Picking Winners in College Football

Before any sports season starts that I am going to be betting on, I try to find as many angles as I can from any and all sources that I believe can give me an advantage in betting on the team that will cover the spread. Some handicappers look at the fundamentals of a team such as how a team blocks and tackles, stops the run, etc. Others look at situational aspects such as how a team, any team, does after a win as a road underdog and now they are favored. Others look at specific team trends, such as the bad ATS (against the spread) record Fresno State has had after a loss.

The bottom line is that it really doesn’t matter how one handicaps, all that matters is whether you are cashing tickets. I like to find some high level filtering approaches that help me put teams in early categories of “play on” or “play against”. Naturally, as a season transpires, teams can move from one category to the other. In some sports, there is credibility in the premise if you can pick who is going to win the game straight-up, you will have a winning year betting. In college football last season, including bowl games, the team with the most points at the end of the game had a 565-202 record against the spread.

Of course you must remember that any underdog that won a game outright obviously covered the number in that game. College football underdogs last season won games straight-up 23.1% of the time. Last season there were 30 teams that covered the spread at a rate of more than 60% for the season including post-season play. Only five of those 30 teams, 16.7%, had a straight-up losing record. Two squads clocked in at .500 records, both 6-6 for the year. The combined SU record of these 30 teams was 275-128, 68.2%. Collectively, they beat the number 67.8% of the time, 257-122. If teams with winning records do such a good job in beating the oddsmaker's line, do losing teams have a strong tendency to have a poor ATS mark? To quote the former governor of Alaska, “you betcha!”

Teams that finished with a below 40% ATS record for the 2008 campaign in college football only won outright 143 times out of 382 games, a 37.4% frequency. The rate that you cashed a ticket betting on these teams was even lower, a 30.2% ATS record. Of the 31 teams that fall into the “below 40% ATS category”, only 7 had winning records with one coming in with a .500 slate.

So, just being able to pick which team will win a game outright should help you increase your winning percentage betting on college football. As noted above, teams with winning records have a better shot at having a winning ATS season. And, just the opposite is true with losing teams dropping more games against the spread than they win. It would be advantageous if we could determine what a team’s final record will be in 2009. Is there a method to project what a teams’ won-loss record will be?

Obviously, one can put many, many hours into studying a team and evaluating their schedule to try to determine what their final record might be before the season kicks-off. This is very time consuming. There is a short-cut to help determine whether a team will win more or fewer games this season compared to their SU record last year.

First, note which teams’ won-loss record improved or worsened by three games or more from the season before. Looking at how teams did in 2008 compared to 2007, 44 of the 120 FBS schools won-loss records varied by three or more games between the two seasons.

Starting with the 2003 season and marking each season’s record, there were some very interesting results.If a team won three or less games from the previous season, there is a very strong trend that they will improve their record the next season. Actual numbers show these teams that dropped down three or more wins from the previous season have the same or a better record 85.1% of the time in the coming season. Over the past four years, this has happened 63 out of 74 times. In this scenario, only 11 teams out of 74 have had a worse record the following year. Some of the teams that suffered a three game or more drop in wins last year are Tennessee, Michigan, and Central Florida.

On the flipside of the equation, when a team improves by three or more total straight-up wins from one season to the next, there is a trend definitely worth noting regarding how their won-loss record will be this year. After a three or more jump in the number of seasonal wins from the previous year, teams fail to improve their win total 80.3% of the time in the following campaign. Eighty-one teams have had a three game or more improvement since 2003, but only 16 of them had a better record the next year after such an improvement. Three of the 24 teams that had such a jump in 2008 and could fall in season wins this year from the previous season are Rice, Minnesota, and Ball State.

The stats and trends I have mentioned are more tools one can use in handicapping college football. The method of looking at the differential in straight-up wins from one season to the next can be beneficial for bettors who like to place wagers on a team’s season wins number. No matter how you do it, having a road map at the beginning of a season on how you believe every team will perform for the year is beneficial to building your bankroll.

