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We'll be back in an hour. Keep asking questions :) we'll get to them.</p>\n\n<p>UPDATE: I'm proud to announce that I just worked my first "Banana for scale" joke in this thread! <a href=\"http://imgur.com/Ck0LBNd\">http://imgur.com/Ck0LBNd</a> (left one is the Jurassic Park version, middle one is a real raptor claw)</p>\n\n<p>UPDATE: My colleague Dr. Don Henderson (Curator of Dinosaurs at the Royal Tyrrell museum) is helping me answer some of the questions. He'll be using my username as well, but he'll identify himself with "DMH" when he does. <a href=\"http://imgur.com/bu9fdK6\">http://imgur.com/bu9fdK6</a></p>\n\n<p>UPDATE: questions are coming in like crazy! Hang in there with me and I'll answer as many as I can...</p>\n\n<p>My name is Francois Therrien and I\u2019m a professional paleontologist working out of the Dinosaur Capital of the World: Drumheller, Alberta in the Canadian badlands. I was part of the team that discovered and described the first feathered dinosaurs in North America, and through my studies, I\u2019ve been able to demonstrate that the tyrannosaurus had the best-developed sense of smell of all meat-eating dinosaurs and the most powerful bite of all theropods. 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Keep asking questions :) we'll get to them.\n\nUPDATE: I'm proud to announce that I just worked my first \"Banana for scale\" joke in this thread! http://imgur.com/Ck0LBNd (left one is the Jurassic Park version, middle one is a real raptor claw)\n\nUPDATE: My colleague Dr. Don Henderson (Curator of Dinosaurs at the Royal Tyrrell museum) is helping me answer some of the questions. He'll be using my username as well, but he'll identify himself with \"DMH\" when he does. http://imgur.com/bu9fdK6\n\nUPDATE: questions are coming in like crazy! Hang in there with me and I'll answer as many as I can...\n\nMy name is Francois Therrien and I\u2019m a professional paleontologist working out of the Dinosaur Capital of the World: Drumheller, Alberta in the Canadian badlands. 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null, "secure_media": null, "link_flair_text": null, "id": "2c4x5b", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "black_flag_4ever", "media": null, "score": 2841, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "", "subreddit_id": "t5_2qh1i", "edited": false, "link_flair_css_class": null, "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": true, "permalink": "/r/AskReddit/comments/2c4x5b/what_should_you_absolutely_not_do_at_a_wedding/", "name": "t3_2c4x5b", "created": 1406727961.0, "url": "http://www.reddit.com/r/AskReddit/comments/2c4x5b/what_should_you_absolutely_not_do_at_a_wedding/", "author_flair_text": null, "title": "What should you absolutely not do at a wedding?", "created_utc": 1406724361.0, "ups": 2841, "num_comments": 9346, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "en.wikipedia.org", "banned_by": null, "media_embed": {}, "subreddit": "todayilearned", "selftext_html": null, "selftext": "", "likes": null, "secure_media": null, "link_flair_text": null, "id": "2c4r5l", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "doc_daneeka", "media": null, "score": 3634, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "http://b.thumbs.redditmedia.com/37twtwpclDe6xijA.jpg", "subreddit_id": "t5_2qqjc", "edited": false, "link_flair_css_class": null, "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": false, "permalink": "/r/todayilearned/comments/2c4r5l/til_that_the_richest_woman_in_germany_met_her/", "name": "t3_2c4r5l", "created": 1406747646.0, "url": "http://en.wikipedia.org/wiki/Susanne_Klatten", "author_flair_text": null, "title": "TIL that the richest woman in Germany met her future husband while she was working in an apprenticeship at BMW (which she owned 12.5 percent of) under a fake name. He had no idea who she actually was until they were sure about their relationship.", "created_utc": 1406718846.0, "ups": 3634, "num_comments": 1173, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "i.imgur.com", "banned_by": null, "media_embed": {}, "subreddit": "EarthPorn", "selftext_html": null, "selftext": "", "likes": null, "secure_media": null, "link_flair_text": null, "id": "2c4zn0", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "Z_FLuX_Z", "media": null, "score": 1826, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "http://b.thumbs.redditmedia.com/sG0zAvc3vJeBA48E.jpg", "subreddit_id": "t5_2sbq3", "edited": false, "link_flair_css_class": null, "author_flair_css_class": "Camera", "downs": 0, "saved": false, "is_self": false, "permalink": "/r/EarthPorn/comments/2c4zn0/mountain_tarn_in_kananaskis_alberta_oc_4000x3000/", "name": "t3_2c4zn0", "created": 1406729844.0, "url": "http://i.imgur.com/vLYeX5N.jpg", "author_flair_text": null, "title": "Mountain tarn in Kananaskis, Alberta [OC] [4000x3000]", "created_utc": 1406726244.0, "ups": 1826, "num_comments": 65, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "self.Music", "banned_by": null, "media_embed": {}, "subreddit": "Music", "selftext_html": "<!