Archive
2012/2013 Bowl Games – Every Meaningful and Meaningless Handicapping Stat You Ever Wanted To Know
The 2012/2013 Bowl Season is upon us and we have put together a bunch of Handicapping Stats has they relate to all the individual Bowl Games as well as the past performance of all teams playing.
Below you will find the following 4 spreadsheets:
1. Bowl_Games – ML/ATS/Total and Projected Results for last 5 years of Bowl Games
2. Team_Detail – ML/ATS/Total and Projected Results for last 5 years By Team as Favorites/Underdogs
3. Line_Total – ATS Result by Line and Total Result by Total for last 5 years of Bowl data
4. Conf_Vs_Conf – ML/ATS/Total and Projected Results By Conference vs Conference for last 5 years of Bowl data
Please note for all data where Bowl names have changed the data has been aggregated to the current Bowl name, and that Conference realignment may make some data appear inaccurate.
Bowl_Games – ML/ATS/Total and Projected Results for last 5 years of Bowl Games
Tab 1 – Alpha By Bowl Game Name
Tab 2 – By Straight Up Favorite Win %
Tab 3 – By GreyMatterStats Straight Up Projected Win %
Tab 4 – By ATS Favorite Win %
Tab 5 – By GreyMatterStats ATS Projected Win %
Tab 6 – By Total Over Win %
Tab 7 – By GreyMatterStats Total Projected Win %
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2012 Army vs Navy Game Preview
The annual Army vs Navy game concludes the 2012/2013 College Football Regular Season this Saturday.
We have attended a few Army/Navy games, and they are just a tremendous experience. If you ever get the opportunity, do yourself a favor and go.
As much as we enjoy Army/Navy, the game always makes us a bit sad since it is a stark reminder that all we have left in College Football is a bunch of crappy Bowl Games, a few good Bowl games, and the National Championship. Of course we are looking forward to Bama/Notre Dame, but it always takes us several weeks to get over our Tuesday/Wednesday Night MAC Conference GOW withdraw.
So in hopes of closing out the 2012/2013 College Football Regular Season with a winner, we offer a review of the current Army/Navy game along with some history of the the last five match ups.
The game will be played at Lincoln Financial Field in Philadelphia, PA the home of the Eagles(and those Temple Owls).
Straight up, Navy leads the overall series with a record of 56-49-7 , and have won the last ten in a row.
While Navy has steadily improved throughout the season, Army has been up and down, at times being in games and at times getting their doors blown off.
Both these teams have solid rushing games with Army leading College Football with 369.8 yards/game while Navy is 6th in the country at 285.5 yards/game. Couple these running attacks with the fact that both Army and Navy have ranked 108 or higher all season in run defense and it should be a reasonable expectation that both teams will run the ball at will and chew clock. Additionally, both teams have struggled to say the least with any kind of passing game, with Army ranked dead last and Navy not too far from them.
For the current season Air Force was their only common opponent, and both teams won their games outright as Dogs. On 10/06/2012 Navy beat Air Force 28-21 as a 8.5 point Road Dog, and on 11/03/2012 Army beat Air Force 41-21 as a 7 point Home Dog.
Our internal Strength of Schedule Calculation moderately favors Navy for the Current Season.
Season to date, the Midshipmen are 6-4 straight up, and 3-7 ATS, and 3 Overs and 7 Unders in the Totals.
Season to date, Army is 2-8 straight up, 3-7 ATS, and 6 Overs and 4 Unders in the Totals.
Currently Navy is a 7 point Favorite and the Total is 56.5.
You can find our full Game Breakdown with Projection, here.
Below is a breakdown of the last five Army vs Navy games, including ML, ATS, and Total, and Projected Results.
NFL – An Historic Analysis Of Q3 ML/ATS/Total Performance By Team
We posted data through Q2 about a month ago, and thought it was worth continuing into Q3.
You can find the original post here.
To recap, we have tracked how teams have done comparatively across different time frames with in a season.
The time-frames are defined as follows for NFL:
- Weeks 01-04 are Q1
- Weeks 05-08 are Q2
- Weeks 09-12 are Q3
- Weeks 13-17 are Q4
The analysis of the NFL Q3 history indicates there are several teams whose ML/ATS/Total performances have been measurably different as compared to other time frames.
For example, the Saints have historically been a very strong Q3 team ATS covering 64.7%, 17.3% over their historic Q2 performance and 12.3% over their historic baseline performance.
