SDQL Thread

JROCK1966

Pretty much a regular
Have any of you dabbled in this stuff at all? It really intrigues me and after a couple SNAFU's I think I'm getting the hang of it. Here's a couple of pics with a scenario of college football home dogs where the scoring margin of the doggie is greater than their opponent's scoring margin. I had to separate my screenshots into two because they were so big. You'll notice on the first pic, overall the trend is not all that great with poor historical SU & ATS records.

HDmargin1.jpg

But, digging a bit further on the 2nd pic, we see (green boxes) that it is 8-3-1 ATS in it's last 11 occurences and 5-0-1 in it's last 6. The trend is active on Ohio and Army this week.


HDmargin2.jpg
 
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I'd like this thread to be an aid to us all...if you are interested, I'll try and teach what I know. If not interested in learning, maybe you have some scenarios you would like to suggest we look up??

:eatingchinese:
 
Well, I think I figured out why D8 may have loved the QB position so much. I figured out how to calculate QB efficiency and run it in the SDQL query. Look at the results in pic 1. ATS historical record hits at a 81% clip and look at that run of ATS wins since the middle of last month!! Wow!

QBefficiency1.jpg QBefficiency2.jpg
 
I used it quite a bit when I had time .

I ran one this afternonn looking for totals of MACtion on Tuesday
 
Akron:



team = AKRON and season = 2017 and ...

games ATS
W - L- P (marg, %win)
Avg Line OU
W - L- P (marg, %over)
Avg Total SU
W - L- P (marg, %win)
SDQL
0 0-0-0 (0.00, 0.0%) - 0-0-0 (0.00, 0.0%) - 0-0-0 (0.00, 0.0%) quarter scores = None
1 0-1-0 (-19.50, 0.0%) 32.5 0-1-0 (-11.00, 0.0%) 63.0 0-1-0 (-52.00, 0.0%) quarter scores = [0, 0, 0, 0]
1 0-0-1 (0.00, 0.0%) -49.0 0-1-0 (-2.00, 0.0%) 57.0 1-0-0 (49.00, 100.0%) quarter scores = [14, 17, 14, 7]
1 0-1-0 (-16.50, 0.0%) 10.5 0-1-0 (-8.00, 0.0%) 63.0 0-1-0 (-27.00, 0.0%) quarter scores = [0, 14, 0, 0]
1 1-0-0 (11.00, 100.0%) 16.0 0-1-0 (-15.50, 0.0%) 54.5 0-1-0 (-5.00, 0.0%) quarter scores = [3, 0, 7, 7]
1 1-0-0 (8.00, 100.0%) -3.0 0-1-0 (-0.50, 0.0%) 57.5 1-0-0 (11.00, 100.0%) quarter scores = [13, 7, 7, 7]
1 1-0-0 (20.00, 100.0%) -8.0 0-1-0 (-17.00, 0.0%) 51.0 1-0-0 (28.00, 100.0%) quarter scores = [7, 10, 0, 14]
1 1-0-0 (13.50, 100.0%) 12.5 0-1-0 (-27.50, 0.0%) 54.5 1-0-0 (1.00, 100.0%) quarter scores = [7, 7, 0, 0]
1 0-1-0 (-11.00, 0.0%) 16.0 1-0-0 (7.00, 100.0%) 62.0 0-1-0 (-27.00, 0.0%) quarter scores = [0, 7, 0, 14]
1 0-0-1 (0.00, 0.0%) -1.0 0-1-0 (-5.50, 0.0%) 46.5 1-0-0 (1.00, 100.0%) quarter scores = [7, 7, 0, 7]
Showing 1 to 10 of 10 entries

Avg just over 9 for 2nd half

MiaO:

team = MIAO and season = 2017 and ...