-- SC_OFF --><div class=\"md\"><p>Well " Reddit", that is the people that took the time to post <a href=\"http://www.reddit.com/r/Music/comments/2bzfqa/what_are_in_your_opinion_the_best_10_albums_of/\">their 10 favorite albums of the 2000s</a>  !</p>\n\n<p><strong>Most popular:</strong><br/>\n*Radiohead - Kid A<br/>\n*The Strokes - Is This It?<br/>\n*Arcade Fire - Funeral<br/>\n*Kanye West - The College Dropout    </p>\n\n<p><strong>Very popular:</strong><br/>\n*LCD Soundsystem - Sound of Silver<br/>\n*Gorillaz - Demon Days<br/>\n*Radiohead - In Rainbows<br/>\n*The White Stripes - White Blood Cells<br/>\n*The White Stripes - Elephant<br/>\n*Queens of the Stone Age - Songs for the Deaf<br/>\n*Wilco - Yankee Hotel Foxtrot<br/>\n*Vampire Weekend - Vampire Weekend<br/>\n*Modest Mouse - Good News for People Who Love Bad News<br/>\n*Green Day - American Idiot    </p>\n\n<p><strong>Popular:</strong><br/>\n*Eminem - The Marshall Mathers LP<br/>\n*Sufjan Stevens - Illinoise<br/>\n*Madvillain - Madvillainy<br/>\n*MGMT - Oracular Spectacular<br/>\n*Amy Winehouse - Back to Black<br/>\n*Daft Punk - Discovery<br/>\n*Outkast - Stankonia<br/>\n*Modest Mouse - The Moon& Antarctica<br/>\n*Arctic Monkeys - Whatever People Say I am, That's What I'm Not<br/>\n*Brand New - The Devil and God Are Raging Inside Me<br/>\n*Phoenix - Wolfgang Amadeus Phoenix<br/>\n*Interpol - Turn on The Bright Lights   </p>\n\n<p>Edit: Thanks to <a href=\"http://www.reddit.com/user/Nchamay\">Nchamay</a>  we now have a <a href=\"http://open.spotify.com/user/1229309035/playlist/3Fj8mA0CSGt4YbWqYPzMar\">Spotify list</a>!</p>\n</div><!-- SC_ON -->", "selftext": "Well \" Reddit\", that is the people that took the time to post [their 10 favorite albums of the 2000s](http://www.reddit.com/r/Music/comments/2bzfqa/what_are_in_your_opinion_the_best_10_albums_of/)  !\n  \n**Most popular:**  \n*Radiohead - Kid A  \n*The Strokes - Is This It?  \n*Arcade Fire - Funeral  \n*Kanye West - The College Dropout    \n\n**Very popular:**  \n*LCD Soundsystem - Sound of Silver  \n*Gorillaz - Demon Days  \n*Radiohead - In Rainbows  \n*The White Stripes - White Blood Cells  \n*The White Stripes - Elephant  \n*Queens of the Stone Age - Songs for the Deaf  \n*Wilco - Yankee Hotel Foxtrot   \n*Vampire Weekend - Vampire Weekend  \n*Modest Mouse - Good News for People Who Love Bad News  \n*Green Day - American Idiot    \n \n**Popular:**  \n*Eminem - The Marshall Mathers LP  \n*Sufjan Stevens - Illinoise  \n*Madvillain - Madvillainy  \n*MGMT - Oracular Spectacular  \n*Amy Winehouse - Back to Black  \n*Daft Punk - Discovery  \n*Outkast - Stankonia  \n*Modest Mouse - The Moon& Antarctica  \n*Arctic Monkeys - Whatever People Say I am, That's What I'm Not  \n*Brand New - The Devil and God Are Raging Inside Me  \n*Phoenix - Wolfgang Amadeus Phoenix   \n*Interpol - Turn on The Bright Lights   \n  \nEdit: Thanks to [Nchamay](http://www.reddit.com/user/Nchamay)  we now have a [Spotify list] (http://open.spotify.com/user/1229309035/playlist/3Fj8mA0CSGt4YbWqYPzMar)!\n", "likes": null, "secure_media": null, "link_flair_text": "Discussion", "id": "2c4uro", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "dirkdiggin", "media": null, "score": 1614, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "", "subreddit_id": "t5_2qh1u", "edited": 1406740885.0, "link_flair_css_class": "disc", "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": true, "permalink": "/r/Music/comments/2c4uro/this_is_what_reddit_thinks_that_are_the_best/", "name": "t3_2c4uro", "created": 1406751189.0, "url": "http://www.reddit.com/r/Music/comments/2c4uro/this_is_what_reddit_thinks_that_are_the_best/", "author_flair_text": null, "title": "This is what Reddit thinks that are the best albums of the 2000s", "created_utc": 1406722389.0, "ups": 1614, "num_comments": 1352, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "self.science", "banned_by": null, "media_embed": {}, "subreddit": "science", "selftext_html": "<!