Partial damage to plantations, horticulture and standing crops. Slippery roads and traffic disruption on roads. "Impact expected due to rain over parts of Delhi & adjoining areas: 1. It also posted an advisory on Twitter about the possible impact of the downpour. But in those other cases, where we just have “regular” rain, what happens?īelow I re-graphed and modeled, excluding games with more than an inch of rain.In view of the incessant rain, the Indian Meteorological Department has issued a yellow warning for Delhi NCR region. By all means, if a game is for sure to be played in a hurricane, then go bet that under before it’s off the board. I’m typically against removing naturally-occurring “outliers,” but in this instance I’m looking for consistent betting value. There are only 46 games in the data (0.6%) with more than an inch of precipitation. A single inch of rain during a college football game would be heavy rain for 3-4 hours straight. The American Meteorological Society defines “heavy” rain between 0.3 and two inches per hour (the only thing higher is “violent” rainfall). My analysis is looking at precipitation during the game often, waiting out the lightning also involves waiting out the rain. Another is that, if it rains hard enough, there might be some lightning involved, and the game will be suspended until the lightning is out of the area. One caveat is accurate weather forecasts. However, as with windy games, there are some caveats. The linear model (blue line) above shows about one point of value for every quarter-inch of precipitation during the game (with lots of noise). Certainly some value here, but let’s not go running to the books yet. (If you’re curious about those three wettest games, they were Louisville at Southern Miss in 2012, Notre Dame at NC State in 2016, and Kansas State at Baylor in 2010.) Instead of using the binary response of over or under, let’s look at how total precipitation affects the difference between actual points and the total line (negative values mean the total was under). The table below indicates that maybe bookmakers aren’t moving total lines enough. Of the 7,300 games I have data for, only 702 of them (9.6%) had any precipitation (almost all of which is rain). Now, do the sportsbooks adjust the line enough? Well, maybe not. I won’t list it here, but when comparing scoring models that don’t include weather versus books’ total lines the answer is clear.
At its worst, teams completely abandon any identity (except stubborn-ass Brian Kelly in a hurricane) and you’re reduced to watching 22 brown uniforms slip and slide in a mud field for four hours. Rain is more “eh.” It’s ugly, it’s sloppy.
Find me someone who didn’t like that Buffalo and Indy snow game last year. Everyone likes a snow game - it’s pretty on HD TV, and it tends to create slightly wacky things. After finishing up showing value in unders in windy games, I wanted to get more out of the weather data by looking at precipitation.
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