We've trained for this for some 9 weeks with a pal, It was a 7km run in heavy terrain and mud (at some points waste high) with around ~15 obstacles.
Here's a vid from last event
First training was some 1600m, 4x3 these steps, 3 different variations: + Show Spoiler +
and 24 burpees, with adding difficulty each week.
We ended running 7.2km, 12x3 steps, 120 burpees on last training and one mock 6.4km run with 30 burpees after every 800m (240 burpees in the end). So yeah we didn't train for any obstacles instead opted to wing it with heavy burpee training
I failed 4 oobstacles AKA 120 penalty burpees: Fell off 3 climbing obstacles and missed with Javelin.
I touched the bottom of my powers when I had to do 3xburpees inbetween crawling in mud under barbed wire uphill in a short time but it was nothing the training didn't prepare us for. Also no injury besides some scratches yay! (And there was a lot of injuries, paramedics on site are always busy)
Last week I've also traveled to meet my pals I used to play floorball with when I was in in the highest Czech league, some 8 years ago.
It was a fun 3+1 (a lot faster than normal floorball I must say) tourney and some top and current national team levels players were there, and I realized how much I suck compared to them. My team mates just couldn't grasp that I'm not gonna be the same before a 7year break as after it and I got chastised quite a bit https://scontent-a-fra.xx.fbcdn.net/h...67151354670_7870243334071210190_n.jpg
I've got a tournament this week in my town again, and after that I plan on taking on summer fitness goalkeeper oriented training.
It won't be as clear cut motivating as the Spartan Race though so I'm trying to find people to work out with. I want to be below 80kg by the end of the summer (87ish now - I've hit a plateau lasting some 3 months now - diet change's needed especially).
Besides my weekly tennis with Grandma Of course :D https://scontent-a-fra.xx.fbcdn.net/h...00495797434_3658074848314875517_n.jpg
Cheers for reading.
P.S. I'm playing poker too btw guys don't think I just run around having fun
I played some 110hrs studied tons last month. I also meditated quite a bit I always do 15-20ish minutes sitting meditation where I just concentrate on concentrating, and if my head's clear enough and I can still concentrate I do another 15-20ish minutes walking meditation where I attack topics from all angles, often poker ones too and came to some cool realizations, but really there's never enough of this so I'll try to put in some hefty meditation volumes next month too.
I have the pokerstrategy vip event at the end of the month - I'll defo post how it went
how do you copy/paste hand histories from pokerstars? Ive got the instant hand history window open but when I drag over the text theres no c/p option lol, help
On May 29 2014 13:14 Daut wrote:
careface, a while back i wrote down the names of 164 good and very good pros who have played the main event. i then added up then # of times they played the main event and their total cashes. i purposefully left off some players like duhamel and joseph cheong because i felt like they would have never reached an ok level had they not done well in the main event. also left off greg merson. and left off all years before 2005. just a different tournament in a different time. took the hachem series to 2012, 8 years of WSOP main events. i actually had 0 WSOP main event winners on the list. i didnt want people screwing up the numbers. i basically only included final table players like matusow, ivey, cunningham, ben lamb, the grinder. i didnt even include michael binger in this list.
results?
955 main events, 170 cashes, ROI 196%
sure this includes guys like ivey and negreanu who likely have 500% ROIs over many of those years, but very good players do have big ROIs in the main event. the tournament is too slow, too deep and too many fish not to.
now, suppose we have a very good player in an online tournament. ill take myself cause i dont want to talk about anyone else. lets say i am selling action to the sunday 100 rebuy on stars. it gets about 900 people, has a bunch of good players and a bunch of terrible fish. i would guess that my ROI in this tournament is about 30%. just based on the feel of how soft it is. since its an online tournament and it costs me virtually nothing to enter it, i think a fair selling price to it would be 1.1:1.