-- SC_OFF --><div class=\"md\"><p>As the Director of The Regional Laboratory for the Science of Cultural Heritage Conservation at Portland State University, I\u2019m excited about the many diverse projects that are studied by the lab \u2013 from Ethiopian manuscripts to modern sculpture. One of our interesting projects is in collaboration with the Seattle Art Museum. And today, we\u2019d like to talk about how we are developing methods to understand the protective quality of coatings used on outdoor sculpture, which are used to protect the artwork from the effects of the environment. You might want to check out our webpage on the project: <a href=\"http://www.pdx.edu/clarelab/artwork-diagnostics\">http://www.pdx.edu/clarelab/artwork-diagnostics</a> Studying artwork is a really fun application of chemistry. It is good to know that protective coatings are also used on many high value metalworks, such as bridges and airplanes. In fact, some estimates have suggested that the problem of corrosion of metalwork consumes 3% of the world\u2019s GNP annually (<a href=\"http://corrosion.org/\">http://corrosion.org/</a>)! So, the work that we do to understanding coatings on sculptures has the potential to help this big economic problem.</p>\n\n<p>Joining me is Liz Brown, <a href=\"/u/Liz_Brown\">/u/Liz_Brown</a> , \u200eAssociate Conservator at Seattle Art Museum.</p>\n\n<p>We will be back at 2 pm EDT to answer questions, Ask Us Anything!</p>\n\n<p>Thanks for the many great questions so far!  I will try to get to as many as I can.  Liz will join us soon.  For those in near OSP -- stop by to see us this week!</p>\n</div><!-- SC_ON -->", "selftext": "As the Director of The Regional Laboratory for the Science of Cultural Heritage Conservation at Portland State University, I\u2019m excited about the many diverse projects that are studied by the lab \u2013 from Ethiopian manuscripts to modern sculpture. One of our interesting projects is in collaboration with the Seattle Art Museum. And today, we\u2019d like to talk about how we are developing methods to understand the protective quality of coatings used on outdoor sculpture, which are used to protect the artwork from the effects of the environment. You might want to check out our webpage on the project: http://www.pdx.edu/clarelab/artwork-diagnostics Studying artwork is a really fun application of chemistry. It is good to know that protective coatings are also used on many high value metalworks, such as bridges and airplanes. In fact, some estimates have suggested that the problem of corrosion of metalwork consumes 3% of the world\u2019s GNP annually (http://corrosion.org/)! So, the work that we do to understanding coatings on sculptures has the potential to help this big economic problem.\n\nJoining me is Liz Brown, /u/Liz_Brown , \u200eAssociate Conservator at Seattle Art Museum.\n\nWe will be back at 2 pm EDT to answer questions, Ask Us Anything!\n\nThanks for the many great questions so far!  I will try to get to as many as I can.  Liz will join us soon.  For those in near OSP -- stop by to see us this week!", "likes": null, "secure_media": null, "link_flair_text": "Art Conservation", "id": "2c4tjf", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "Tami_Lasseter_Clare", "media": null, "score": 1679, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "", "subreddit_id": "t5_mouw", "edited": 1406742433.0, "link_flair_css_class": "chem AMA", "author_flair_css_class": "chem", "downs": 0, "saved": false, "is_self": true, "permalink": "/r/science/comments/2c4tjf/science_ama_series_im_tami_lasseter_clare_a/", "name": "t3_2c4tjf", "created": 1406750055.0, "url": "http://www.reddit.com/r/science/comments/2c4tjf/science_ama_series_im_tami_lasseter_clare_a/", "author_flair_text": "Professor of Chemistry|Portland State University", "title": "Science AMA Series: I\u2019m Tami Lasseter Clare, a Professor of Chemistry at Portland State University. Today I\u2019m at the Seattle Art Museum\u2019s Olympic Sculpture Park in Seattle, WA, with a team of three graduate and undergraduate students and the Seattle Art Museum\u2019s Objects Conservator, Liz Brown. AMA!", "created_utc": 1406721255.0, "ups": 1679, "num_comments": 195, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "np.reddit.com", "banned_by": null, "media_embed": {}, "subreddit": "bestof", "selftext_html": null, "selftext": "", "likes": null, "secure_media": null, "link_flair_text": "[astrophotography]", "id": "2c4wxe", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "EorEquis", "media": null, "score": 1346, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "", "subreddit_id": "t5_2qh3v", "edited": false, "link_flair_css_class": null, "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": false, "permalink": "/r/bestof/comments/2c4wxe/ubersonics_amazing_picture_of_the_andromeda/", "name": "t3_2c4wxe", "created": 1406752981.0, "url": "http://np.reddit.com/r/astrophotography/comments/2c4ukh/my_picture_of_m31_is_todays_apod_astronomy/", "author_flair_text": null, "title": "/u/Bersonic's amazing picture of the Andromeda Galaxy is selected as NASA's Astronomy Picture of the Day", "created_utc": 1406724181.0, "ups": 1346, "num_comments": 31, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "self.explainlikeimfive", "banned_by": null, "media_embed": {}, "subreddit": "explainlikeimfive", "selftext_html": null, "selftext": "", "likes": null, "secure_media": null, "link_flair_text": "Explained", "id": "2c51nb", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "SlipperyThong", "media": null, "score": 1098, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "", "subreddit_id": "t5_2sokd", "edited": false, "link_flair_css_class": "resolved", "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": true, "permalink": "/r/explainlikeimfive/comments/2c51nb/eli5_why_are_there_so_many_checkout_lines_in/", "name": "t3_2c51nb", "created": 1406756392.0, "url": "http://www.reddit.com/r/explainlikeimfive/comments/2c51nb/eli5_why_are_there_so_many_checkout_lines_in/", "author_flair_text": null, "title": "ELI5: Why are there so many checkout lines in grocery stores but never enough employees to fill them?", "created_utc": 1406727592.0, "ups": 1098, "num_comments": 524, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "bbc.co.uk", "banned_by": null, "media_embed": {}, "subreddit": "technology", "selftext_html": null, "selftext": "", "likes": null, "secure_media": null, "link_flair_text": "Politics", "id": "2c4b4p", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "sensor111", "media": null, "score": 3209, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "", "subreddit_id": "t5_2qh16", "edited": false, "link_flair_css_class": "politics", "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": false, "permalink": "/r/technology/comments/2c4b4p/uk_to_allow_driverless_cars_on_public_roads/", "name": "t3_2c4b4p", "created": 1406730180.0, "url": "http://bbc.co.uk/news/technology-28551069", "author_flair_text": null, "title": "UK to allow driverless cars on public roads", "created_utc": 1406701380.0, "ups": 3209, "num_comments": 582, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "insidetv.ew.com", "banned_by": null, "media_embed": {}, "subreddit": "television", "selftext_html": null, "selftext": "", "likes": null, "secure_media": null, "link_flair_text": null, "id": "2c5cnf", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "GraceDangerous", "media": null, "score": 272, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "http://a.thumbs.redditmedia.com/LJB_xWxX8qCMw39B.jpg", "subreddit_id": "t5_2qh6e", "edited": false, "link_flair_css_class": null, "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": false, "permalink": "/r/television/comments/2c5cnf/allison_williams_cast_as_peter_pan_in_nbcs_live/", "name": "t3_2c5cnf", "created": 1406763281.0, "url": "http://insidetv.ew.com/2014/07/30/allison-williams-peter-pan-live/", "author_flair_text": null, "title": "Allison Williams cast as Peter Pan in NBC's live theatrical production.", "created_utc": 1406734481.0, "ups": 272, "num_comments": 198, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "self.askscience", "banned_by": null, "media_embed": {}, "subreddit": "askscience", "selftext_html": null, "selftext": "", "likes": null, "secure_media": null, "link_flair_text": "Biology", "id": "2c46ul", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "reginaldtato", "media": null, "score": 1476, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "", "subreddit_id": "t5_2qm4e", "edited": false, "link_flair_css_class": "bio", "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": true, "permalink": "/r/askscience/comments/2c46ul/why_do_poisonous_berries_exist_didnt_berries/", "name": "t3_2c46ul", "created": 1406726563.0, "url": "http://www.reddit.com/r/askscience/comments/2c46ul/why_do_poisonous_berries_exist_didnt_berries/", "author_flair_text": null, "title": "Why do poisonous berries exist? Didn't berries evolve to be eaten?", "created_utc": 1406697763.0, "ups": 1476, "num_comments": 387, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "self.csgobetting", "banned_by": null, "media_embed": {}, "subreddit": "csgobetting", "selftext_html": "<!