We say this all the time, but we want to be absolutely clear that any of these trends in a vacuum are no reason in and of itself to play a side or total. This data should be used as just one more piece of information in your handicapping.
Some of this we said in our original post but it bears repeating:
- There has been a noteworthy consistency to this data for several teams, and we believe it is worth your while to familiarize yourself with the information.
- There are a lot of arguments that can be made as to why these trends occur for some teams from quarter to quarter over time. Coaching philosophies, scheduling, QB’s that start slow, and odds-makers’ adjustments all play apart in the fluctuations we see between time-frames for some of the teams.
- When using this reference it is important that you keep in mind situations such as coaching or impact roster changes that would render historic data much less useful. Obviously for teams that have enjoyed coaching and player continuity, the data should tend to hold more true.
- The baseline represents all results for a given team across all time-frames.
In the embedded Excel workbook below, you will find the following worksheets for both the NFL and NCAAF:
- ML_HISTORY_Q1-Q4 – ML WIN % BY TEAM
- ATS_HISTORY_Q1-Q4 – ATS WIN % BY TEAM
- TOTAL_HISTORY_Q1-Q4 – TOTAL OVER WIN % BY TEAM
- SUMMARY_HISTORY_Q1-Q3 – ML/ATS/TOTAL COUNTS BY FAV/OVER FOR Q1, Q2, Q3, AND A BASELINE PERIODS
Please note the following regarding the data:
- THE DATA REPRESENTS A 5 YEAR HISTORY AND IS GROUPED BY QUARTER
- ML AND ATS PERCENTS ARE IN TERMS OR WIN %
- TOTAL PERCENTS ARE IN TERMS OF PERCENT OF GAMES THAT WENT OVER
- THE BASELINE PERIOD REPRESENTS ALL DATA FOR ALL TIME-FRAMES BY TEAM
- For Q3 any Historic percentages >= 60% are highlighted in green
- For Q3, any Historic – Baseline differences of >= 10% are highlighted in green and any <=-10% in red
- For Q3 as compared to Q2, any differences of >= 20% are highlighted in green and <=20% in red
- Under the column “Best Quarter” is Q3 it is highlighted in green, and if “Worst Quarter” highlighted in red
- ALL PUSHES HAVE BEEN OMITTED
NFL DATA
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We hope you find the information an asset to your handicapping and please visit our free site, GreyMatterStats, where we put this information at your fingertips.
If you find something of interest that you would like to share, please feel free to leave a comment or Tweet us @GreyMatterStats
College Football – An Historic Analysis Of Q3 ML/ATS/Total Performance By Team
We posted data through Q2 about a month ago, and thought it was worth continuing into Q3.
You can find the original post here.
To recap, we have tracked how teams have done comparatively across different time frames with in a season.
The time-frames are defined as follows for NCAAF:
- Weeks 01-04 are Q1
- Weeks 05-08 are Q2
- Weeks 09-12 are Q3
- Weeks 13-Through the Bowl Games are Q4
The analysis of the Q3 history in College Football indicates there are several teams whose ML/ATS/Total performances have been measurably different as compared to other time frames.
For example, Ole Miss has historically been a very strong Q2 team ATS covering 66.7%, but for Q3 their ATS cover rate drops dramatically to just 37.5%. The current Rebel team has held true to this trend and are undefeated Q2 season-to-date Q2 ATS. We will be using this information to look to make a case to fade Ole Miss ATS as part of our overall handicapping process.
We say this all the time, but we want to be absolutely clear that any of these trends in a vacuum are no reason in and of itself to play a side or total. This data should be used as just one more piece of information in your handicapping.
Some of this we said in our original post but it bears repeating:
- There has been a noteworthy consistency to this data for several teams, and we believe it is worth your while to familiarize yourself with the information.
- There are a lot of arguments that can be made as to why these trends occur for some teams from quarter to quarter over time. Coaching philosophies, scheduling, QB’s that start slow, and odds-makers’ adjustments all play apart in the fluctuations we see between time-frames for some of the teams.
- When using this reference it is important that you keep in mind situations such as coaching or impact roster changes that would render historic data much less useful. Obviously for teams that have enjoyed coaching and player continuity, the data should tend to hold more true.
- The baseline represents all results for a given team across all time-frames.