games ATS
W - L- P (marg, %win)
Avg Line OU
W - L- P (marg, %over)
Avg Total SU
W - L- P (marg, %win)
SDQL
0 0-0-0 (0.00, 0.0%) - 0-0-0 (0.00, 0.0%) - 0-0-0 (0.00, 0.0%) quarter scores = None
1 0-1-0 (-5.00, 0.0%) 0.0 1-0-0 (8.00, 100.0%) 49.0 0-1-0 (-5.00, 0.0%) quarter scores = [3, 10, 7, 6]
1 0-1-0 (-14.50, 0.0%) -35.5 0-1-0 (-17.00, 0.0%) 58.0 1-0-0 (21.00, 100.0%) quarter scores = [7, 14, 0, 10]
1 0-1-0 (-8.00, 0.0%) -4.0 0-1-0 (-10.00, 0.0%) 48.0 0-1-0 (-4.00, 0.0%) quarter scores = [7, 0, 7, 3]
1 1-0-0 (15.00, 100.0%) -2.0 0-1-0 (-7.00, 0.0%) 52.0 1-0-0 (17.00, 100.0%) quarter scores = [14, 14, 3, 0]
1 0-1-0 (-13.50, 0.0%) 21.5 1-0-0 (15.50, 100.0%) 53.5 0-1-0 (-35.00, 0.0%) quarter scores = [7, 7, 3, 0]
1 0-1-0 (-23.50, 0.0%) -15.5 1-0-0 (16.00, 100.0%) 50.0 0-1-0 (-8.00, 0.0%) quarter scores = [6, 13, 10, 0]
1 0-1-0 (-11.50, 0.0%) -8.5 0-1-0 (-10.50, 0.0%) 41.5 0-1-0 (-3.00, 0.0%) quarter scores = [0, 14, 0, 0]
1 1-0-0 (7.00, 100.0%) -3.0 0-1-0 (-8.00, 0.0%) 46.0 1-0-0 (10.00, 100.0%) quarter scores = [10, 0, 14, 0]
1 0-1-0 (-7.50, 0.0%) 9.5 1-0-0 (18.00, 100.0%) 55.0 0-1-0 (-17.00, 0.0%) quarter scores = [14, 7, 7, 0]
Showing 1 to 10 of 10 entries

Avg O7 for 2nd half.

LIne= MIAO -4.5 and 24.5...

I took U24.5

GL

Press
 
Here's a nice one! Scenario: Home Dogs that have a 1) better QB efficiency, 2) better total defense, and 3) lower turnover margin than their opponent have gone 7-1 ATS this year and 5-3 straight up. It is active on Miami this Saturday. I don't think I'll be laying points with Notre Dame this weekend.

QB-totdef-tomargin1.jpg
QB-totdef-tomargin2.jpg
 
Road dogs, with similar scenario as Miami above, have not fared as well going 8-8-1 this year ATS. Active on Purdue this Saturday.

QB-totdef-tomargin3.jpg
QB-totdef-tomargin4.jpg
 
Dogs, at neutral sites, with total defense allowing between 400-500ypg and opponents allowing between 375-450ypg are 6-1-1 ATS in it's last 8 occurences. This trend is active on Baylor this Saturday. Interesting to note my Cats were the lone ATS loss and I can tell you they were just happy to be playing in that Gator Bowl last year. These are all bowl games from last year so I don't know how much of a difference that makes fyi.....with the exception of the Tex/Okla game in AT&T Stadium last October.

neutral1.jpg
neutral2.jpg
 
It's pretty interesting. Not sure I would go into it ,but certainly like hearing what you come up with. I don't think it would determine who I play but would perhaps aid in confidence on or against perhaps. So is this a website or a program you download?
 
It's pretty interesting. Not sure I would go into it ,but certainly like hearing what you come up with. I don't think it would determine who I play but would perhaps aid in confidence on or against perhaps. So is this a website or a program you download?
killersports.com hosts the ability to run the queries....users just need to learn some of their pseudocode to run their own queries. I've often thought about keeping my own databse but I would never have that much time to work on anything like this..it's massive and all at one's fingertips.

To give you and idea, I spent about 4 hours last week going thru each game and researching them trying to find D8 style 1st half plays. Now that I developed my own code...it's will take me seconds to copy and paste it into their database and get results whenever I want.
 