-- SC_OFF --><div class=\"md\"><p>Recently I've seen a lot of advice posts offering good insight into teams but being very, very incorrect on how to bet given the information. I thought I'd write up a post explaining probability and how to 'beat' CSGL.</p>\n\n<p>Every bet you make has two outcomes with odds prescribed by CSGL. These odds are determined by the total value of bets placed on the respective teams. If people bet $750 on Team A and $250 on Team B, the odds will be 75:25. The formula that CSGL uses to determine the value of your winnings is:</p>\n\n<pre><code>= (bet size) * (value of losing team) / (value of winning team)\n</code></pre>\n\n<p>But since the odds are determined using the proportion of values of the losing and winning teams, we can rewrite this as:</p>\n\n<pre><code>= (bet size) * (probability of losing) / (probability of winning)\n</code></pre>\n\n<p>Notice that as our probability of winning goes down, the denominator gets smaller, meaning our returns get larger.</p>\n\n<p>Every bet also has an <strong>expected value</strong> (or EV) which is defined as <em>the sum of all products of outcome probabilities and the rewards for those outcomes</em>. For CSGL, that equation is:</p>\n\n<pre><code>= (probability of winning) * (reward for winning) + (probability of losing) * (reward for losing)\n</code></pre>\n\n<p>For example, if I pay $1 to flip a 50/50 coin and win $2 if it's heads, my EV is:</p>\n\n<pre><code>=(.5) * (2) + (.5) * (-1)\n= 1 + (-.5)\n= .5\n</code></pre>\n\n<p>So I should expect to make 50 cents on every coin flip.</p>\n\n<p>Now let's make the assumption that CSGL predicts the odds of every match correctly; that is, for given odds of a match, if the match were played infinitely many times, each team would win a proportion of the time that corresponds with the odds given by CSGL. We can now rewrite this formula as:</p>\n\n<pre><code>= (probability of winning) * ((bet size) * (probability of losing) / (probability of winning)) + (probability of losing) * -(bet size)\n= (bet size) * (probability of losing) + (probability of losing) * -(bet size)\n= 0\n</code></pre>\n\n<p>Wait, what? Our expected value is ZERO?!</p>\n\n<p>Well, not really - remember that CSGL takes a rake. From bets.js:</p>\n\n<pre><code>function newBetCalculate() {\n    var total = 0;\n    $("#betpoll .item").children('input[name="worth"]').each(function( index ) {\n        total += parseFloat($(this).val());\n    });\n    total = Math.round(total * 100) / 100;\n    $("#yourVal").html(total);\n    $("#teamA").html( Math.round((valB*total/valA) * 97) / 100 );\n    $("#teamB").html( Math.round((valA*total/valB) * 97) / 100 );\n}\n</code></pre>\n\n<p>In reality, CSGL is taking between 1 and 3% of your calculated winnings depending on the match. Which makes sense - remember, the purpose of providing a gambling service is to make money from the gamblers. Casinos do this by offering bets against the bank with a disadvantage to the bettor, either in the rules of the game (blackjack) or by trusting that their predictions are more accurate than yours (sports lines). Since CSGL isn't providing the bank, it takes its payment directly from the pool of all total bets.</p>\n\n<p>The result of this is that if you make uninformed bets based on CSGL lounges, you will <em>always lose money in the long term</em> because your bets are expected to lose money. So why bet at all, right?</p>\n\n<p>Well, let's back up a bit - remember when I made the assumption that CSGL predicts the odds of every match correctly? Here's the thing - it doesn't. Not even a little bit. Think about the people you play matchmaking with in CS:GO. They're the people you're betting against. You know more about CS than them, right? <a href=\"https://www.youtube.com/watch?v=q-K_Cyxjf8A#t=26\">Thought so</a>. </p>\n\n<p>The way to get an advantage in CSGL is to find out which teams are <strong>undervalued</strong> according to the odds - preferably at a significant enough ratio to beat the rake.