakes’ Baker 32 4 12.5%
Jacobo Fernandez 31 4 12.9%
Dan Kelly 30 5 16.7%
Nick Binger 30 3 10.0%
Fabrice Soulier 30 1 3.3%
David Chiu 29 5 17.2%
Justin Bonomo 29 4 13.8%
Bertrand Grospellier 29 4 13.8%
Alexander Kuzmin 29 3 10.3%
Eric Cajelais 29 1 3.4%
Shaun Deeb 28 6 21.4%
Phil Hellmuth 28 5 17.9%
David Sands 28 5 17.9%
Issac Haxton 28 4 14.3%
Chad Brown 28 3 10.7%
Daniel Makowsky 28 3 10.7%
Mclean Karr 28 1 3.6%
Brent Hanks 27 5 18.5%
Scott Seiver 27 4 14.8%
Matthew Smith 27 4 14.8%
John Racener 27 4 14.8%
Jeremy Ausmus 27 4 14.8%
Allen Kessler 27 3 11.1%
Chris Bjorin 27 3 11.1%
Humberto Brenes 27 3 11.1%
Phil Collins 27 2 7.4%
Steve Billirakis 27 2 7.4%
Gabriel Nassif 26 6 23.1%
Barry Greenstein 26 5 19.2%
Michael Binger 26 4 15.4%
Joe Tehan 26 4 15.4%
Andrey Zaichenko 26 3 11.5%
Josh Brikis 26 3 11.5%
Brandon Meyers 26 2 7.7%
Jared Solomon 26 1 3.8%
Matt Stout 25 4 16.0%
Dario Alioto 25 4 16.0%
Alexander Wice 25 3 12.0%
Alexander Queen 25 2 8.0%
Matt Glantz 24 5 20.8%
Eli Elezra 24 5 20.8%
David Baker 24 5 20.8%
Josh Arieh 24 5 20.8%
Vitaly Lunkin 24 4 16.7%
Michael Benvenuti 24 4 16.7%
Eugene Katchalov 24 3 12.5%
Alexander Kostritsyn 24 3 12.5%
Chris Tryba 24 3 12.5%
Matthew Waxman 24 3 12.5%
Maria Ho 24 2 8.3%
Dan O’Brien 23 6 26.1%
Victor Ramdin 23 6 26.1%
Samuel Stein 23 5 21.7%
Christian Harder 23 4 17.4%
Max Pescatori 22 6 27.3%
Shawn Buchanan 22 5 22.7%
David Bach 22 4 18.2%
David Pham 22 4 18.2%
Eric Froehlich 22 3 13.6%
Brock Parker 22 3 13.6%
Adam Kornuth 22 2 9.1%
John Hennigan 22 2 9.1%
Antonio Esfandiari 22 1 4.5%
James Vanneman 22 1 4.5%
Jonathan Tamayo 22 1 4.5%
Odette Tremblay 22 1 4.5%
Simon Charette 21 6 28.6%
Matt Sterling 21 4 19.0%
Allen Bari 21 4 19.0%
Hans Winzeler 21 3 14.3%
Daniel Hirleman 21 3 14.3%
Sean Getzwiller 21 3 14.3%
Andre Akkari 21 2 9.5%
Jeffrey Gross 21 2 9.5%
Ronald Lee 21 2 9.5%
Max Weinberg 21 2 9.5%
Chris Moorman 20 5 25.0%
Mitch Schock 20 5 25.0%
John Monnette 20 5 25.0%
Thomas Fuller 20 4 20.0%
Tyson Marks 20 3 15.0%
Ted Lawson 20 3 15.0%
Eric Cloutier 20 3 15.0%
John Juanda 20 2 10.0%
Mika Passonen 20 1 5.0%
TOTALS/AGGREGATES 2,521 332 13.2% average
13.6% median

Ill-Timed

I keep going back to The Final Table despite the fact that the only time I’ve ever cashed there was in the Santa Bounty game last Christmas. My ITM there is truly horrible, unless you limit it to events with 50 or more players, and then my rate’s pretty much the same as it is anywhere else in town with 50 or more players. The only event I cashed in there, I made it to the final table of 131 players. These two games show a screw-up and just plain bad luck.