in the main event, with many more players and a much better structure, i think my ROI is likely in the 75-100% range. some would say higher, but i think they are a bit delusional. but if i were to play the main event id have to drive to vegas, stay in a hotel, not play online those long hours....the cost is rather high. so while the profits of an online tournament should be split much more fairly, and maybe even a little in the favor of the backer, the profits of a live tournament should mostly go to the horse. i think 1.5:1 is a completely fair markup to sell at for someone with a 75-100% ROI in the main event.
there is A LOT that factors into this markup. more than you would consider for a 1500 prelim or an online tournament. for a 1500 prelim id sell at 1.3:1. but the main event...i mean fuck, if i make day 3 and dont cash i HAVE TO BE IN VEGAS FOR AT LEAST 6 DAYS. its really absurd the cost of playing it.
For fun I put in the payout structure from 2011 wsop into excel so I could see how ROI works out with different probabilities of finishing in spots.
- A perfectly average player returns (-6%) roi with an itm of 10%
- A player who gets itm 18% (like in Daut's sample) but has an even probability distribution of finishing in any itm spot returns 68% roi
- A player who gets itm 18% and is three times as likely to reach any final table spot as the person in point above who got 18% itm (with the extra probability of final table being taken out of the probability of mincash - a simplifying assumption), returns 214% roi
Now here's the problem, roi is ridiculously sensitive to minute differences in probability of finishing in the top spots. When we talk about a 5.3x increase in probability of final tabling between a theoretically perfectly average player (as in point 1) and a player with 18% itm who returns 214% roi (as in point 3), we're talking about an increase from 0.13% to 0.70% probability. In absolute terms it's a tiny difference yet leads to a huge change in roi.
Quick example, for Daut's sample size of 955 WSOPMEs played by a basket of good players, total buyins are $9.55mm. with 196% roi, total returns are $28.268mm. If we just remove one tournament result from this sample - Ben Lamb's final table finish for $4m, this reduces sample roi to 154%. The number of FT finishes in Daut's sample of 955 MEs is going to be in the low single figures. You can see where I'm going with this - this sample doesn't give us close to a clear idea of realistic ME rois. If we tried to get a 95% confidence interval around that 196% point estimate, it would be very wide indeed (an exercise i'll leave to those of you who are so motivated)
Payout data from 2011 wsop ME (i think it was 2011 but not sure + Show Spoiler +
This is intended to kick off discussion of the difficulty of ROI estimation in tournaments like the ME where we need a much bigger sample than we actually have before we can get narrow confidence intervals - and the implications for backing and staking "fair" markup. Can there even be such a thing as a normative idea of "fair"? Or is fair just what the market decides and what people are willing to pay / sell for?
>be me
>raise kq pre
>tell myself im going to flop a straight, but there's going to be a pair on the flop, and my villian won't let his trips go no matter what i do, and that he's going to boat the river
>exactly that happens
>tell myself i should become cleo's assistant considering how often this happens
first 1st place in a 'big' tourney, money will be squandered pretty fast tho... probably for gf related stuff, as usual i should say... shit costs so much.
Deleted original post because it was too much of a whine.
Basically, what are your happiness life hacks? Everyone has their own things they do that makes them happy. Share yours. (even if what makes you happy may not make someone else happy.)
Main event coming up again and I'm definitely going to play. Hopefully can make a slightly deeper run than last year (196). I'm looking to sell about half my action. You guys let me know what you think is a reasonable markup. I'll take the best offer.
I'm purchasing a license for CREV soon and want to use it to work on my blind game a ton. I'm a little bit of a boob when it comes to figuring out ideal blind defense ranges (even away from the table) so I was hoping to get some criticism / insight from you guys on how you'd do it.
For the sake of this hypothetical let's imagine both players ONLY check postflop.
Assumptions:
- SB opens 55%.
- SB opens to 2x.
- SB folds to 3bet 70%
- SB calls 3bet 22%
- SB 4bets 8%
- Hero's 3B size is 6BB when he 3bets.