Written by Jim Kruger of Vegas Sports Authority.

Learning From the First Quarter in the NBA

I was participating in a panel discussion with some other handicappers last week on a local radio show here in Las Vegas. Having a couple of beers before the show, (just like in trying to meet women, I always thought having a few drinks beforehand always makes you sound much better) the discussion came around to what happens in the first quarter of an NBA game makes no difference at all. I said it might not in that game, but it definitely can in a team’s next game.

We found some good trends last week where a team in their previous game came back after being down at halftime to outright win the game. There was a definite effect on how the team performed in their next game. Let’s see if we can dig something up when a team is down at the end of the first quarter but comes back to win. The sample is games starting with the 2005 season.

Using the premise that our team was down only by one to four points at the end of the first quarter but ended up winning the game straight up, we looked at how they performed in their next game. To get any results of significance, our comeback team in the first game had to have been an underdog. In their next game, they only cover the spread 43.5% of the time, 123-160. The Under happens in 54.7% of these games. These are nice results for such a basic situation.

We are not specifying locations for either the previous or the next game. If we do add locations to the equation, we get a nice improvement on our Under to 66.7% if the come-from-behind game was on the road and we are now playing at home. But, if both the former game and the next one are both at home, our ATS rate drops to 28.6%. Our team must get a little too relaxed staying at home after their comeback win.

Let’s see how altering a couple of qualifiers can dramatically change the results of a trend. First, we are going to change the deficit at the end of the first quarter from being behind one to four points to five to nine points. Next, instead of the team that rallied and won being an underdog, we change them to have been the favorite. Comparing our previous situation where the first game was on the road and now playing at home and the Under happened at a 66.7% rate, just by changing from a dog to a favorite in the previous game and increasing the deficit, the next game now has completely opposite results with a 62.0% play on the Over!

If the team that rallied and won did it in an underdog role, it is probable to assume they are more focused in their next game and play better defense. However, if the team was a favorite and thus expected to win that game, even being down by a larger margin than the underdog had been after the first stanza, the favorite apparently doesn’t play with the same intensity in their next game. Perhaps an added emphasis is put on the offensive side after having to rally to win, but I do believe that it is easier to improve your defensive efficiency as compared to that on offense.

Now let’s increase the opponent’s lead at the end of Q1 to 10 to 15 points. We’ll keep the sites the same, previously away and now home. With the bigger margin to overcome for the win, the Over occurs 68.6% of the time in our next game. Interestingly enough, with the increase in the Q1 deficit to 10 to 15, there is very little difference between whether our team was a dog or a favorite in the first game. That significant enough of a comeback apparently affects all teams in a similar manner allowing the high Over rate in the next contest.

Since we looked at how teams do coming back to win a game after being down after only the first 12 minutes have been played, we need to turn the tables and discover if there are any trends for teams that blow a first quarter lead.

Our first situation will be a team that is ahead by one to four points after Q1 and ends up losing outright. There was nothing worth noting without adding some qualifiers. Let’s use the same sites that we did before: the first game on the road and the next at home. Let’s make our team favored in the first game.

Apparently in their next game, they want to make up for blowing the early lead as they play good defense staying Under the lined total 66.7% of the time. Just out of curiosity, I wanted to see what affect there might be in their next game to a team that loses a first quarter lead quickly on the way to a loss.

I took a team with a 5 to 9 point advantage at the end of Q1. That good feeling of having a lead quickly vanished as I made them behind in the score at halftime before going on to lose the game. There is a hangover effect with our team going just 65-99 ATS, 39.6%, in their very next game without any additional qualifiers. The ATS rate is lowered to 33.0% if the second game’s type of location is not the same as the first. One is a road game, the other is a home game, in either order.

In this scenario, we get a big wagering improvement when the team that blew the Q1 lead in Q2 are playing their next game without any rest. A pitiful 28.0% spread coverage rate, 11-27, occurs without having any consideration for locations. The Over comes through at 76.3%, 29-9. The record of this trend this season is 6-1 ATS and OU. However, the real icing on the cake is if our team’s opponent is playing the game with at least a day off as then the Over improves to a fantastic 25-3, 89.3%.