In the embedded Excel workbook below, you will find the following worksheets for both the NFL and NCAAF:
- ML_HISTORY_Q1-Q4 – ML WIN % BY TEAM
- ATS_HISTORY_Q1-Q4 – ATS WIN % BY TEAM
- TOTAL_HISTORY_Q1-Q4 – TOTAL OVER WIN % BY TEAM
- SUMMARY_HISTORY_Q1-Q3 – ML/ATS/TOTAL COUNTS BY FAV/OVER FOR Q1, Q2, Q3, AND A BASELINE PERIODS
Please note the following regarding the data:
- THE DATA REPRESENTS A 5 YEAR HISTORY AND IS GROUPED BY QUARTER
- ML AND ATS PERCENTS ARE IN TERMS OR WIN %
- TOTAL PERCENTS ARE IN TERMS OF PERCENT OF GAMES THAT WENT OVER
- THE BASELINE PERIOD REPRESENTS ALL DATA FOR ALL TIME-FRAMES BY TEAM
- For Q3 any Historic percentages >= 60% are highlighted in green
- For Q3, any Historic – Baseline differences of >= 10% are highlighted in green and any <=-10% in red
- For Q3 as compared to Q2, any differences of >= 20% are highlighted in green and <=20% in red
- Under the column “Best Quarter” is Q3 it is highlighted in green, and if “Worst Quarter” highlighted in red
- ALL PUSHES HAVE BEEN OMITTED
COLLEGE FOOTBALL DATA
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We hope you find the information an asset to your handicapping and please visit our free site, GreyMatterStats, where we put this information at your fingertips.
If you find something of interest that you would like to share, please feel free to leave a comment or Tweet us @GreyMatterStats
Football Is At The Quarter Mile Post And History Suggests That Some Teams Perform Measurably Different In The Next Leg Of Their Seasons
If you’re like us, whenever football is not being played you can’t wait for it to start, then once it does the weeks just fly by.
It’s hard to believe that we are already one quarter of the way into the NFL season, and one quarter plus into the College Football season.
One of the things we have tracked for some time but never reported on, is an analysis of how teams have done comparatively across different time frames with in a season.
For football, we have found that by taking the regular season and grouping it into quarters we have gotten that best results overtime when it comes to this type of comparative analysis.
The time-frames are defined as follows:
- For both the NFL and NCAAF – Weeks 01-04 are Q1
- For both the NFL and NCAAF – Weeks 05-08 are Q2
- For both the NFL and NCAAF – Weeks 09-12 are Q3
- Q4 for the is NFL Weeks 13-17, and for NCAAF Weeks 13-Through the Bowl Games
Everyone reading this is probably well aware that at the end of any football season, there is a fairly even distribution of Favorites and Dogs that cover ATS. But you will never see an even distribution of Favorites and Dogs from week to week. A few weeks might be top heavy with Favorites followed by a run of Dogs, that at the end of the season results in relative ATS parity.
The same basic philosophy can be applied when analyzing result data at the individual team level across various time-frames.
For example, the Florida Gators historically have been overall a very strong 60.6% ATS in the past 5 years. But when we review how the Gators have done across our time-frames we see an interesting and consistent trend. For Q1 the Gators have been an off the charts 76.2% ATS, but for Q2 their ATS win rate drops to only 33.3%. Currently the Gators are 3-1, or 75.0%, ATS and host LSU as a 2.5 point Dog in this Q2 matchup.
In another example, the Minnesota Vikings have gone Over the Total 52.4% of the time for the past five years of history. But for Q1 only across that five year history the Vikings Total has gone Over only 39.1% of the time, while for Q2 they have been Over 72.2% of the time. This week Minny, who is 1 Over/3 Under on the year, hosts the Titans with the Total currently at 44.
We want to be absolutely clear, that any of these trends in a vacuum are no reason in and of itself to play a side or total. This data should be used as just one more piece of information in your handicapping.
That said, there has been a noteworthy consistency to this data for several teams, and we believe it is very much worth your while to familiarize yourself with the information.
There are a lot of arguments that can be made as to why these trends occur for some teams from quarter to quarter over time. Coaching philosophies, scheduling, QB’s that start slow, and odds-makers’ adjustments all play apart in the fluctuations we see between time-frames for some of the teams.
When using this reference it is important that you keep in mind situations such as coaching or impact roster changes that would render historic data much less useful. Obviously for teams that have enjoyed coaching and player continuity, the data should tend to hold more true.
The screenshots and spreadsheet show historic Q1/Q2 and baseline data for the NFL and College Football. The baseline represents all results for a given team across all time-frames. We will revisit this post at the end of Q2 and see how the data fared versus the actual results, as well as add data for Q3.