If you’re good with Access, it will allow you to import data. You could set your parameters, and it will spit out excel for your queries. It will also remove some the excess for a more user friendly reading.
 
Akron:



team = AKRON and season = 2017 and ...

games ATS
W - L- P (marg, %win)
Avg Line OU
W - L- P (marg, %over)
Avg Total SU
W - L- P (marg, %win)
SDQL
0 0-0-0 (0.00, 0.0%) - 0-0-0 (0.00, 0.0%) - 0-0-0 (0.00, 0.0%) quarter scores = None
1 0-1-0 (-19.50, 0.0%) 32.5 0-1-0 (-11.00, 0.0%) 63.0 0-1-0 (-52.00, 0.0%) quarter scores = [0, 0, 0, 0]
1 0-0-1 (0.00, 0.0%) -49.0 0-1-0 (-2.00, 0.0%) 57.0 1-0-0 (49.00, 100.0%) quarter scores = [14, 17, 14, 7]
1 0-1-0 (-16.50, 0.0%) 10.5 0-1-0 (-8.00, 0.0%) 63.0 0-1-0 (-27.00, 0.0%) quarter scores = [0, 14, 0, 0]
1 1-0-0 (11.00, 100.0%) 16.0 0-1-0 (-15.50, 0.0%) 54.5 0-1-0 (-5.00, 0.0%) quarter scores = [3, 0, 7, 7]
1 1-0-0 (8.00, 100.0%) -3.0 0-1-0 (-0.50, 0.0%) 57.5 1-0-0 (11.00, 100.0%) quarter scores = [13, 7, 7, 7]
1 1-0-0 (20.00, 100.0%) -8.0 0-1-0 (-17.00, 0.0%) 51.0 1-0-0 (28.00, 100.0%) quarter scores = [7, 10, 0, 14]
1 1-0-0 (13.50, 100.0%) 12.5 0-1-0 (-27.50, 0.0%) 54.5 1-0-0 (1.00, 100.0%) quarter scores = [7, 7, 0, 0]
1 0-1-0 (-11.00, 0.0%) 16.0 1-0-0 (7.00, 100.0%) 62.0 0-1-0 (-27.00, 0.0%) quarter scores = [0, 7, 0, 14]
1 0-0-1 (0.00, 0.0%) -1.0 0-1-0 (-5.50, 0.0%) 46.5 1-0-0 (1.00, 100.0%) quarter scores = [7, 7, 0, 7]
Showing 1 to 10 of 10 entries

Avg just over 9 for 2nd half

MiaO:

team = MIAO and season = 2017 and ...

games ATS
W - L- P (marg, %win)
Avg Line OU
W - L- P (marg, %over)
Avg Total SU
W - L- P (marg, %win)
SDQL
0 0-0-0 (0.00, 0.0%) - 0-0-0 (0.00, 0.0%) - 0-0-0 (0.00, 0.0%) quarter scores = None
1 0-1-0 (-5.00, 0.0%) 0.0 1-0-0 (8.00, 100.0%) 49.0 0-1-0 (-5.00, 0.0%) quarter scores = [3, 10, 7, 6]
1 0-1-0 (-14.50, 0.0%) -35.5 0-1-0 (-17.00, 0.0%) 58.0 1-0-0 (21.00, 100.0%) quarter scores = [7, 14, 0, 10]
1 0-1-0 (-8.00, 0.0%) -4.0 0-1-0 (-10.00, 0.0%) 48.0 0-1-0 (-4.00, 0.0%) quarter scores = [7, 0, 7, 3]
1 1-0-0 (15.00, 100.0%) -2.0 0-1-0 (-7.00, 0.0%) 52.0 1-0-0 (17.00, 100.0%) quarter scores = [14, 14, 3, 0]
1 0-1-0 (-13.50, 0.0%) 21.5 1-0-0 (15.50, 100.0%) 53.5 0-1-0 (-35.00, 0.0%) quarter scores = [7, 7, 3, 0]
1 0-1-0 (-23.50, 0.0%) -15.5 1-0-0 (16.00, 100.0%) 50.0 0-1-0 (-8.00, 0.0%) quarter scores = [6, 13, 10, 0]
1 0-1-0 (-11.50, 0.0%) -8.5 0-1-0 (-10.50, 0.0%) 41.5 0-1-0 (-3.00, 0.0%) quarter scores = [0, 14, 0, 0]
1 1-0-0 (7.00, 100.0%) -3.0 0-1-0 (-8.00, 0.0%) 46.0 1-0-0 (10.00, 100.0%) quarter scores = [10, 0, 14, 0]
1 0-1-0 (-7.50, 0.0%) 9.5 1-0-0 (18.00, 100.0%) 55.0 0-1-0 (-17.00, 0.0%) quarter scores = [14, 7, 7, 0]
Showing 1 to 10 of 10 entries

