Poker ICM 101: What is ICM poker? ICM poker term explained
“..it does it so well that practically all of the consistently big
winning players in MTTs and SitandGo’s use it to guide their play in
critical situations. It has proven to be the most accurate model time and
time again, and in a competitive field where millions of dollars are up
for grabs, that’s saying a lot”
Contents
 ICM poker term definition
 Why do we use ICM In Tournament Poker?
 The effects of Bubble factor, ICM factor and The Varying Effects of ICM Pressure
 Using ICM to design optimal strategies
 Flaws in the poker ICM model
ICM Poker Definition
The ICM poker term stands for the Independent Chip Model.
In poker ICM allows you to convert tournament players stacks in chips into their
money equity (as percentage of total or remaining prize pool).
ICM can be used to perform fair chops on the final table of a multitable
poker tournament or to compare the monetary values of making different decisions
within a game.
In essence poker ICM is the function of two parameters: a list of payouts and a list
of the chipstacks within the tournament, and it ignores things like skill advantages,
position, and the size of the blinds. ICM uses this information of the payout list
and the list of chip stacks to output a list of corresponding dollar values for each
stack which are representative of their equity share of the remaining prize pool.
Poker ICM equity can be easy to understand in the context of a final table chop—it
would allow each player to figure out what part of the prize pool goes in their pocket
if the tournament had concluded at that moment with no further play, and that amount
should be the same, on average, if the tournament played out to the end.
There exist various poker ICM models which differ from each other by their approach
to calculating the probabilities of each stack finishing at each potential position.
The most popular and proven ICM poker model that is generally considered as the ICM
poker model is the MalmuthHarville model.
Why do we use ICM In Tournament Poker?
When you play in a cash game the value of your chips is constant, they represent a
dollar. So every $1chip is worth exactly $1, and your goal is simply to get as many
of them as you can. But when you play in a tournament things aren’t so simple.. Let’s
consider a simple example:
3 players enter a tournament with a $100 buyin (ignoring the rake), they each get
100 chips at 5/10 blinds, and play for a prize pool of $300 split $195 for 1st place,
$105 for 2nd, and $0 for 3rd.
In the first hand Player 1 folds the button, Players 2 shoves allin, Player 3 calls,
loses the hand, and is out of the tournament.
Before the game each player paid $100 for their 100 chips, and all things being
equal, obviously has an equal 1/3rd chance to finish in any of the 3 positions.
You might think that those 100 chip stacks are worth $100 and by that logic each
1 chip is worth $1, but let’s think about what happened here.
Player 3 lost his 100 chips, and the $100 he used to buy in, and Player 2 doubled
his starting stack, but did he double his equity in the tournament? No. Player 2 has
secured a 2nd place finish, and the $105 that goes with it, and given himself a 2:1
chip lead setting himself up as the favorite to win the match. But notice that even
if he does win the entire tournament he would not have even doubled his buyin equity
of $100, as first place only pays $195 and he is still not guaranteed to win
So what happened to the remaining equity? It went to Player 1, who hadn’t won
or lost a single chip but had increased his starting equity of $100 to a situation
where he has locked in a minimum prize of $105 for 2nd and has at least a little more
equity than that since he still has a chance to play for first.
So the value of tournament chips isn’t constant, their value is tied to your
ability to use those chips to win money from the tournament by finishing in the
paying spots. And that depends on a lot of factors such as your relative skill over
the field, the payouts, number of players, their stack sizes, positions,..., and
on and on. It’s really rather complex, and it’s not possible to account for all
of the factors at play to make the best decisions, so we need some way to approximate
the value of our chips and chips added to and taken from our stack  this is exactly
what ICM does, and it does it well.
In fact it does it so well that practically all of the consistently big winning
players in MTTs and SitandGo’s use it to guide their play in critical situations.
It has proven to be the most accurate model time and time again, and in a competitive
field where millions of dollars are up for grabs, that’s saying a lot!