In the embedded Excel workbook below, you will find the following worksheets for both the NFL and NCAAF:
- ML_HISTORY_Q1-Q2 – ML WIN % BY TEAM FOR BASELINE/Q2/Q1 – SORTED BY ALPHA AND BY Q2 WIN % AND BY Q2 DIFFERENCE FROM BASELINE AND BY Q2 DIFFERENCE FROM Q1
- ATS_HISTORY_Q1-Q2 – ATS WIN % BY TEAM FOR BASELINE/Q2/Q1 – SORTED BY ALPHA AND BY Q2 WIN % AND BY Q2 DIFFERENCE FROM BASELINE AND BY Q2 DIFFERENCE FROM Q1
- TOTAL_HISTORY_Q1-Q2 – TOTAL OVER WIN % BY TEAM FOR BASELINE/Q2/Q1 – SORTED BY ALPHA AND BY Q2 WIN % AND BY Q2 DIFFERENCE FROM BASELINE AND BY Q2 DIFFERENCE FROM Q1
- SUMMARY_HISTORY_Q1-Q2 – ML/ATS/TOTAL COUNTS BY FAV/OVER FOR Q1, Q2, AND A BASELINE PERIODA
Please note the following regarding the data:
- THE DATA REPRESENTS A 5 YEAR HISTORY AND IS GROUPED BY QUARTER
- ML AND ATS PERCENTS ARE IN TERMS OR WIN %
- TOTAL PERCENTS ARE IN TERMS OF PERCENT OF GAMES THAT WENT OVER
- THE BASELINE PERIOD REPRESENTS ALL DATA FOR ALL TIME-FRAMES BY TEAM
- ALL PUSHES HAVE BEEN OMITTED
NFL DATA
COLLEGE FOOTBALL DATA
We hope you find the information an asset to your handicapping and please visit our free site, GreyMatterStats, where we put this information at your fingertips.
If you find something of interest that you would like to share, please feel free to leave a comment or Tweet us @GreyMatterStats
NCAAF – HANDICAPPING STATS – WEEK 02 REVIEW – WEEK 03 PREVIEW
The information presented here is inclusive of all games played through Week 02 of the College Football Season, as well as historic data through Week 03 that provides a snapshot of what is happening by week for the current and prior seasons across many variables.
In the embedded Excel workbook below, you will find the following worksheets:
- BY_GAME_TYPE_STD – ML/ATS/TOTAL RESULTS BY CONFERENCE/NON-CONFERENCE GAMES BY WEEK
- BY_AWAY_HOME_STD – ML/ATS/TOTAL RESULTS BY AWAY/HOME BY WEEK
- ML_BY_WEEK – GRAPH OF MONEY LINE FAVORITE WIN% BY WEEK FOR CURRENT SEASON AND HISTORY
- ATS_BY_WEEK – GRAPH OF ATS FAVORITE WIN% BY WEEK FOR CURRENT SEASON AND HISTORY
- TOTAL_BY_WEEK – GRAPH OF TOTAL OVER WIN% BY WEEK FOR CURRENT SEASON AND HISTORY
- CLOSING_LINE_BY_WEEK – ATS FAVORITE WIN% BY WEEK FOR CURRENT SEASON AND HISTORY BY CLOSING LINE – ROLLING TOTAL REPRESENTS AGGREGATE FOR ALL WEEKS TO DATE
- LINE_MOVE_BY_WEEK – PERCENT INDICATING HOW CORRECT LINE MOVES WERE BY WEEK
- ATS VARIANCE BY WEEK – FREQUENCY BY WEEK OF HOW FAR THE EQUATION (FAV FINAL-DOG FINAL-CLOSING LINE) FELL FROM THE CLOSING LINE
- CLOSING_TOTAL_BY_WEEK – TOTAL OVER WIN% BY WEEK FOR CURRENT SEASON AND HISTORY BY CLOSING TOTAL – ROLLING TOTAL REPRESENTS AGGREGATE FOR ALL WEEKS TO DATE
- TOTAL_MOVE_BY_WEEK – PERCENT INDICATING HOW CORRECT TOTAL MOVES WERE BY WEEK
- TOTAL_VARIANCE_BY_WEEK – FREQUENCY BY WEEK OF HOW FAR THE EQUATION (FAV FINAL+DOG FINAL-CLOSING TOTAL) FELL FROM THE CLOSING TOTAL
CLICK IMAGE TO GO TO SPREADSHEET
NCAAF – HANDICAPPING STATS – THROUGH WEEK 02
The information presented here is inclusive of all games played through Week 02 of the College Football Season.
