Something I stumbled across

[floridagolfer]

I looked at the ATS records of about 100 CBB teams and noticed that teams that get outscored on the road by an average of 10 ppg or more also have poor ATS records. Yeah, they not only lose, but they tend to get blown out a lot.

Of the approximately 100 teams I looked at, I found 15 whose road scoring average is at least 10 ppg less than what it gives up. Their combined ATS record in road games (strictly road games, not those at neutral sites) is 53-83-1. So, if you went against those teams in road games, you'd have a winning percentage of .609. (For the record, I only counted those games in which there was a line posted, and when a team's road scoring differential improved to be less than 10 ppg, I didn't count those games until it once again met that criterion.)

I sure would like to know if someone with a database that includes a larger number of Division I teams is able to confirm these kind of numbers.

[smoke a bowl]

You are testing something that is correlated. Obviously teams that are avg 10 points less on the road are getting blasted some games. The problem is that we didn't know the teams were going to perform 10 points worse than their opponents before the season started. Now that the lines have adjusted for these performances, those teams should go 50/50 vs the spread going forward.

Another words, if you were to run the same test with teams that outscored their opponents at home by an avg of 10 points or more, you will probably get similar results favoring the teams that won by an avg of 10 points or more.

[reno cool]

smoke a bowl is absolutely right. Perhaps you want to say test the teams that get outscored by>10ppg in the first half of season, and see how they do in the second half.

[Data]

smoke a bowl is absolutely right. Perhaps you want to say test the teams that get outscored by>10ppg in the first half of season, and see how they do in the second half.

reno cool, when I said I am tired of your nonsense I did not mean just your political views. You are by far the worst poster in the Think Tank. It is hard to believe but again and again, if you disagree with a concept then it is a right concept that you just could not grasp, while if you agree with something, like you did here, it is something blatantly wrong.

You can say whatever you want in other forums (Politics, PT etc) but the Think Tank should be kept nonsense-free. You have not contributed anything to this forum but nonsense and truly proved that you are incapable of anything else. That is why I just wish you get banned from the Think Tank.

[reno cool]

did I hurt your feelings there buddy? Maybe you should take it to the players talk.

[Peep]

I donno Data, I agree with Reno and Smoke a bowl.

The guy is testing the same thing twice. If you test teams that get blown out for their ATS against the spread in the same games, well, duh......

[Data]

Peep, since I respect you for the other things...

Based on what he wrote, the guy is not looking at the past results and notices obvious correlation between losing and not covering. For every single game, he looks at how a team performs if that team averaged -10 points or worse up until that game. It does NOT include that game results and, therefore, there is no perceived correlation.

[smoke a bowl]

Data, you have to be misreading the original post. The way I read it, there is no way that his test has any bearing on future results.

[Justin7]

Perhaps Floridagolfer could clarify. From what I read, I thought the same thing as smoke and reno.

[curious]

I agree with Data. What the original poster said is that he looked at the road average game by game and included games where the PF/PA delta was >= -10 at that point in time.

The events are not correlated and are predictive.

[DeluxeLiner]

This is interesting, though I would also like to know if someone has more information on this like the OP requested.

[LT Profits]

I must say that the OP's wording is ambiguous. I interpreted it as him including the games in his numbers (backfitting), which would be useless. Obviously, if Data's interpretation is correct, then the numbers become valid. We need florida to clarify.

[Pancho sanza]

Teams with bad records straight up will generally have bad ATS records, this is nothing new.

[Data]

when a team's road scoring differential improved to be less than 10 ppg, I didn't count those games until it once again met that criterion.

I do not see how this part can leave any misunderstanding on what the OP meant. But I do stand corrected, reno cool is not a complete outsider in this forum as I previously thought.

[durito]

Teams with bad records straight up will generally have bad ATS records, this is nothing new.

huh

[LT Profits]

Teams with bad records straight up will generally have bad ATS records, this is nothing new.

May I present the Oklahoma City Thunder.

[curious]

May I present the Oklahoma City Thunder.