The effects of Bubble factor, ICM factor and The Varying Effects of ICM Pressure
The restrictive effect that tournament equity considerations have on a player’s range of
playable hands is commonly referred to as “ICM Pressure”. As the risk of losing higher
than average equity becomes greater, and proper play dictates playing tighter ranges
relative to purely chipEV (like cash game) poker, a player is said to be under “high
ICM pressure”.
When that risk is lower, and proper ranges become closer to chipEV, the player
is said to have “low ICM pressure”.
The amount of pressure can be measured by the distance between the odds needed for
a play to show a positive value in chips and the odds needed for a play to show a
positive value in $ or ICM Equity (real monetary value).
This distance is referred to as “Bubble Factor” or “ICM factor” and can be used to
figure out the range of hands which can be played profitably by determining if they
satisfy the ICMFactor odds requirements against an opponent's range.
As an example consider a 9player tournament (1st3rd places pay 50%,30%, 20%
of the total prize pool) bubble, 4 handed with the following stacks:
To simplify, let’s ignore positions and blinds for now.
In the images below we can see the exact resulting poker ICM EV’s of certain players
winning or losing allins against each other.
With 37.31% of the tournament's prize pool in expected value  players’ B1 and
B2 clearly have the most equity in this tournament. However, an allin confrontation
with one another could eliminate one of them from the tournament costing them all of
that equity, and because of this they need much better odds to risk their stacks
against each other than they would against players S or M.
Player S, at 4.39%, has so much less equity than all the other players that he has
the least to lose and the most to gain by getting into a confrontation with any player,
but he would prefer to get into confrontations with M rather than B1 or B2 since
when he doubles up through M he brings himself closer to being the 3rd stack than
if he doubled through B1 or B2.
Player M is the middle stack and with 20.98% has considerably less equity than B1
or B2 but considerably more than S and so he is very unwilling to clash with one of
the big stacks, where he could be eliminated when losing but still remain the 3rd
stack by winning, and much more willing to clash with the shortest stack.
Here we see that ICM Pressure is very high for confrontations between B1 and B2,
and between M when confronting B1 or B2, and that ICM Pressure is low for B1 or B2
when confronting S or M, for M when confronting S, or for S when confronting any of
the players.
Using ICM to design optimal strategies
Now that we know about what ICM does and how to calculate it we can start using it
to plan our strategies in tournaments. We do this by using the ICM equity conversion
to compare the difference in expected value (“EV Diff”) of our stack between our
options of folding or playing (in all of the various ways) the hands we’re dealt.
Tournament: 6max SnG
Payouts: 1st  $65, 2nd  $35, 3rd  $0
Blinds: 100/200
BTN: 4,000, SB: 3,000, BB: 2,000
Preflop: Big Blind is dealt KQo
Button shoves allin, Small Blind folds, action on the Big Blind
and let’s assume the Big Blind has good reason to believe the Button is shoving
the following range
{22+,A2+,K5s+,KTo+,Q7s+,QTo+,J8s+,JTo,T8s+,98s,87s}
Using a basic equity calculator (or the Detailed Result view in ICMIZER) we can see
that against this Button’s shoving range the Big Blind’s KQo will win 46.74% of the time,
tie 3.53% of the time, and lose 49.73% of the time when he calls the allin.
A quick sidenote  If this were a cash game hand we’d simply look at our odds of calling
1,800 chips into a pot of 2,300 to see that we need 43.9% equity to profitably make the call,
and clearly being over that number here we can see this is a +chipEV call, but tournament
poker isn’t as easy to solve.
So 46.74% of the time ending stacks will be [BTN: 2,000, SB: 2,900, BB: 4,100] and
3.53% of the time when BB and BTN tie to chop the Small Blind’s post they will be
[BTN: 4,050, SB: 2,900, BB: 2,050]. The 49.73% of the time that BB loses the allin his
$EV will, obviously, be $0.
We can plug all of those ending stack setups into our poker ICM calculator to see the ICM_$EV of
each result, multiply those EV’s by their probability of happening, and sum those numbers
up to get our overall ICM EV of calling the shove.
Readers are encouraged to do the work on their own (open basic ICM calculator
to do these poker ICM calculations for free) but I’ll include the results below without maticulous
detailing of the process