The data provides a snapshot of what is happening by week for the current season and historically across many variables.
In the embedded Excel workbook below, you will find the following worksheets:
- BY_GAME_TYPE_STD – ML/ATS/TOTAL RESULTS BY CONFERENCE/NON-CONFERENCE GAMES BY WEEK
- BY_AWAY_HOME_STD – ML/ATS/TOTAL RESULTS BY AWAY/HOME BY WEEK
- ML_BY_WEEK – GRAPH OF MONEY LINE FAVORITE WIN% BY WEEK FOR CURRENT SEASON AND HISTORY
- ATS_BY_WEEK – GRAPH OF ATS FAVORITE WIN% BY WEEK FOR CURRENT SEASON AND HISTORY
- TOTAL_BY_WEEK – GRAPH OF TOTAL OVER WIN% BY WEEK FOR CURRENT SEASON AND HISTORY
- CLOSING_LINE_BY_WEEK – ATS FAVORITE WIN% BY WEEK FOR CURRENT SEASON AND HISTORY BY CLOSING LINE – ROLLING TOTAL REPRESENTS AGGREGATE FOR ALL WEEKS TO DATE
- LINE_MOVE_BY_WEEK – PERCENT INDICATING HOW CORRECT LINE MOVES WERE Y WEEK
- ATS VARIANCE BY WEEK – FREQUENCY BY WEEK OF HOW FAR THE EQUATION (FAV FINAL-DOG FINAL-CLOSING LINE) FELL FROM THE CLOSING LINE
- CLOSING_TOTAL_BY_WEEK – TOTAL OVER WIN% BY WEEK FOR CURRENT SEASON AND HISTORY BY CLOSING TOTAL – ROLLING TOTAL REPRESENTS AGGREGATE FOR ALL WEEKS TO DATE
- TOTAL_MOVE_BY_WEEK – PERCENT INDICATING HOW CORRECT TOTAL MOVES WERE BY WEEK
- TOTAL_VARIANCE_BY_WEEK – FREQUENCY BY WEEK OF HOW FAR THE EQUATION (FAV FINAL+DOG FINAL-CLOSING TOTAL) FELL FROM THE CLOSING TOTAL
CLICK IMAGE TO GO TO SPREADSHEET
Please note the following regarding the data:
For the spreadsheets BY_GAME_TYPE_STD and BY_AWAY_HOME_STD:
- The data is grouped by a week-ending date and a running season-to-date total
- When a Money Line percent is greater than 75%, the cell is highlighted in green
- When a Line or Total percent is greater than 60%, the cell is highlighted in green
- We have added cells that show the current week differences for both the Season to Date and the Prior Week’s data
- In games that closed as a Pick, for our purposes the Home Team was the Favorite
- All Pushes have been omitted
For the spreadsheets labeled LINE_MOVE_BY_WEEK and TOTAL_MOVE_BY_WEEK:
- The data is displayed in terms of how often the Line/Total move was correct for each line item
- the value of -99 = the cumulative sum of all cases where the line moved down
- the value of 99 = the cumulative sum of all cases where the line moved up
For the spreadsheets labeled LINE_VARIANCE_BY_WEEK and TOTAL_VARIANCE_BY_WEEK:
- The data is displayed frequencies indicating how far from the Closing Line/Total the Final Outcomes were – More accurate Closing Lines/Totals would display as a cluster around the center value of 0(zero), while data painted further from either side of 0(zero) would indicate less accurate Lines/Totals
On the Excel Web App toolbar of embedded spreadsheet, if you click the right-most button, View Full Size Workbook, the entire workbook will open for viewing in a new window
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We hope you find the information an asset to your handicapping and please visit our free site, GreyMatterStats, where we put this information at your fingertips.
If you find something of interest that you would like to share, please feel free to leave a comment or Tweet us @GreyMatterStats
An Analysis Of How College Football Teams Have Performed In Their First Year In A New Conference
A member of BeyondTheBets Forum asked the following question.
How have teams done historically in their first year in a new conference; especially major conferences? Missouri and TAMU have been two teams with some highly varied opinions on them.
You can find the thread here.
