ESPN Magazine recently had a "conspiracy theories" issue, in which it explored (among other things) the long-held, popular theory that basketball is fixed. College basketball, in particular. IIRC, the preconditions for a fixed game tended to be:<p>- Non-tournament, regular season play (b/c not as many bettors and media would be paying attention)<p>- The favorite team is favored by 11 or more points<p>- The favorite team is dominated by one or two very strong players<p>If one player controls his team's play, and he's favored by 11+ points, he has the incentive, the ability, and the margin to shave points without risking losing the game. With a smaller point spread, on the other hand, it's too risky. For reasons I can't recall, an 11-point spread was the magic number. It provided just enough cushion to cover shaving, without jeopardizing the nominal win.<p>When analysts looked at the history of games that met these criteria, they found consistently abnormal distributions of outcomes in favor of the winning team, but just south of the spread. They estimated that about 3-4% of games in the study sample are quite likely to have been fixed.<p>At any rate, it would be interesting to see bigger data sets plied for this sort of thing.
"On the other hand, all the leagues have significantly lower average hotness in the first half compared to the second half, so maybe it’s not just the NBA that has a boring first half problem."<p>This seems to be a misconception. It stands to reason that the chart will grow jumpier as you near the end of the game. In options lingo, the implied volatility will be more stable the further you are from expiry (the end of the game). Theta decay and all that. The market is basically giving you an integrated forecast from each point in time until the final buzzer, and as that window shrinks you expect the odds to be jumping around more.
It strikes me as a shame that people can be addicted to gambling and we see it as a moral problem. For example, gambling data around elections seems highly likely to be more useful than opinion polls are. After all, this is simply another application of the ideas behind how we expect markets to function.<p>Gambling is one of the few ways you can incentivise someone to be honest with you about their opinion, and for that reason I think it's actually a mass of untapped potential.
This is pretty interesting and fun data. The article talks a lot about what games are exciting and it basis this off of wild fluctuations in a team's chances of winning. This makes perfect sense, but there is more to it than that.<p>If there are two teams playing each other and the score is 43-36 with plenty of ups and downs along the way, is it an exciting game? Sure sounds like it. What if those two teams are the Browns and Dolphins playing in a meaningless game in December with two backup quarterbacks? Is that game still exciting?<p>These things are hard to quantify because the algorithm needs to put things into context that it may not be able to understand.
Link to the site being explained: <a href="http://www.gambletron2000.com/" rel="nofollow">http://www.gambletron2000.com/</a><p>and the non-RapGenius about URL:
<a href="http://www.gambletron2000.com/about" rel="nofollow">http://www.gambletron2000.com/about</a><p>This is unbelievably cool. I am blown away.
Blatant blogspam? It's a single paragraph that links to <a href="http://news.rapgenius.com/Atodd-what-real-time-gambling-data-reveals-about-sports-introducing-gambletron-2000-annotated" rel="nofollow">http://news.rapgenius.com/Atodd-what-real-time-gambling-data...</a><p>Edit: I guess it's cross-promotion, which is fine just not what I expected.
How do these betting sites handle real-time events? I believe there was a case recently where a man at the Australian Open tennis in Melbourne was arrested for transmitting point information outside the stadium before it could be broadcast on television (there is always broadcast delay), which obviously could give you a big advantage. I think European football ones go into a vol auction (pause betting) when a goal is scored? But you could have a guy sitting in the stadium, wired up with a buzzer to press when a striker goes one on one with a goalie, or a penalty is awarded, and then just go all-in on the market? The whole thing is a can of worms.
Great stuff. Very entertaining read.<p>This said, I am a bit skeptical about the asessment of "game hotness". Of course games that are tied or close near the end exhibit significant agitation at that stage (and "boring 1st halves") from a betting standpoint.<p>This might sound obvious, but great games are not just about the outcome. Think of something like soccer, where few points are scored in a given match. It would be very interesting to see what the data looks like for those, as there are fewer data points.
<i>"Maybe there’s a slight tendency for teams in the 10-20% range to win at a slightly higher rate than expected (and consequently teams in the 80-90% range to lose more than expected), but the difference is pretty small, and given the number of observations and parameters, it would not be surprising if this deviation occurred completely randomly."</i><p>This is a well known phenomena [1] that manifests in almost all prediction markets. People tend to overestimate the likelihood of likely events, and underestimate the chance of a rare events. If you're patient (and, importantly, trading fees are low enough) then it is usually possible to profit from these "sure thing" positions over many event<p>1. Just one of the many links you find in google on the subject: <a href="http://journal.sjdm.org/9729b/jdm9729b.html" rel="nofollow">http://journal.sjdm.org/9729b/jdm9729b.html</a>
It will be interesting to compare the data and graphs presented here to historic win probability charts provided by Advanced NFL Stats[1] for the NFL and Fangraphs[2] for MLB. See how Vegas stacks up against models based on historical data.<p>[1] <a href="http://live.advancednflstats.com/" rel="nofollow">http://live.advancednflstats.com/</a>
[2] <a href="http://www.fangraphs.com/wins.aspx?date=2013-10-30&team=Red%20Sox&dh=0&season=2013" rel="nofollow">http://www.fangraphs.com/wins.aspx?date=2013-10-30&team=Red%...</a>
I think the Recap functionality might be understated. If they can add more color data about event times, actual scores, player names, then I think they could be on to something in automating recaps of games.
Pretty cool data, but doesn't reveal anything too insightful into peoples' gambling behaviors regarding sports. People are prone to a game's intangible momentum, who knew?
I wonder where they get their data, I feel that the community could come up with a better ranking algorithm than the square distance formula that they give
I wonder how much better the prediction market does compared to a predictive model based on the score and time remaining. Given data on the games, it would be pretty easy to develop a model on the P(winning|scores,time_remaining). Would that do as well as humans in aggregate? Obviously it doesn't take into account momentum, how well the teams are playing, etc.
Another thought: Some indication of a "trade volume" equivalent might be useful as well (and probably a good input for a "hotness" score, as more popular games will probably get more bets). I don't know if that information is available though.