I was thinking the same thing. And Minnesota was in that list until they self destructed a few weeks ago. Minn ATS was something ridiculous compared to their record for a long time.

[Pancho sanza]

May I present the Oklahoma City Thunder.

There are exceptions, like when everyone knows the team will suck, ie, OK City.

If you look at the top 5 and bottom 5 teams in any league, add up their ATS records, you'll see what I mean.

This fellow is likely gathering data on teams that are the dregs of the league, so no surprise they have crappy ATS records.

[smoke a bowl]

I do not see how this part can leave any misunderstanding on what the OP meant. But I do stand corrected, reno cool is not a complete outsider in this forum as I previously thought.

Reading that makes me think you could be interpreting it right, but if that is the case then I would still be skeptical due to sample size.

[DukeJohn]

May I present the Oklahoma City Thunder.

Well, Florida, is referring to College Basket Ball anyway... It would be interesting to see if it has always been that way, but it seems like a huge undertaking to begin processing since each week you would have to have a rolling average of every College Team, well, Division I, but still... Anyway, something to spend some time on for a couple of weeks working through the night.

[smoke a bowl]

Well, Florida, is referring to College Basket Ball anyway... It would be interesting to see if it has always been that way, but it seems like a huge undertaking to begin processing since each week you would have to have a rolling average of every College Team, well, Division I, but still... Anyway, something to spend some time on for a couple of weeks working through the night.

Currently I would lay a dime to a wooden nickel that this theory has no validity but would love to be wrong.

[floridagolfer]

Geez, now that you guys starting discussing my original post, even I'M confused. Let me see if I can clarify my original thought process.

As I look through my database today, I notice that Air Force, in road games (not neutral sites) in which there was a number posted, was outscored in those games by an average of about 14 ppg (55.3 to 69.9). I also notice that Air Force is 2-6 ATS in those games. My database includes information for about 105 teams; I don't have time to do all 340-some Division I teams. So my question is, once a team has, say, 5 road games in which to compile averages, does this scoring average relate to poor ATS performance?

Other examples:
DePaul, outscored in road games by about 16 ppg, 4-7 ATS in those games
Fordham, outscored in road games by about 19 ppg, 3-7 ATS in those games
Indiana, outscored in road games by about 17 ppg, 4-5 ATS in those games
Iowa State, outscored in road games by about 10.5 ppg, 3-6-1 ATS in those games
St. John's, outscored in road games by about 16 ppg, 1-7 ATS in those games

Of the 15 teams I cited in my original post, only one had (at the time) a winning ATS record in those games.

So, if I'm conducting my sampling incorrectly, well, that's why I'm asking people who know more about these things. The last thing any of us want to do is risk our money on flawed research. Thanks.

[smoke a bowl]

Geez, now that you guys starting discussing my original post, even I'M confused. Let me see if I can clarify my original thought process.

As I look through my database today, I notice that Air Force, in road games (not neutral sites) in which there was a number posted, was outscored in those games by an average of about 14 ppg (55.3 to 69.9). I also notice that Air Force is 2-6 ATS in those games. My database includes information for about 105 teams; I don't have time to do all 340-some Division I teams. So my question is, once a team has, say, 5 road games in which to compile averages, does this scoring average relate to poor ATS performance?

Other examples:
DePaul, outscored in road games by about 16 ppg, 4-7 ATS in those games
Fordham, outscored in road games by about 19 ppg, 3-7 ATS in those games
Indiana, outscored in road games by about 17 ppg, 4-5 ATS in those games
Iowa State, outscored in road games by about 10.5 ppg, 3-6-1 ATS in those games
St. John's, outscored in road games by about 16 ppg, 1-7 ATS in those games

Of the 15 teams I cited in my original post, only one had (at the time) a winning ATS record in those games.

So, if I'm conducting my sampling incorrectly, well, that's why I'm asking people who know more about these things. The last thing any of us want to do is risk our money on flawed research. Thanks.

Thx for clarifying Florida. I'm pretty sure the way you described this that the results are insignificant because you are testing the same games but I could be missing something. Please don't mistake my posts for anything else besides trying to be helpful. Please feel free to keep sharing thoughts and opinions here as there are a lot of good,knowledgeable,helpful people here in the tank.

