Since more people wager on football than any other sports it’s usually the easiest game to figure out how to bet. If you don’t know what to do, you can probably ask anyone in the sports book for instructions. The people visiting the casino might not know everything but they can give you the basics. Here’s a fairly thorough look at the different ways you can wager on football in Las Vegas.


Many people will say that the odds on a spread bet are even, paying 1:1. But this is not true. The actual odds are 0.90:1. For every dollar bet, you can win 90 cents. When checking out the spread, you’ll usually see a number listed next to each spread. That number, which is your stake, is posted as -110. This number tells you how much you have to bet to win $100. If you put $110 on either team, you stand to win $100. If you bet $11.00, you can win $10.00. Every NFL point spread works this way.
It is also widely known as the over/under and, just like the point-spread myth, it is not Las Vegas' guess at how many points will be scored in the game by both teams combined. It's a number it feels will encourage just as many bets on the over as the under. If you picked the under 47.5, you want tough defense and the team running the ball to eat the clock. If you pick the over, you want offensive fireworks and long bombs for TDs. In totals betting, you are predicting whether the combined total score will be more than or less than the total.

Another way to beat football point spreads is to shop for off market prices. For example, let's say you're shopping online betting sites and see every site is offering Vikings +7.0. Then, you stumble upon one site that's offering +7.5. There's a good chance that this is a +EV wager, simply because it is out of sync with every other site. Please note that this strategy isn't quite the same as simply shopping for the best lines. Here, you're specifically looking for wagers that are +EV because they're against the market.
!function(e){function n(t){if(r[t])return r[t].exports;var i=r[t]={i:t,l:!1,exports:{}};return e[t].call(i.exports,i,i.exports,n),i.l=!0,i.exports}var t=window.webpackJsonp;window.webpackJsonp=function(n,r,o){for(var u,s,a=0,l=[];a1)for(var t=1;td)return!1;if(p>f)return!1;var e=window.require.hasModule("shared/browser")&&window.require("shared/browser");return!e||!e.opera}function s(){var e="";return"quora.com"==window.Q.subdomainSuffix&&(e+=[window.location.protocol,"//log.quora.com"].join("")),e+="/ajax/log_errors_3RD_PARTY_POST"}function a(){var e=o(h);h=[],0!==e.length&&c(s(),{revision:window.Q.revision,errors:JSON.stringify(e)})}var l=t("./third_party/tracekit.js"),c=t("./shared/basicrpc.js").rpc;l.remoteFetching=!1,l.collectWindowErrors=!0,l.report.subscribe(r);var f=10,d=window.Q&&window.Q.errorSamplingRate||1,h=[],p=0,m=i(a,1e3),w=window.console&&!(window.NODE_JS&&window.UNIT_TEST);n.report=function(e){try{w&&console.error(e.stack||e),l.report(e)}catch(e){}};var y=function(e,n,t){r({name:n,message:t,source:e,stack:l.computeStackTrace.ofCaller().stack||[]}),w&&console.error(t)};n.logJsError=y.bind(null,"js"),n.logMobileJsError=y.bind(null,"mobile_js")},"./shared/globals.js":function(e,n,t){var r=t("./shared/links.js");(window.Q=window.Q||{}).openUrl=function(e,n){var t=e.href;return r.linkClicked(t,n),window.open(t).opener=null,!1}},"./shared/links.js":function(e,n){var t=[];n.onLinkClick=function(e){t.push(e)},n.linkClicked=function(e,n){for(var r=0;r>>0;if("function"!=typeof e)throw new TypeError;for(arguments.length>1&&(t=n),r=0;r>>0,r=arguments.length>=2?arguments[1]:void 0,i=0;i>>0;if(0===i)return-1;var o=+n||0;if(Math.abs(o)===Infinity&&(o=0),o>=i)return-1;for(t=Math.max(o>=0?o:i-Math.abs(o),0);t>>0;if("function"!=typeof e)throw new TypeError(e+" is not a function");for(arguments.length>1&&(t=n),r=0;r>>0;if("function"!=typeof e)throw new TypeError(e+" is not a function");for(arguments.length>1&&(t=n),r=new Array(u),i=0;i>>0;if("function"!=typeof e)throw new TypeError;for(var r=[],i=arguments.length>=2?arguments[1]:void 0,o=0;o>>0,i=0;if(2==arguments.length)n=arguments[1];else{for(;i=r)throw new TypeError("Reduce of empty array with no initial value");n=t[i++]}for(;i>>0;if(0===i)return-1;for(n=i-1,arguments.length>1&&(n=Number(arguments[1]),n!=n?n=0:0!==n&&n!=1/0&&n!=-1/0&&(n=(n>0||-1)*Math.floor(Math.abs(n)))),t=n>=0?Math.min(n,i-1):i-Math.abs(n);t>=0;t--)if(t in r&&r[t]===e)return t;return-1};t(Array.prototype,"lastIndexOf",c)}if(!Array.prototype.includes){var f=function(e){"use strict";if(null==this)throw new TypeError("Array.prototype.includes called on null or undefined");var n=Object(this),t=parseInt(n.length,10)||0;if(0===t)return!1;var r,i=parseInt(arguments[1],10)||0;i>=0?r=i:(r=t+i)<0&&(r=0);for(var o;r
Parlays - these might be the most popular bets out there, especially among novice and amateur bettors, perhaps because of the lure of betting a small amount for a potentially big payoff. But they are fool's gold at best. Parlays involve wagering on two or more games on the same bet following the casino's pre-determined payout scale. Each game on a parlay must win for the bet to be a winner.
Machine learning models can make predictions in real time based on data from numerous disparate sources, such as player performance, weather, fan sentiment, etc. Some models have shown accuracy slightly higher than domain experts.[61] These models require a large amount of data that is comparable and well organized prior to analysis, which makes them particularly well suited to predicting the outcome of Esports matches, where large amounts of well structured data is available.[citation needed]
Total: Also called the over/under, it is a number set by the sportsbooks that proposes a number of points that will be scored in the game by both teams combined. Then, fans predict whether there will be more points or less points than the ‘total.’ If you bet the under 41.5, you are hoping for a tough defensive battle with lots of running game. Pick the over, and presumably you feel this will be a high-scoring game. In short, you are predicting whether the combined total score will be more than (over) or less than (under) the total.
×