Here is another reason to look for who led after every quarter. If a team goes wire to wire leading after the first quarter, halftime, and the third quarter on their way to a win, there is a very good trend on the Over in their next game, if it’s at home. The one other qualifier is the team had to have been an underdog in the first game.

An underdog getting a win where they never were behind at the end of a quarter creates a relaxed feeling about playing defense the next time on the hardwood. The Over is 162-110 since the tip-off of the 2005 campaign, a 59.6% success ratio. If you want to drill down just a little bit more to improve that Over rate, we hit 68.7% if their next game is a non-conference one. Most of the time there is not the same amount of focus when going against a non-conference foe. Our super sweet spot is if the previous game was also played at home, the Over skyrockets to an 86.7% mark, 26-4!

The extra factor of no travel plus the comforts of playing in your arena, and perhaps the chance to go out and celebrate an easy win, can have tremendous influence on a team’s next total. Again, let’s look at the opposite: a team that was behind after each of the first three quarters but ended up winning the game covers the point spread in their next game only 36.7% of the time if that game and the previous game were played at home. Sometimes it pays to go out on the road!

How about when a team starts out really clicking on offense and puts up over 30 points in the opening period. Their offense then goes cold in Q2 and they only tally 20 points or less and go on to lose the game. Apparently, our team loses some confidence if they are now playing their next game as an underdog because they only cover the linesmaker’s number 32.8% of the time. That poor line-covering rate falls to 22.2% if our team was favored in their previous game where they went cold in Q2 after a hot start.

Paying attention to what happens in the first quarter of a game can make you some cash in the following game. You just have to know what to look for.

Jim Kruger of Vegas Sports Authority did all this work, probably without beers.

What a Difference a Day can make Betting Hoops

There are a multitude of different angles, trends, and tendencies that can help a person pick winners in college basketball. Some of them are well known and some are only known by a few people. Some are obvious and there are some that are obscure.

Some, such as the trend to play on an unranked home team if they are playing a ranked team and the home team is favored, become almost urban legend. Often these types of trends will have a supposed unbelievable gaudy record attached to them. Like many trends, they might work for a while until enough people have found out about them and drive the line too far in one direction and subsequently the trend starts losing. Also, the linesmakers might discover the trend, after all, that is their job, and help end its profitability. They do this by adjusting the line enough against the trend that it can go from a winning angle to one that burns sports bettors’ money.

I don’t know how many sports bettors realize there are different tendencies in college hoops for certain days of the week. What results teams have in certain situations on Saturdays might be totally different than the same situation has on Wednesdays. Thursday games might have an opposite pattern to Sunday games.

Why do we see such contrasts in ATS and O/U results on different days of the week? There are a number of potential reasons. Very rarely is a game during the week, Monday through Friday, played during the day. Almost 100% of these games, unless on a holiday, take place at night.
A good portion of the games on Saturdays and Sundays are during the day. Teams can play differently during the day as compared to in the evening.Weekday games at many venues won’t draw the same size of crowd as weekend games. The students at a Tuesday night game will probably be more subdued with classes and tests the next day than they would on a Saturday. Alumni attendance might very well be down and the alums more reserved with a full day of work looming ahead. Home-court crowds with their noise and fervor do influence teams, both home and visitors.

Most conferences play a basic schedule during league play with variations thrown in, many times for television games. There are two main basic schedules, the Thursday-Saturday and the Wednesday-Saturday formats. The obvious difference is the extra day of rest the Wednesday-Saturday schedule provides.

With games being played on Thursday night, Friday in most all cases becomes a travel day. Depending upon the length and mode of travel, any practice or preparation time for their Saturday opponent can be greatly reduced. This is compounded even more so if the Saturday game is being played during the day. There are many significant differences in a team’s results playing on Saturday as to whether the team is off of a Thursday game or one with more rest, such as a Tuesday or Wednesday clash.