Immediate considerations:
- SB needs to succeed 60% of the time for his steal to break even.
- Hero's 3bet needs to succeed 63% of the time to show a tiny profit.
- Hero is getting 3:1 on a call and only needs 25% equity to break even.
So things start getting pretty fuzzy for me straight away.
On the one hand, I only need 25% equity against a loose range to call, so in theory I could profitably call with a ton of complete junk hands, while simply 3betting all hands that have an edge on his 3bet calling range for value (removing some of the bottom of that value range and adding in some bluffs to account for his 4bets).
On the other hand, if I defend the top 40% of his range (22% of hands) then I will show profit.
So, where do you start? How do you determine bluff frequency and based on what stats? What do you call with? What do you 3b for value? When is your range linear v polarized?
Improved Solution to Secretary Problem?by Daut, May 26
Posting this here for 2 reasons. First as a brag, thought it was pretty cool that I came across a problem with some real world applications and was able to improve on the solution for the simplest case. And second cause there are some really smart mathematicians here (catyoul for instance and others) who may want to run with my algorithm and apply it to the more general cases or come up with even better algorithms than I have.
Was doing my normal web surfing last week and came across the secretary problem, something I had never heard of before.
" imagine an administrator willing to hire the best secretary out of n rankable applicants for a position. The applicants are interviewed one-by-one in random order. A decision about each particular applicant is to be made immediately after the interview. Once rejected, an applicant cannot be recalled. During the interview, the administrator can rank the applicant among all applicants interviewed so far, but is unaware of the quality of yet unseen applicants. The question is about the optimal strategy (stopping rule) to maximize the probability of selecting the best applicant. If the decision can be deferred to the end, this can be solved by the simple maximum selection algorithm of tracking the running maximum (and who achieved it), and selecting the overall maximum at the end. The difficulty is that the decision must be made immediately."
When I read the solution I was at first impressed by it's mathematical beauty: Reject the first n/e applicants, choose the next best applicant after that or choose the last one. this gives a probability of 1/e of delivering the best applicant.
But on second thought it seemed rather risky. When the best applicant occurs in the first n/e spots, the last applicant is always the one chosen. Which means ~36.8% of the time you get a random choice between the worst and 2nd best applicant. It's likely that the applicants are normally distributed about an average number, and while the best applicant may be a standard deviation above the 2nd best or next group of best applicants, the worst applicant might be just as far on the other side of the spectrum or worse. This could be really disastrous.
For example, the most likely real world application of this problem is in dating. Sure you dont know exactly what N will be, but you date a certain number of girls and then eventually you choose one to settle down with. If you wait a while and refuse to settle for someone worse than your first set of applicants, you may end up getting stuck with a real shitty girl at an older age.
I thought I could immediately improve the solution to this problem. My solution was fairly simple: iterate this same process. Go through first n/e applicants, write down max, reject those. now there are n - n/e applicants. look through next (n-n/e)/e applicants, if you find a better one in there you choose it, if not you write down the max from that group, etc. iterated on to the end where you just go 1 at a time.
I programmed a simple version of both in python. I ranked secretaries 0-99, randomized their order and used each method to test the % choosing best applicant, the median applicant chosen and the average applicant chosen.
#Original secretary problem solution based on 100 secretaries and just on the ranking of secretaries from 1-100
#want to figure out both average ranking chosen and how often the best candidate is chosen
#function which sorts a list
def sortedRankings(sec):
x=0
while x <99:
import random
from random import randint
a = random.randint(x,99)
temp = sec[x]
sec[x] = sec[a]
sec[a] = temp
x = x+1
return sec
#function which returns a secretary based on original algorithm
def chooseSecretary(sec):
max=sec[0]
x=1
while x<36:
if (sec[x] > max):
max = sec[x]
x=x+1
while x<99:
if (sec[x] > max):
return sec[x]
x=x+1
#sort winners
a=0
while a<1000:
b=a
min=100
minLocation=-1
while b<1000:
if(min > winners[b]):
min = winners[b]
minLocation=b
b=b+1
temp=winners[a]
winners[a]=winners[minLocation]
winners[minLocation]=temp
a=a+1
print winners
print winners[499]
results: Ran the simulation 1000 times. The best secretary was chosen 375 times. The median secretary chosen was the 2nd best. The average choice was the 18th best. And roughly 3.5% of the time a bottom 10 secretary was chosen.