The Final Table $1,000 Guarantee (T7,000)

Started off with the extra T1,000 because I signed up on-time. Picked up [kc tc] UTG with a flush draw on the flop of [ac 2c ad] and hit my flush with [5c] on the turn but it made a full house for my opponent who called with [ax 5x].

Made a least flush on the flop with [ad 3d] and took down a T3,000 pot about twenty minutes into the game, then went up against [kx qx] with [kx tx] and top pair on the flop. We both drew down to four spades on the board, which kept the pot smaller since neither of us had one. I was holding T8,350 after that hand.

[9s ts] and I made a jack-high straight on the turn. I bet 650 and shoved over a re-raise to felt a player half-an-hour in. T12,150 and I got moved to a newly-opened table.

Forty minutes into the game, I called 1,600 early with [jx tx]. Two pair on the flop and a full house on the river and I tripled up against two all-ins. Then I lost T6,000 almost immediately as SB drawing for a flush with [3d 5d]. [qx tx] made a full house on the turn. Three-quarters of an hour into the game and I was still sitting on T28,125, with the chip average at just T7,655.

Kicked myself a bit for folding [jx 6x] when I would have double-paired on the flop and hit a river boat in a hand with two players all-in.

Played [jx qx] and raised to 600, calling a re-raise to 1,800 pre-flop, then folding to an all-in on the [3x 3x x] flop. Down to T24,800.

Lost several thousand with [qs 7d] against [8x 9x] on a flop of [6x 7x 8x]. I had trips on the turn, but a [tx] river card made his straight.

Ten minutes later, I lost more than half my stack with [kx kx] again, calling an all-in against pocket sixes that made a set on the flop. I went into the break with just T7,825. The add-on more than doubled me up.

I called with [7c 4c] and hit the [9x 7x 6x] flop lightly. I bet 1,100 and got a call then hit my [4x] on the turn and managed to get an all-in called to take it down with two pair. That put me back up to T27,700, with the average at T17,733.

Raised to 1,000 from UTG2 with [ah 9h]. The flop was [7c 2c 7s] and I folded to a 2,500 bet.

Two hours in on BB with [qd 3h] and the flop was all diamonds. I called the bets down to the river to see another diamond and bet 2,300 to win without a showdown.

T33,525 at two hours and five minutes.

Raised with [ah td] to 1,200 and got four calls. Everyone checked it to the river which turned up a king. The BB won.

I raised to 1,500 from CO with [qh th] and got an uncomfortable [ax 9d 6d] flop, then folded to a 2,500 bet.

My next BB I had [ax kx] and re-raised to 3,800 from 800, getting an all-in from SB, which I called. He had [9x 9x], the flop was [ax jx 8] and the rest of the cards didn’t matter.

Two-and-a-half hours in and I was up to T34,450. Then I lost a chunk with [jc 5c] against [kx qx]. I was ahead on the [jx ax 8x] flop but running tens gave him Broadway. Ten minutes later, my stack was at T28,800 (average T26,600), there were 20 players left, with 17 re-buys and 29 add-ons.

With [4h 5h] from BB, I saw a [kx 2x 2x] flop then called a bet of 3,200 after the five on the turn. Another 1,200 went down the hole calling 1,200 on the river six. I was out soon after with [ax 9x] against [kx kx].

Three hours. 17th of 33 players.

Size Does Matter

Hearkening back to the discussion of median return on investment (mROI) from a couple months back, what tournaments should you be playing to maintain profitability?

The big determining factor is your in-the-money percentage (ITM). If you’re some sort of poker god and cash in half the tournaments you enter, you should be profitable, assuming your mROI is above 200% (i.e. you aren’t always min-cashing). When you’re in the more mortal realm of 12% to 18% ITM, however, the math gets a bit murkier.