Avg O7 for 2nd half.

LIne= MIAO -4.5 and 24.5...

I took U24.5

GL

Press
And it hits!! Nice one Press! :shake:
 
A couple fun little angles with tiny samples and huge deviations from the line:

Play on home conference favorite off a shutout loss as a home favorite >>> Play on Air Force

HCF and p:HFL and points = 0 >>> Play on Air Force

ATS: 3-0-0 (18.67, 100.0%) avg line: -13.3 +6: 3-0-0 (100.0%) -6: 2-1-0 (66.7%)
----
After week 5, play against an undefeated road favorite visiting a winning team (win % greater than 60%) thatis home off three straight road games >>>> Play on Auburn

week > 5 and o:WP = 100 and WP > 60 and HD and p:A and pp:A and ppp:A and P:L >>>> Play on Auburn

ATS: 4-0-0 (19.38, 100.0%) avg line: 8.4 +6: 4-0-0 (100.0%) -6: 4-0-0 (100.0%)
---

If SMU plays Navy, bet against SMU. LOL.

team = SMU and o:team = NAVY and season > 1994 >>> Play on Navy

ATS: 2-9-0 (-17.82, 18.2%) avg line: 1.3 +6: 4-7-0 (36.4%) -6: 1-10-0 (9.1%)
---
 
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I edited to explain each situation. The numbers after "ATS" are the ATS record of the situation, and the numbers in parens are first the average amount by which the angle covered (or failed to cover) and second the winning % of the angle. The +6 and -6 show the results if you moved the number 6 points one way or the other (for covering teasers or pleasers).

I'm not recommending that you bet Air Force or Auburn. I wasn't data-mining; I just saw unusual situations and was curious to see whether they pointed in one direction or the other. Frankly, I expected a lot more results for each of these, but the limited results showed the home team covering by an amazing 19 points per game.

I already knew SMU consistently gets killed by Navy; I was just curious about how bad the actual number was.
 
Thanks for posting, JRock. I'm always interested in statistical analysis, but I'm leery of it until I know there have been no changes--such as different coaching staffs, or new coordinators, QB injured, etc--during the time frame in which the stats were compiled. I'm not sure what the theory you are posting is, so I look forward to seeing you post teams the system produces and then seeing how they do.

You mentioned Purdue and that game with N Western is one of the interesting ones this week. I like to bet against teams that played a taxing, down to the final gun game the previous week, and going against one that played an overtime is even better. Every set of stats I have ever seen says you have a 56-58% chance of winning if you bet against a team that plays a hard game that goes to overtime, and especially multiple overtimes, the prior week. N Western blows that out of the water though because they have just done something no team has ever done in the history of college football--they have played 3 straight overtime games and won them all SU and I believe won all three ATS (not sure why, but teams that lose overtime games do slightly better than winners the following week).

Still, three OT's in a row makes me lean to going against N Western, but Purdue has lost their QB. I don't know for sure, but I doubt if a new first year coach at an historically bad program has been able to build up depth at QB.

So I'm passing on that game this week, but I'll be watching to see if NW shows any fatigue from the last three games.
 