#function which sorts a list
def sortedRankings(sec):
x=0
while x <99:
import random
from random import randint
a = random.randint(x,99)
temp = sec[x]
sec[x] = sec[a]
sec[a] = temp
x = x+1
return sec
#function which returns a secretary based on original algorithm
def chooseSecretary(sec):
max=sec[0]
max2=0
max3=0
max4=0
max5=0
max6=0
max7=0
max8=0
max9=0
max10=0
x=1
while x<36:
if (sec[x] > max):
max = sec[x]
x=x+1
while x<60:
if (sec[x] > max):
return sec[x]
if (sec[x] > max2):
max2 = sec[x]
x=x+1
while x<74:
if (sec[x] > max2):
return sec[x]
if (sec[x] > max3):
max3 = sec[x]
x=x+1
while x<84:
if (sec[x] > max3):
return sec[x]
if (sec[x] > max4):
max4 = sec[x]
x=x+1
while x<90:
if (sec[x] > max4):
return sec[x]
if (sec[x] > max5):
max5 = sec[x]
x=x+1
while x<93:
if (sec[x] > max5):
return sec[x]
if (sec[x] > max6):
max6 = sec[x]
x=x+1
while x<95:
if (sec[x] > max6):
return sec[x]
if (sec[x] > max7):
max7 = sec[x]
x=x+1
while x<97:
if (sec[x] > max7):
return sec[x]
if (sec[x] > max8):
max8 = sec[x]
x=x+1
while x<98:
if (sec[x] > max8):
return sec[x]
if (sec[x] > max9):
max9 = sec[x]
x=x+1
while x<99:
if (sec[x] > max9):
return sec[x]
if (sec[x] > max10):
max10 = sec[x]
x=x+1
#sort winners
a=0
while a<1000:
b=a
min=100
minLocation=-1
while b<1000:
if(min > winners[b]):
min = winners[b]
minLocation=b
b=b+1
temp=winners[a]
winners[a]=winners[minLocation]
winners[minLocation]=temp
a=a+1
print winners
print winners[499]
Results: ran 1000 times. best chosen 263. 3rd best was median choice. average: 4th best. worst chosen: 50th best.
this seems much much better. of course i didnt program it for random values in a normal distribution, nor did i program it for the more likely real world scenario of an unknown N. but this clearly seems like a much better solution despite the fact that the original solution chooses the best secretary ~10% more often.
So, if you guys would like, run with this in the more general forms or try and come up with an even better solution.
I've just started playing a bit of poker again for the first time in a while. I used to play a lot and be very active on this site around 2006-2009 so I don't know how many people from then still post, maybe no one remembers me but I used to play NL50-NL200 6 max on Pokerstars.
A few friends of mine just started playing online after we went to the casino together for a donkament, and it gave me the itch to start playing a bit again. I've decided to try grind up from the beginning again without depositing and found my FTP account still had enough FPPs in to buy 20x$1 SnG tickets and used what I won from those to start playing my preferred form of poker again - ring games. I tried Rush Poker but didn't like it, broke even after a couple thousand hands so went back to the 'traditional' games with better success. I won't be playing loads, since I used to play I have a real job now so don't have time for grinding away, but poker is undeniably good fun when things go well so hopefully I can make a bit of money while enjoying it. Here's my first 2 days back playing ring games (NL2 then NL5) -
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