Let’s assume you have a solid but not outrageous ITM value of 14%. You’re cashing in about one out of every seven games, not just small games but across the board including games with more than 100 players. If you’re playing in casinos where tips are taken out of the total prize pool, your mROI needs to be +600% or better in order to be profitable. If you’re playing in something like Portland’s social gaming clubs where the winning players need to tip the dealers in order to keep the scene going, your mROI needs to be +440% or better to stay ahead. As an example of the latter, if you enter a tournament with a $25 buy-in, a $10 add-on, and a $10 door fee, your payout needs to be about $350; pay $35 as a tip and subtract $45 for other costs, and the remaining $270 buys you the six tournament entries you don’t cash in. Although the overall mROI for social clubs is lower, the tip means that the prize has to be a higher multiple of the other costs (buy-in, add-on, door) for a positive average return (+677% in the example above).

A $350 payout for a $25 entry tournament is a fairly decent-sized prize, though. Depending on the prize structure, that’s more or less the top prize of a $1,000 guarantee tournament with 25 or 26 players. The median payout in a tournament that size would be less than $300; unless you got the top spot, you’d be dragging down your mROI.

This is why the Poker Mutant is focusing on larger fields, these days. Aside from a preference for the blinds structures of deep stack games, larger fields are simply the only way to maintain profitability. A tournament like the Encore Club’s $25K Guarantee earlier this month paid 12 places with a scheduled median ROI of +490% (the 9-way chop actually made the median ROI +1150%). But that required a field of 150 players.

Small-field tournaments in Portland—i.e. those with 20-30 players—pay about 45-50% for the top prize, with three or four places total paying (before any bubble agreements), and with the median payout in the range of 20-30% of the pot. The pot to basic cost ratio varies considerably depending on the tournament structure and club. An 11am $250 guarantee freeroll tournament at Portland Players Club ($5 door, $5 pre-add-on, $10 add-on) with close to 30 players can generate a pot to cost ratio of nearly 25:1 with a third of the players re-buying (I don’t include re-buys in basic costs because as I’ve explained, rebuys are the death of ROI). That means the median payout in those tournaments is approximately 625% of your basic cost. If you tip your dealer 10% of your 625% prize ($125), your ROI for the game is +285%, which sounds great, but only if your ITM is better than 26%. Of course, if you win the top prize in that tournament you’re doing better, but then if you cash in third you’d better be cashing in almost every game you play.

Games that induce a lot of re-buys, like the afternoon Pot Limit Omaha Hi-Lo tournaments at The Final Table ($10 door, $20 buy-in, $10 add-on), can change the math a little. It’s not uncommon for there to be nearly as many re-buys as original entries, which can juice the pot a bit. One game late last year had 28 entries, 21 re-buys, and 22 add-ons, for a $1,200 pot (30:1). That’s still not a great number, though, with the median payout at just under 16% ($190), for a potential ROI of only +222%; more money but not as high a return as the median payout in the PPC game. Again, the top end does better—+450%—but that’s just keeping your head above water for someone with an ITM of 14% (and it means you need to take first place every time you cash).

Is there a sweet spot? Is there a magic number that makes it more likely that your tournament cashes will be profitable cashes? So much of that decision rests on variables like re-buy and payout structures, but in Poker Mutant’s humble opinion—in the world of Portland poker rooms, at least—you’re more likely to be profitable in events with 75 or more entrants. Apart from the opportunity of winning a big stake if you take down the top prize, which can have a pot to cost ratio of 20:1 or 30:1, the average cash in a field of that size is large enough to maintain profitability for most above-average players. You’ll still find Poker Mutant at the tables for smaller games, but our focus is on those bigger tournaments for the time being.

Anyone heading down to Reno for the World Poker Challenge?

Moneycard

Here’s a little something for you stats junkies.

This data’s taken from the Encore Club’s posting of point leaders near the end of last month. Yes, I took a grainy snapshot of the top sheet when I was working on my post about median ROI and ITM the other day, then coded the basic number of tournaments entered and xash (or “place”) information into an Excel spreadsheet. This is what you get:

The point leader sheet doesn’t have any info about dollar values of cashes or field sizes (it does give the number of times the player made positions 1-5), so there’s no ROI calculation, but I’ve added the break-even median ROI for each ITM value on the vertical axis, just for reference.

So here it is. 46 live game players from a single venue in town over most of a month. The median number of games played is 21. The median number of games in the money is 6. The median cash percentage is 24% (yes, that’s different from the games ITM/games played; that’s statistics for you). The sample size is relatively small in terms of games played, but you can see a definite progression downward to the mean as the number of games increases.