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A couple fun little angles with tiny samples and huge deviations from the line:

Play on home conference favorite off a shutout loss as a home favorite >>> Play on Air Force

HCF and p:HFL and points = 0 >>> Play on Air Force

ATS: 3-0-0 (18.67, 100.0%) avg line: -13.3 +6: 3-0-0 (100.0%) -6: 2-1-0 (66.7%)
----
After week 5, play against an undefeated road favorite visiting a winning team (win % greater than 60%) thatis home off three straight road games >>>> Play on Auburn

week > 5 and o:WP = 100 and WP > 60 and HD and p:A and pp:A and ppp:A and P:L >>>> Play on Auburn

ATS: 4-0-0 (19.38, 100.0%) avg line: 8.4 +6: 4-0-0 (100.0%) -6: 4-0-0 (100.0%)
---

If SMU plays Navy, bet against SMU. LOL.

team = SMU and o:team = NAVY and season > 1994 >>> Play on Navy

ATS: 2-9-0 (-17.82, 18.2%) avg line: 1.3 +6: 4-7-0 (36.4%) -6: 1-10-0 (9.1%)
---
Love it M.W....I'm still learning and was wondering how to code in the conference angle and you nailed it for me....Thanks!!
 
Thanks for posting, JRock. I'm always interested in statistical analysis, but I'm leery of it until I know there have been no changes--such as different coaching staffs, or new coordinators, QB injured, etc--during the time frame in which the stats were compiled. I'm not sure what the theory you are posting is, so I look forward to seeing you post teams the system produces and then seeing how they do.

You mentioned Purdue and that game with N Western is one of the interesting ones this week. I like to bet against teams that played a taxing, down to the final gun game the previous week, and going against one that played an overtime is even better. Every set of stats I have ever seen says you have a 56-58% chance of winning if you bet against a team that plays a hard game that goes to overtime, and especially multiple overtimes, the prior week. N Western blows that out of the water though because they have just done something no team has ever done in the history of college football--they have played 3 straight overtime games and won them all SU and I believe won all three ATS (not sure why, but teams that lose overtime games do slightly better than winners the following week).

Still, three OT's in a row makes me lean to going against N Western, but Purdue has lost their QB. I don't know for sure, but I doubt if a new first year coach at an historically bad program has been able to build up depth at QB.

So I'm passing on that game this week, but I'll be watching to see if NW shows any fatigue from the last three games.
8 of those occurrences, in that 8-8-1 ATS record, were wins Tahoe....you might be in the right side with Purdue!
 
I was interested in Michigan State ML, even though I knew OSU was coming home off a loss, because it seemed like their defense got ripped the past two games. So I tried to figure out a scenario that quantified the chances of a Buckeye bounce-back. I ran a query where the home favorites of >10 had lost their last game, given up >54pts in their last game, and given up >37pts two games ago. Turns out, the bounce-back threat looks absolutely for real with a 22-3 SU record and 13-11-1 ATS historical records. And it is active on Ohio State Saturday.

ohiost1.jpg
ohiost2.jpg
 
I watched the end of the Arkansas/CC game last Saturday and it looked like Coastal players were absolutely crushed losing that game. So I tried to quantify what that letdown might mean for this week's matchup vs. Troy. I ran a query of home dogs, with a line of >15pts, that lost their last game and gave up >38pts and also gave up >26pts two games ago. The SU historical record is 22-333 and the 2017 ATS record is 1-9-1. The 2017 SU record is 0-10. The struggle is real y'all!

ccu1.jpg
ccu2.jpg
 
This one was unexpected....I was dabbling around with the above line and tried the same thing from post #22 but changed the line to 1-10pt dogs. Turns out it has a 10-6-1 ATS record in 2017 so far and 8-9 SU record. Considering some of the trends I've read, a 8-9 SU record does not seem that bad if you're looking for a dog to win straight up! It is active on Florida this Saturday.

