This is the first time in 5 years where I see the model predicting a team to score NEGATIVE points, thank you Jacksonville for this.
The results: Unfortunately a wrong veto, maybe Atlanta isn’t what it was, or maybe Miami is up for a huge season.
Disculpen la falta de acentos en el siguiente texto.
Despues de lo que paso ayer en el Azteca no queda mas que sacar la calculadora por que la logica ha dejado de ser nuestra aliada en este proceso mundialista.
Asi se ve la tabla a falta de 3 jornadas en el hexagonal de la CONCACAF:
Estos son los 3 partidos restantes para todos:
Las combinaciones son varias. Les recomiendo el simulador del hexagonal que tiene mediotiempo.com
en su pagina.
Desafortunadamente como yo lo veo, iremos a Brasil via Nueva Zelanda. Siendo lo mas realista posible creo que el partido mas importante del martes es el Honduras vs Panama. Lo que Mexico desea es que Honduras le gane a Panama y nos juguemos la repesca el 11 de octubre contra Panama en el Azteca. Asi de sencillo. Evidentemente existe la posibilidad de que Mexico le gane a Estados Unidos el martes y suspire por el boleto directo, ojala suceda, pero no creo. Lo que Mexico debe prevenir a toda costa es jugarse el boleto a Brasil contra Costa Rica en territorio Tico.
Me rehuso a hacer simulaciones donde Mexico no llegue al Mundial. Pero tampoco me han dado motivos para hacer simulaciones para ir a Brasil con el boleto directo.
El comun denominador de estas simulaciones es una victoria de Honduras sobre Panama. Todavia un empate entre esos 2 equipos no es tan grave para Mexico por la diferencia de goles. Tener que hablar de diferencia de goles es una pena.
Esperemos al martes.
De aqui a la otra, ahinos.
PD. Mexico jugaria la ida en Mexico y la vuelta en Nueva Zelanda el 20 de noviembre. Asi los vuelos #porsiocupan
This is the simplest way of picking NFL games. Simply pick the team you think will win each game and you’ll earn points. The strategy I use for this contests is pretty much the same as for those in NFL Pick’em, it just has a minor tweak: I do not use vetos or last minute vetos. What this means is that I’ll trust 100% on what the numbers tell me.
My model usually picks those that are actually the favorites to win the game according to the Vegas lines, but it is not always the case. I hope you can enjoy it as much as I have in the past years!
The Survivor or Eliminator contests are very popular during the NFL season. For the people that don’t know how it works, here is a brief summary: Every week starting week 1 you choose a team that you think will win, if that team wins then you survived and are still alive to play week 2. The trick in this contest is that you are not allowed to choose the same team more than one time each season! The winner will be the player that lasts the longest.
I’ll be using as reference a Survivor pool which I’m playing along with other 67 players in Yahoo!’s Survival.
After badly failing last couple of seasons by trying to be too creative while making my selections for this contests, I have decided to opt for a more conservative approach this season. I will be using the same model created for the usual Pick’em contests and I will choose one of the top 2 teams that have the greater advantage according to the model. If the model suggests a team which I’ve already used in previous weeks, then I will use the second best option and so on.
For the first 2 weeks I’ll use my “gut” feeling since the model will not be created by then. I’ll be as conservative as possible.
For those interested in using a little more than your gut feeling when making your weekly selections for NFL Pick’em contests against the spread, I highly recommend following my picks. I make my picks following a statistical model, the next few paragraphs contain a brief history and explanation about it.
The model was created back in 2008 after taking a Sports Economics class at Boston College during my undergrad. I learned how to predict scores for college football games and after doing some minor tweaks I came up with a very simple yet efficient way to predict outcomes for NFL games. I have won good money by trusting the model and my goal right now is to spend more time on it and try to make it even better and more accurate.
Throughout the years I’ve changed some variables in order to try to make it better, but I have realized that the simpler it is the better results I have gotten. That doesn’t necessarily mean that it can’t be improved by adding more variables, it just means that I need to find the right information to plug into the model.
The purpose of the model is to win bets against the spread for NFL games. It is believed that you need a winning percentage of 52.8% in order to break even
, so the goal is to be above that line to earn some money. I have to tell you, it is not only about the money. For me personally it has to do with having tons of fun and live my Sundays in a whole different way.
It is composed in 2 ways: 90% numbers & 10% gut feeling; the numerical part is computed with a very simple linear regression. The principal variables used are points received, points scored, home field advantage, and bye weeks. The fact that it does not take into consideration things like injuries, weather, yards, etc. could be seen as a flaw and maybe it is, but to compensate that part, I assign “vetos” to games when the score predicted doesn’t seem right. So part of the model is to actually contradict the “numerical” side of the model. Trust me, it just makes it more exciting.
Since I only use data from the current season to run the model, I start computing it on the 3rd week of the season. So far in the 2013 NFL season my record is (week 3 through 5): 25-20 (60%) for the spread at ESPN’s Pigskin Pickem and 23-21-1 (57.78%) for Yahoo! Pickem. To simplify the analysis and because tying when betting is almost like winning, I will consider ties as wins (they hardly occur).
Also, I recently installed what I call a Last Minute Veto. This type of veto is used only after some crucial information is released minutes before kickoff. Basically when a key player is confirmed as inactive for a game, for the majority of the time it only applies to quarterbacks or huge different makers like Calvin Johnson or Adrian Peterson.