[Data]

I do not see how this part can leave any misunderstanding on what the OP meant. But I do stand corrected, reno cool is not a complete outsider in this forum as I previously thought.

I was wrong. I was assuming that what the OP meant is expressed in what he said but it was not. Nonetheless, I stand by my reading comprehension.

[floridagolfer]

Thx for clarifying Florida. I'm pretty sure the way you described this that the results are insignificant because you are testing the same games but I could be missing something. Please don't mistake my posts for anything else besides trying to be helpful. Please feel free to keep sharing thoughts and opinions here as there are a lot of good,knowledgeable,helpful people here in the tank.

No problem. All reasonable input is welcome.

Someone suggested that the reverse would be true -- teams with a plus scoring average of 10 or more at HOME might have very good ATS record in those games. But a quick glimpse of this does not show that to be the case. Without going through my entire database, I quickly see that all the teams listed below are outscoring their opponents at home by more than 10 ppg, but the ATS records do not show a similar good performance:
UAB 5-4 ATS
UConn 3-8
Duke 7-7-1
Florida 5-5
Kentucky 6-6
Marquette 5-6-1
UNC 3-9
Notre Dame 3-5
Oklahoma 5-7
Texas 4-8
What does all this prove? I don't know; maybe nothing at all.

[Peep]

Yes, it may be an easy game, but not quite that easy.

[evo34]

No, Data, the original post was quite clear. The guy was making the same absurd argument as people who say, "the NFL team with more rushing attempts in a game will likely win the game." It's observing the past; nothing to do with the future -- which is what everyone else immediately recognized except you. I wouldn;t bother to say this if it weren't for your inexplicably condescending tone.

[curious]

No, Data, the original post was quite clear. The guy was making the same absurd argument as people who say, "the NFL team with more rushing attempts in a game will likely win the game." It's observing the past; nothing to do with the future -- which is what everyone else immediately recognized except you. I wouldn;t bother to say this if it weren't for your inexplicably condescending tone.

This is what I thought the dude said.

If I start tracking games on the first day of the season, and I look at the road scoring record of each team.

And I make a list of teams that get outscored by an average of 10 points per game, and say I wait for a team to have played 3 road games before adding them to the list. Then, I start betting against any team from the list when it plays on the road.

I recalculate every team's road scoring record every day and sometimes add new teams to the list and sometimes remove teams from the list.

The points differential is a predictor that a given team won't cover ATS on the road if its YTD scoring record shows that it gets outscored by an average of 10 or more points when on the road.

I thought that was what he was saying.

Which is a very different thing then what you said.

[curious]

Floridagolfer, can you run this test to validate your findings?

Hi floridagolfer,

there is a heated debate going on in this thread as to whether you found something that is predictive or just did the equivalent of "teams that get 500 yards passing in a game usually win that game".

I think a way to show whether or not what you have is predictive is to calculate the road scoring differential for all NCAAB teams for this season and then every day post a list of the teams that are outscored by an average of 10 points on the road that are playing on the road that day.

Then we can track the results and see if your theory is predictive.

This statistic might be available somewhere. And it would have to be updated daily.

Would this be too much work?

[floridagolfer]

Hi floridagolfer,

there is a heated debate going on in this thread as to whether you found something that is predictive or just did the equivalent of "teams that get 500 yards passing in a game usually win that game".

I think a way to show whether or not what you have is predictive is to calculate the road scoring differential for all NCAAB teams for this season and then every day post a list of the teams that are outscored by an average of 10 points on the road that are playing on the road that day.

Then we can track the results and see if your theory is predictive.

This statistic might be available somewhere. And it would have to be updated daily.

Would this be too much work?