EV (% prizepool)

Probability

Win:

41.75

46.74

Tie:

25.12

3.53

Lose:

0

49.73

Multiplying each ending stack’s EV by its probability of happening and summing
those numbers we can see that the overall EV of calling the shove with KQo is
(0.4175 * 0.4674) + (0.2512 * 0.0353) + (0.0 * 0.4973) = 0.20400686 = 20.40 EV
Now that we know the EV of calling the shove with KQo we need one last bit of information
to determine what our most profitable move is  do you remember what that piece of information
is? Take a moment to think about it before reading on.
The last crucial piece of information that we need to account for is the expected value of
our fold. Without knowing the EV of fold we would have nothing to compare the EV of calling
the shove against.
We’ll note that if the BB folds to the Button’s shove he loses his post of 200 chips and
we have an ending stack setup of [BTN: 4,300, SB: 2,900, BB: 1800] and ICM tells us that this
setup gives the BB player an EV of (EV Fold: 22.73%) and we can compare that to (EV Call: 20.40%)
to see that BB should clearly prefer to fold this hand as it is worth (22.73  20.40) = 2.33% of the
prize pool more than calling, and to a less experienced player 2.33% may not sound like much but
in reality this is an absolutely huge amount of equity  representing more money in one decision
than the biggest winners in 1table SnGs make in an entire game on average  let’s make sure we
pick the right side of this decision as often as possible.
In cash games this calculation of comparing the EV of playing a hand to the EV of folding
a hand is so trivial that it’s easy to forget that we do it at all  when a cash game player
is out of the blinds he just needs to outperform his $0 from folding, and when in the blinds
he needs to outperform the loss of his posted blind when he folds. But, once again, we see
that things aren’t so easy in tournament poker.
In fact the example we used above is actually as easy as it gets in tournaments.
Finding our EV of fold wasn’t as simple as merely the chips posted for the big blind and
rather had to be calculated using the ICM poker model, but there was only one resulting
stack setup because the BB’s fold closed the action.
If we were to look at the Button’s decision when comparing his EV_Push to EV_fold we
would need to calculate for all of the possible ending stack setups after he folds
including: SB Push / BB Call [win/tie/lose], SB Push / BB Fold, and SB Fold.
And even still, that is just for calculating the simplified push/fold game, to truly
calculate the real world game the button would need to consider the sum of all of the possible
ending stacks even after his fold  even including when the small blind limped or raised non
allin and both of those players saw a flop, and then for every possible ending stack setup
for every postflop decision.
Luckily, many important situations in tournament poker actually are purely push/fold or
are close enough that push/fold models will still be very valuable  but my point in writing
this is to say that tournament poker ICM considerations don’t stop at push/call decisions, they
always exist, after a fold and even in postflop play so a player should make great effort
to always be aware of its effect when making decisions.
Flaws in the poker ICM model
ICM is a wonderful model, but it isn’t perfect. Before we conclude this article
let’s talk about the shortcomings of the poker ICM model.
ICM Assumes The Game Ends Now
Solving the true EV’s of any play in a poker tournament would require knowledge
of how every possible hand in the tournament from this point until every possible
conclusion would play out for all of the remaining players. This is clearly far too
complex for there to be any hope to model in any but the most incredibly elementary
situations, so we turn to models which simplify the game and that is exactly what
ICM does.
Tournament poker ICM simplifies the impossibly complex real world game into a
much simpler game, a game where everything stops and every player is simply paid,
right now, his share of the tournament prize pool based entirely on his and every
other player's stack size. ICM ignores relative skill, position, blinds, or really
any poker actually being played.
So ICM doesn’t consider that the UTG player will be posting a big blind next hand,
or that blinds are going up in 2 hands  in fact ICM doesn’t even know that there
are blinds in this game at all! ICM doesn’t know that the player in seat 2 is tilting,
player in seat 5 is sitting out, or that you are, obviously, the best player in the
world on a table full of donks and fish.
ICM simply gives us a model to estimate the value of a stack of chips, and then we
use those estimated values to compare the different plays we can choose from by modeling
a real hand of poker, accounting for blinds and skill (ranges chosen) for that one hand.
But at the end of that model for that one hand, once again, everything stops and all
players are just paid their ICM equity of the prize pool and all of the information
that exists in the real world (skill, rotating and increasing blinds, etc) is ignored.
Let’s take a look at one last hand example, an extreme yet common case on the bubble
of a 6max SnG  where the SB is considering a shove into the chipleading BB, while the
short stack button player has only one blind left  to see how a single poker hand
modeled with ICM suffers from the ignorance of rotating blinds.
Tournament: 6max SnG
Payouts: 1st  $65, 2nd  $35
Blinds: 100/200
BTN: 200, SB: 1,500, BB: 2,000
Preflop: Button folds, Action on Small Blind
To speed things up we won’t be doing any work by hand here, we’ll just look at the
results of an ICMIZER calculation and assume a NASH calling range for the big blind.
At equilibrium in this push/fold game modeled with ICM, the BB will call an SB shove
roughly 12% of the time and so the SB shoves about 40%. Certainly there is merit to
the SB shoving some hands  the BB is forced to fold often and the the 300 chips in
the middle represent a decent chunk of equity. Looking at this result things may not
seem so strange, but if you think about what ICM considers and what it does not it
will become immediately apparent that there is a flaw that requires an obvious
adjustment.
ICM assumes that, at the end of the hand, all things are equal and everyone gets
paid their ICM equity share of the prize pool. So in this example it assumes that
the BTN is going to get paid at the end of this hand based on his 200 chip stack.
But all things aren’t equal, and we know that in the next hand that short stack
will have to post his blind allin with any hand he is dealt, clearly this event
is much worse for the short stack than the naive assumption that he’ll be awarded
his equity next hand  and that loss for the short stack is a gain for the others.
This issue is always present with ICM calculations, although at deeper stacks and
further away from the bubble it’s effects are lessened.
We’ve just shown that ICM has definite flaws, but we can’t ignore just how powerful
ICM is.
Virtually every winning professional SnG and MTT player at reasonable stakes
uses ICM to analyze their play and help craft their strategies for the tables, clearly
ICM is the best model we have available today to estimate tournament equity.
There have been attempts to improve ICM’s accuracy by addressing the flaws we mentioned here.
The most notable among them is the Future Game Simulation (FGS) which uses ICM at it’s
core and takes the method we used in this article of modeling a poker hand a step deeper
by modeling a number of hands which follow the current one. This model better accounts for
issues which cause problems in hands like the example above.
You are welcome to like and share this article if you learned something new about ICM poker model!