Conferences that are on the Thursday-Saturday type of schedule are the Big Sky, Big West, Horizon, Ohio Valley Conference, Pac-10, Sun Belt, Southern, WAC, and West Coast Conference. Everybody else is on the Wednesday-Saturday timetable with a couple of exceptions. The Ivy League is the most unique playing their conference games on Fridays and Saturdays. The Metro Atlantic’s base is a Friday-Sunday agenda, but has variations just like most all conferences. All trends cited start with the 2000 season and only pertain to games between two teams of the same conference.If you just look at the most basic results of Saturday games, about the only thing worth noting is big home favorites of 14 or more points don’t do well, 336-404, 45.4%, and big road dogs obviously do. This is not a situation you want to bet blindly, but it is enough of an edge to be aware of before you place a wager. There was not even a trend that good for the basic results with no additional qualifiers of games being played on Tuesday, Wednesday, or Thursday.

However starting with Monday, there are some situations worth talking about. In conference play, if a team had a game on Saturday and is now playing two days later on Monday, there is a strong overall bias to the Under, 518-400, 56.4%. The Under is strongest if our team is a road favorite going 78-51, 60.5%. There is a sweet spot if the away team is favored by 3 to 6.5 points, 40-17 Under, 70.2%. Wagering on the Under on away dogs getting up to 6.5 points also does quite well, 97-61, 61.4%.

There is only one side play on Monday teams playing with just one day of rest that is worth noting and it is just a small slice. Home dogs of 3 to 6.5 points have only been covering the point spread 41.7% of the time since the 2000 season.Now let’s look at games played on Monday by a team with more than one day of rest. While home favorites with just one day of rest covered the point spread 49.2% of the time, our better-rested home squads laying points are beating the number just 37.9% of the time. That is a huge differential. We no longer have an overall Under bias, in our previous Monday example, 56.4%, now just 50.5%. Road favorites now actually have a small lean to the Over, 50.9%, as compared to a 60.5% Under trend.

Our Monday, teams with more rest are doing well as single-digit road dogs cashing tickets at a 58.3% rate versus a 51.4% clip for teams who played Saturday. The amount of rest a team has when playing on Monday definitely makes a difference.

How about if we add a qualifier into this Monday game mix. What if our team is off of a road win? Will the additional rest give us a contrast in results? It shows a huge difference between home favorites of the teams with extra rest versus the ones with just one day, a 32.3% ATS mark compared to a 56.5% record respectively. The team with extra time to think about their road win and be congratulated by their fans and media does much more poorly than the squad who has a very quick turnaround playing their next game.

Incidentally, those Monday home faves off of a Saturday road win are an excellent Under wager, 66.2% winners. The sweet spot here is from pick’em to less than a seven point chalk, an amazing 25-4 Under mark. With such interesting differences in teams playing on Monday off of a road win, let’s see what the same situation in Saturday games provides.

A great play against spot is when a team wins a road game on Thursday and is now put in the position of a home favorite on Saturday, 45-77 ATS, 36.9%. A fantastic optimum wagering spot is if the home team is favored by 10 to 20 points, a pitiful 24.4% record of covering the spread. As compared to home favorites on Monday off a road win with a quick turnaround, we get the opposite results if the game happens to be played on a Saturday.

Now looking at a team that has more than one day of rest playing on a Saturday and their previous game was a road win, there is nothing of ATS significance as a home favorite, almost an exact 50% rate. However, if they are a single-digit home fave they have been going Over the lined total 55.3% of the time.

There is a 56.0% ATS edge if our rested team playing on Saturday off of a road win is still on the road and is favored. If this team is an Away dog, there is a sweet spot of 58.2% ATS if they are getting 3 to 10 points.

Games played on the same day of the week can show widely different results depending upon how much rest a team has and the results and location of their previous game.

Jim Kruger of Vegas Sports Authority wrote this article.