It would not be too much work in the proper program was established, and while I have a database of information, it's something I created myself and I'm not a whiz in this kind of thing; it's not a complex or extensive document. I only track about one-third of the Division I teams. I could easily post the teams playing every day that fall into this category, but before I did that, I wanted to be sure my sampling was worthwhile; just because I have a statistic for 100 teams, that doesn't mean the information necessarily is representative of all 340-some teams. Maybe in the offseason I'll work toward increasing the number of teams I'm able to track. I need to find an Excel expert who can refine what I've already done.

Thanks, everyone, for your input.

[curious]

It would not be too much work in the proper program was established, and while I have a database of information, it's something I created myself and I'm not a whiz in this kind of thing; it's not a complex or extensive document. I only track about one-third of the Division I teams. I could easily post the teams playing every day that fall into this category, but before I did that, I wanted to be sure my sampling was worthwhile; just because I have a statistic for 100 teams, that doesn't mean the information necessarily is representative of all 340-some teams. Maybe in the offseason I'll work toward increasing the number of teams I'm able to track. I need to find an Excel expert who can refine what I've already done.

Thanks, everyone, for your input.

So post what you do have. It would be informative. The math boyz will now yell at me that the sample size is too small, but I have found edges before using a small sample size.

There are plenty of programmers on here would could create a prediction model if the theory can be developed a bit more.

Posting whatever you do have daily, if it turns out that it is predictive, would motivate them to get involved.

[DukeJohn]

Well checking last year, using this site:

http://www.scoresline.com/teamlist.asp?S=NCAAB

I stopped after the first ten or so teams... It was showing about even, flat betting... I am sure you could use some form of money management to probably make it profitable, if you could discover other values associated with the pick if you were so inclined.

BOL

[floridagolfer]

So post what you do have. It would be informative. The math boyz will now yell at me that the sample size is too small, but I have found edges before using a small sample size.

There are plenty of programmers on here would could create a prediction model if the theory can be developed a bit more.

Posting whatever you do have daily, if it turns out that it is predictive, would motivate them to get involved.

OK, here it is. These are the teams from my database who fit the -10 ppg road criterion (and, where noted, those playing road games this weekend, 2/28 and 3/1). We'll see how it goes.

Air Force
Colorado (Sat.)
DePaul
Fordham (Sat.)
Geo. Wash. (Sat.)
Georgia (Sun.)
Indiana (Sat.)
Iowa St. (Sat.)
Maryland (Sun.)
Oregon
Rice
St. John's (Sat.)
SMU
Southern Miss (Sat.)
Texas Tech
Wyoming (Sat.)

[Data]

No, Data, the original post was quite clear.

Please provide a clear rational explanation to what does this

"when a team's road scoring differential improved to be less than 10 ppg, I didn't count those games until it once again met that criterion"

has anything to do with what the OP actually has done. Until you or anybody else does this I maintain that my understanding was correct.

The guy was making the same absurd argument as people who say, "the NFL team with more rushing attempts in a game will likely win the game." It's observing the past; nothing to do with the future -- which is what everyone else immediately recognized except you.

Again, based on what he wrote, it was an example of datamining and datamining is very common. The dataminers select certain criteria (e.g. av<=-10) then they select games where one of the playing team meets that criteria and look how those teams do ATS. Effectively, they check that on game by game basis and a given team may meet the criteria for some games yet not meet it for the other games. Obviously, the teams parameters can "improve" (as per the OP) over time.

What the OP admittedly has done is looking at the past results. This requires one single observation, the results he looked at are static, they do not change. How the static result can "improve" (as per the OP)?

I wouldn;t bother to say this if it weren't for your inexplicably condescending tone.

I thought the OP has done something pretty common which, if used properly, may be a part of a valid technic. Everybody else, except Curious who initially agreed with me, thought that he has done something different, something meaningless beyond any critics. So, who are the misanthropes here? Since this proves what a philanthropist I am, I should be forgiven for expressing my strong sentiment towards reno cool and all the blame should be laid on him.

[HedgeHog]

Two things I get from this thread is (1) that the OP's theory is flawed, because teams that get beaten badly on the road are naturally going to have poor points scored vs points allowed (duh). And (2) Data's complaint against Reno is a distraction and not proper in this Think Tank discussion (take it to Player's Forum).