</p>\n\n<p>Let's say there's a matchup that CSGL says is 80/20 but you think the true odds are closer to 70/30. (which is to say, if the game were played 100 times, Team A would win ~70 and Team B would win ~30). Because the 'true' odds are different from the CSGL odds, our expected value is different. Because we think Team B has a higher chance to win than CSGL is giving them credit for, we want to bet on them. Assuming the rake is 3%, the EV for our bet becomes:</p>\n\n<pre><code>= (real probability of winning) * ((bet size) * (CSGL probability of losing) / (CSGL probability of winning)) * (.97) + (real probability of losing) * -(bet size)\n= (.3) * ((bet size) * (.8) / (.2)) * .97 + (.7) * -(bet size)\n= 1.164 * (bet size) - (.8) * (bet size)\n= .464 * (bet size)\n</code></pre>\n\n<p>Hot dog! Our projected advantage on this match (assuming our odds are correct) is almost half of our bet. Conversely, our EV for betting on the overvalued Team A is:</p>\n\n<pre><code>= (real probability of winning) * ((bet size) * (CSGL probability of losing) / (CSGL probability of winning)) * (.97) + (real probability of losing) * -(bet size)\n= (.7) * ((bet size) * (.2) / (.8)) * .97 + (.3) * -(bet size)\n= .16975 * (bet size) - (.3) *  (bet size)\n= -.13025 * (bet size)\n</code></pre>\n\n<p>Our EV here is negative which means we should expect to lose roughly 10% of our bet every time we made this bet (if we made it infinitely many times).</p>\n\n<p>EV gets calculated a lot in poker, and during those calculations it's easy to come out with a raw numerical EV because the values of our bets are determined by our opponents. In these calculations, however, our EV is based on our bet size but doesn't determine it. So <strong>how much do we bet</strong>?</p>\n\n<p>Turns out there's a mathematically optimal amount to bet on games that's entirely dependent on your bankroll called the Kelly Criterion. The Kelly Criterion is:</p>\n\n<pre><code>f = (b * p - q) / b\n</code></pre>\n\n<p>Where:</p>\n\n<ul>\n<li>f = fraction of your total bankroll to bet</li>\n<li>b = given odds, defined as <code>(CSGL probability of losing) / (CSGL probability of winning)</code></li>\n<li>p = real probability of winning</li>\n<li>q = real probability of losing</li>\n</ul>\n\n<p>So let's say we have $100 of skins in our bankroll and we're betting on the same 70/30 game we were talking about earlier. Then our optimal fraction of our bankroll to bet determined by the Kelly Criterion is:</p>\n\n<pre><code>= (((.8) / (.2)) * .3 - .7) / ((.8) / (.2))\n= (4 * .3 - .7) / 4\n= .5 / 4\n= .125\n</code></pre>\n\n<p>So for this match where we think we have a 10% advantage on betting on an underdog, the Kelly Criterion suggests we bet 12.5% of our bankroll (which, conveniently, is $12.50).</p>\n\n<p>There are a couple other wrinkles of the CSGL betting system to take into account - specifically the inability to get returns under a certain value (roughly ~$1 in my experience) and the "value hack" where betting a large amount on a heavy favorite returns larger-than-advertised returns. The only real thing to take away from this is that people with large bankrolls have a big advantage, but you should never be making bets that have a risk of not winning anything.</p>\n\n<p>The last thing to think about is the arbitrage between the Marketplace and CSGL. If you can find items that have a higher value on CSGL than on the Steam Marketplace, you can give yourself better 'effective' odds. If you have $20 in cash to start with, the best thing you can do for yourself is buy 10 keys off of Paypal from a trader and suddenly you have $25 in value.</p>\n\n<p><strong>TLDR</strong>:</p>\n\n<ul>\n<li>bet on teams you think have a better chance to win than CSGL are giving them <em>regardless of who you think will win</em></li>\n<li>if you aren't confident in the odds or you think the CSGL odds are accurate, <em>don't bet</em></li>\n<li>bet based on the Kelly Criterion</li>\n<li>gotta have money to make money</li>\n</ul>\n</div><!-- SC_ON -->", "selftext": "Recently I've seen a lot of advice posts offering good insight into teams but being very, very incorrect on how to bet given the information. I thought I'd write up a post explaining probability and how to 'beat' CSGL.