florida1.jpg
florida2.jpg
 
Trying to cap the Wash/Stan game. Ran a query similar to the ones above...road fav that won the last two games, last game by >20pts and two games ago by >20pts. Upon first look, the trend is heavily in the fav's favor. Then I took a look at the games that lost this year and I remember each of them had a serious situation going on for the home dog. MSU hates LSU and had revenge on their mind, Vandy was fired up for their game vs. K. St., NC St. was horribly humiliated last year @ Louisville, and LSU was trying to re-establish themselves, after that 1pt win at Florida, when they beat Auburn. It just so happens Stanford might have some revenge on their minds as they lost 44-6 last year at Wash. Not sure about Col. State. The trend is active on Boise St. & Washington Saturday, however.

wash1.jpg
wash2.jpg
 
Thanks

it happens. I like trends and historical data. Used their database a long time.
Not great with it. I use simple strings.
The half scores in baskets and qtr scores in foots worked pretty good over the years.
First time I had time to try it on the NFL this year went 0-6, so you still have to keep up with the games/players etc..
 
Thanks

it happens. I like trends and historical data. Used their database a long time.
Not great with it. I use simple strings.
The half scores in baskets and qtr scores in foots worked pretty good over the years.
First time I had time to try it on the NFL this year went 0-6, so you still have to keep up with the games/players etc..
What about running a query of how a team fares at the beginning of a season That also had lost a lot of production from the previous season? I’m thinking of doing that for basketball with my Cats. They are starting over completely again this year.
 
What's the chance of an Appy State bounce-back tonight? Possibly very good.....Home favs that have lost their last two games by greater than 51pts and greater than 29pts are historically 21-1 SU and 15-7 ATS. You have to go all the way back to 1984 to find the last upset in this scenario.

appy1.jpg
appy2.jpg
 
Concerning N. Illinois -28.5....Home Favs that lost their last game and gave up > 26pts but won 2 games ago and gave up > 26pts are historically 30-1 SU and 17-11-3 ATS. Pretty solid numbers until you take a closer look. HF's were 10-0-1 ATS in the first 11 occurrences, 7-11-2 thereafter and have lost the last 4 in a row ATS. My recommendation is, if you feel so inclined to take the points in this matchup, then do so. Good luck in what you decide!

BALL1.jpg
BALL2.jpg
 
Concerning N. Illinois -28.5....Home Favs that lost their last game and gave up > 26pts but won 2 games ago and gave up > 26pts are historically 30-1 SU and 17-11-3 ATS. Pretty solid numbers until you take a closer look. HF's were 10-0-1 ATS in the first 11 occurrences, 7-11-2 thereafter and have lost the last 4 in a row ATS. My recommendation is, if you feel so inclined to take the points in this matchup, then do so. Good luck in what you decide!

View attachment 30050
View attachment 30051
In addition, away dogs (Ball St. in this case) that have lost their last three games by greater than 55, 57, & 55pts are a historical 3-0 ATS.

ball3.jpg
 
Concerning NC / Pitt game....ran the sims for Pitt and got a mixed bag, not very conclusive. However, ran the sims for UNC and found that away dogs that have lost their last 3 games and gave up >23, 57, and 19pts respectively, are 6-12 ATS. I would have leaned Pitt here with the points but then I saw the last six occurrences have gone W-L-W-L-W-L....it's due for a W so I think I'll just pass.

unc.jpg
 
Just to update....my SDQL leans so far this week have been on:

Ohio (Won SU & ATS)
Army ATS & SU
Purdue (lean on them due to info Tahoe provided)
Baylor ATS
Florida ATS & SU
Stanford (SDQL trend in favor of Wash but situation says Stanford) ATS & SU
Appy State -18
Ball State +31
UNC or Pitt - Pass

:eatingburger:
 
Adding: Charlotte +12.5.
Home dogs (in this case Charlotte) with lines between 10 & 15 and have a loss, win, and loss in their last 3 games and gave up greater than 5, 23, and 44pts respectively, and have a QB efficiency < than the opponent, have gone 0-6 SU but 3-3 ATS....not so great but when you add in my similar sim below on MTSU as a Road Fav, their ATS record is a historical 0-3 ATS. Look for MTSU to win the game but not cover.