\n\nEvery bet you make has two outcomes with odds prescribed by CSGL. These odds are determined by the total value of bets placed on the respective teams. If people bet $750 on Team A and $250 on Team B, the odds will be 75:25. The formula that CSGL uses to determine the value of your winnings is:\n\n    = (bet size) * (value of losing team) / (value of winning team)\n\nBut since the odds are determined using the proportion of values of the losing and winning teams, we can rewrite this as:\n\n    = (bet size) * (probability of losing) / (probability of winning)\n\nNotice that as our probability of winning goes down, the denominator gets smaller, meaning our returns get larger.\n\nEvery bet also has an **expected value** (or EV) which is defined as *the sum of all products of outcome probabilities and the rewards for those outcomes*. For CSGL, that equation is:\n\n    = (probability of winning) * (reward for winning) + (probability of losing) * (reward for losing)\n\nFor example, if I pay $1 to flip a 50/50 coin and win $2 if it's heads, my EV is:\n\n    =(.5) * (2) + (.5) * (-1)\n    = 1 + (-.5)\n    = .5\n\nSo I should expect to make 50 cents on every coin flip.\n\nNow let's make the assumption that CSGL predicts the odds of every match correctly; that is, for given odds of a match, if the match were played infinitely many times, each team would win a proportion of the time that corresponds with the odds given by CSGL. We can now rewrite this formula as:\n\n    = (probability of winning) * ((bet size) * (probability of losing) / (probability of winning)) + (probability of losing) * -(bet size)\n    = (bet size) * (probability of losing) + (probability of losing) * -(bet size)\n    = 0\n\nWait, what? Our expected value is ZERO?!\n\nWell, not really - remember that CSGL takes a rake. From bets.js:\n\n    function newBetCalculate() {\n        var total = 0;\n        $(\"#betpoll .item\").children('input[name=\"worth\"]').each(function( index ) {\n            total += parseFloat($(this).val());\n        });\n        total = Math.round(total * 100) / 100;\n        $(\"#yourVal\").html(total);\n        $(\"#teamA\").html( Math.round((valB*total/valA) * 97) / 100 );\n        $(\"#teamB\").html( Math.round((valA*total/valB) * 97) / 100 );\n    }\n\nIn reality, CSGL is taking between 1 and 3% of your calculated winnings depending on the match. Which makes sense - remember, the purpose of providing a gambling service is to make money from the gamblers. Casinos do this by offering bets against the bank with a disadvantage to the bettor, either in the rules of the game (blackjack) or by trusting that their predictions are more accurate than yours (sports lines). Since CSGL isn't providing the bank, it takes its payment directly from the pool of all total bets.\n\nThe result of this is that if you make uninformed bets based on CSGL lounges, you will *always lose money in the long term* because your bets are expected to lose money. So why bet at all, right?\n\nWell, let's back up a bit - remember when I made the assumption that CSGL predicts the odds of every match correctly? Here's the thing - it doesn't. Not even a little bit. Think about the people you play matchmaking with in CS:GO. They're the people you're betting against. You know more about CS than them, right? [Thought so](https://www.youtube.com/watch?v=q-K_Cyxjf8A#t=26). \n\nThe way to get an advantage in CSGL is to find out which teams are **undervalued** according to the odds - preferably at a significant enough ratio to beat the rake.\n\nLet's say there's a matchup that CSGL says is 80/20 but you think the true odds are closer to 70/30. (which is to say, if the game were played 100 times, Team A would win ~70 and Team B would win ~30). Because the 'true' odds are different from the CSGL odds, our expected value is different. Because we think Team B has a higher chance to win than CSGL is giving them credit for, we want to bet on them. Assuming the rake is 3%, the EV for our bet becomes:\n\n    = (real probability of winning) * ((bet size) * (CSGL probability of losing) / (CSGL probability of winning)) * (.97) + (real probability of losing) * -(bet size)\n    = (.3) * ((bet size) * (.8) / (.2)) * .97 + (.7) * -(bet size)\n    = 1.164 * (bet size) - (.8) * (bet size)\n    = .464 * (bet size)\n\nHot dog! Our projected advantage on this match (assuming our odds are correct) is almost half of our bet. Conversely, our EV for betting on the overvalued Team A is:\n\n    = (real probability of winning) * ((bet size) * (CSGL probability of losing) / (CSGL probability of winning)) * (.97) + (real probability of losing) * -(bet size)\n    = (.7) * ((bet size) * (.2) / (.8)) * .97 + (.3) * -(bet size)\n    = .16975 * (bet size) - (.3) *  (bet size)\n    = -.13025 * (bet size)\n\nOur EV here is negative which means we should expect to lose roughly 10% of our bet every time we made this bet (if we made it infinitely many times).\n\nEV gets calculated a lot in poker, and during those calculations it's easy to come out with a raw numerical EV because the values of our bets are determined by our opponents. In these calculations, however, our EV is based on our bet size but doesn't determine it. So **how much do we bet**?\n\nTurns out there's a mathematically optimal amount to bet on games that's entirely dependent on your bankroll called the Kelly Criterion. The Kelly Criterion is:\n\n    f = (b * p - q) / b\n\nWhere:\n\n* f = fraction of your total bankroll to bet\n* b = given odds, defined as `(CSGL probability of losing) / (CSGL probability of winning)`\n* p = real probability of winning\n* q = real probability of losing\n\nSo let's say we have $100 of skins in our bankroll and we're betting on the same 70/30 game we were talking about earlier. Then our optimal fraction of our bankroll to bet determined by the Kelly Criterion is:\n\n    = (((.8) / (.2)) * .3 - .7) / ((.8) / (.2))\n    = (4 * .3 - .7) / 4\n    = .5 / 4\n    = .125\n\nSo for this match where we think we have a 10% advantage on betting on an underdog, the Kelly Criterion suggests we bet 12.5% of our bankroll (which, conveniently, is $12.50).\n\nThere are a couple other wrinkles of the CSGL betting system to take into account - specifically the inability to get returns under a certain value (roughly ~$1 in my experience) and the \"value hack\" where betting a large amount on a heavy favorite returns larger-than-advertised returns. The only real thing to take away from this is that people with large bankrolls have a big advantage, but you should never be making bets that have a risk of not winning anything.\n\nThe last thing to think about is the arbitrage between the Marketplace and CSGL. If you can find items that have a higher value on CSGL than on the Steam Marketplace, you can give yourself better 'effective' odds. If you have $20 in cash to start with, the best thing you can do for yourself is buy 10 keys off of Paypal from a trader and suddenly you have $25 in value.\n\n**TLDR**:\n\n* bet on teams you think have a better chance to win than CSGL are giving them *regardless of who you think will win*\n* if you aren't confident in the odds or you think the CSGL odds are accurate, *don't bet*\n* bet based on the Kelly Criterion\n* gotta have money to make money", "likes": null, "secure_media": null, "link_flair_text": "Betting 101", "id": "2c5pm2", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "DGMavn", "media": null, "score": 16, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "", "subreddit_id": "t5_2zume", "edited": false, "link_flair_css_class": "announcement", "author_flair_css_class": "compl", "downs": 0, "saved": false, "is_self": true, "permalink": "/r/csgobetting/comments/2c5pm2/expected_value_the_rake_and_you_betting_101/", "name": "t3_2c5pm2", "created": 1406770272.0, "url": "http://www.reddit.com/r/csgobetting/comments/2c5pm2/expected_value_the_rake_and_you_betting_101/", "author_flair_text": "", "title": "Expected Value, the Rake, and You: Betting 101", "created_utc": 1406741472.0, "ups": 16, "num_comments": 11, "visited": false, "num_reports": null, "distinguished": null}}, {"kind": "t3", "data": {"domain": "i.imgur.com", "banned_by": null, "media_embed": {}, "subreddit": "funny", "selftext_html": null, "selftext": "", "likes": null, "secure_media": null, "link_flair_text": null, "id": "2c58m2", "gilded": 0, "secure_media_embed": {}, "clicked": false, "stickied": false, "author": "Who_Care_About_Acc", "media": null, "score": 3168, "approved_by": null, "over_18": false, "hidden": false, "thumbnail": "http://a.thumbs.redditmedia.com/TbYaD1L1kkathzSr.jpg", "subreddit_id": "t5_2qh33", "edited": false, "link_flair_css_class": null, "author_flair_css_class": null, "downs": 0, "saved": false, "is_self": false, "permalink": "/r/funny/comments/2c58m2/be_careful_what_you_wish_for/", "name": "t3_2c58m2", "created": 1406760822.0, "url": "http://i.imgur.com/N72vREm.jpg", "author_flair_text": null, "title": "Be careful what you wish for", "created_utc": 1406732022.0, "ups": 3168, "num_comments": 261, "visited": false, "num_reports": null, "distinguished": null}}], "after": "t3_2c58m2", "before": null}}