CHAR1.jpg
CHAR2.jpg
 
I prefer the sportsdatabase website over killer sports though. Just feels like it runs cleaner.
Awesome austinhous! Have you done any basketball? I'm curious to know how to find out records for teams in the month of november that lose a lot of production from previous years (Kentucky for example.) Any idea how I would design a query like that?
 
maybe you have some scenarios you would like to suggest we look up?

This is always a challenge. I like to keep my shit as non-arbitrary as possible. If I can't explain the angle in plain English I back away. I never understood these queries where it's some random compilation of unrelated things and it spits out like a 28-0 ATS record since 1999 or something like that. I like stuff like "Titans with a Thursday look ahead" or "Opposing teams versus Marvin Lewis with a Thursday look ahead."
 
Some momentum for a Western Ky upset this weekend, perhaps? Away dog query active on Western.....

wky1.jpg
 
Awesome austinhous! Have you done any basketball? I'm curious to know how to find out records for teams in the month of november that lose a lot of production from previous years (Kentucky for example.) Any idea how I would design a query like that?

I am not sure off the top of my head, but I see where you're going. I do know that the NCAA basketball database is pretty sketchy at the moment, just with all the data and it still being under construction. I think there's even a disclaimer they use warning you of its sketchiness.
 
This is always a challenge. I like to keep my shit as non-arbitrary as possible. If I can't explain the angle in plain English I back away. I never understood these queries where it's some random compilation of unrelated things and it spits out like a 28-0 ATS record since 1999 or something like that. I like stuff like "Titans with a Thursday look ahead" or "Opposing teams versus Marvin Lewis with a Thursday look ahead."
What I would love to do is design a query using Ken Pomeroy's Four Factors theory...I looked at his formula and the stats offered on Killersports and think I can do it. I'm pretty proud of myself for figuring out the QB efficiency in this thread....don't know how good or bad that is so try not burst my bubble LOL!!
 
You guys have any links explaining the language? Like what the code is for certain things? I assume p:L is previous game loss and pp:L is two games ago loss, etc
 
Got one in early this am....tried to quantify a possible letdown this week for Iowa as they had that humongous win last week and it does not look good for the Hawkeyes....SU 9-1 record for a home fav and 60% ATS active on Wisconsin Saturday....Iowa has their work cut out for them IMHO. Good luck on what you decide!

wisky.jpg
 
Where I had a need was to port it to a spreadsheet .
And that could be as simple as my query being copied/pasted by "hand". It just doesn't give that up easily.
When I would play half/quarters , I would move the totals for each into a spreadsheet, run a macro to give me a mean and assign a margin for a play or no play(pre determined from historical data).
Once all teams are entered and the games were caught up to the present , I would only need the latest game to enter.
Very difficult to do in CBB, because of the amount games played each day.

I did ok when I could stay on top of it, but it was a beating.
Portability across formats would help.
 
Where I had a need was to port it to a spreadsheet .
And that could be as simple as my query being copied/pasted by "hand". It just doesn't give that up easily.
When I would play half/quarters , I would move the totals for each into a spreadsheet, run a macro to give me a mean and assign a margin for a play or no play(pre determined from historical data).
Once all teams are entered and the games were caught up to the present , I would only need the latest game to enter.
Very difficult to do in CBB, because of the amount games played each day.

I did ok when I could stay on top of it, but it was a beating.
Portability across formats would help.
Yeah that sounds like it would take a toll. I️ was dabbling yesterday with my formula for effective FG% which is one of the 4 factors KP emphasizes. I️ used to go thru each game and enter them into a spreadsheet to compare each teams stats and, like you, took a beating. I’m optimistic I️ can set up a query and find the four factors daily...esp if I️ can automate it!
 
You guys have any links explaining the language?

I taught myself using the MLB query manual. MLB was a great way to start using it simply because of the sheer number of games per season, and the way that simple stuff like "days of the week" apply to baseball - a sport that I think is really fine tuned. Baseball is such a well-oiled machine so when you find situations or trends it's easier to be confident about them. http://killersports.com/Download/MLB/query_manual.pdf

NFL: http://killersports.com/Download/NFL/query_manual.pdf
 
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