We thought it was an interesting question especially in light of the fact that this coming season has 12 teams either switching conferences or moving up in class.
A list of those 12 teams can be found here:
| 2012/2013 | C-FRESNO STATE | WAC | MW |
| 2012/2013 | C-HAWAII | WAC | MW |
| 2012/2013 | C-MASSACHUSETTS | CAA | MAC |
| 2012/2013 | C-MISSOURI | BIG 12 | SEC |
| 2012/2013 | C-NEVADA | WAC | MW |
| 2012/2013 | C-SOUTH ALABAMA | FCS INDEP | SUN BELT |
| 2012/2013 | C-TCU | MW | BIG 12 |
| 2012/2013 | C-TEMPLE | MAC | BIG EAST |
| 2012/2013 | C-TEXAS A&M | BIG 12 | SEC |
| 2012/2013 | C-TX SAN ANTONIO | SOUTHLAND | WAC |
| 2012/2013 | C-TEXAS STATE | SOUTHLAND | WAC |
| 2012/2013 | C-WEST VIRGINIA | BIG EAST | BIG 12 |
For our analysis we included teams that had either switched conferences or moved up dating back to the 2004/2005 season. Overall there were 28 occurrences included in the study as outlined below.
| SEASON | TEAM | FROM | TO |
| 2004/2005 | C-CONNECTICUT | INDEPENDENT | BIG EAST |
| 2004/2005 | C-MIAMI FLORIDA | BIG EAST | ACC |
| 2004/2005 | C-TROY | INDEPENDENT | SUN BELT |
| 2004/2005 | C-VIRGINIA TECH | BIG EAST | ACC |
| 2005/2006 | C-ARMY | USA | INDEPENDENT |
| 2005/2006 | C-BOSTON COLLEGE | BIG EAST | ACC |
| 2005/2006 | C-CENTRAL FLORIDA | MAC | USA |
| 2005/2006 | C-CINCINNATI | USA | BIG EAST |
| 2005/2006 | C-FLA ATLANTIC | D2 | SUN BELT |
| 2005/2006 | C-FLA INTL | D2 | SUN BELT |
| 2005/2006 | C-IDAHO | SUN BELT | WAC |
| 2005/2006 | C-LOUISVILLE | USA | BIG EAST |
| 2005/2006 | C-MARSHALL | MAC | USA |
| 2005/2006 | C-NEW MEXICO | SUN BELT | WAC |
| 2005/2006 | C-RICE | WAC | USA |
| 2005/2006 | C-SMU | WAC | USA |
| 2005/2006 | C-SOUTH FLORIDA | USA | BIG EAST |
| 2005/2006 | C-TCU | USA | MW |
| 2005/2006 | C-TEMPLE | BIG EAST | INDEPENDENT |
| 2005/2006 | C-TULSA | WAC | USA |
| 2005/2006 | C-UTAH | SUN BELT | WAC |
| 2005/2006 | C-UTEP | WAC | USA |
| 2007/2008 | C-TEMPLE | INDEPENDENT | MAC |
| 2011/2012 | C-BOISE STATE | WAC | MW |
| 2011/2012 | C-BYU | MW | INDEPENDENT |
| 2011/2012 | C-COLORADO | BIG 12 | PAC 12 |
| 2011/2012 | C-NEBRASKA | BIG 12 | BIG 10 |
| 2011/2012 | C-UTAH | MW | PAC 12 |
For the purposes of the analysis we created a baseline for each team that consisted of data both pre and post their move to a new conference.
So for example if a team is showing a positive 10.5% over baseline, we are saying that in that first season the team moved to a new conference they did 10.5% better than they had during the comparative baseline period.
Twitter Question – In College Football, How Do Ranked Road Dogs Do When Facing Unranked Home Favorites?
We got a question via Twitter from @EltLearn33 who asked, in college football, how do ranked road dogs do when facing unranked home favorites?
To answer this question we used five years of our NCAAF history which included the 2007/2008, 2008/2009, 2009/2010, 2010/2011, and the 2011/2012 seasons. It is important to note that the rankings we use are our own internal calculations that may or may not , sync up with nationally published ranking data for the given time frames.
The way the information lays out makes it impractical to create a screen capture, so please visit the embedded spreadsheet below for the full breakdown of the data by Season, by Week, and by Conference Match-Up.
Some miscellaneous notes and observations:
- The selection criteria only yielded 64 games which is a very small sample size for analysis purposes, so please keep this in mind as you review the findings
- In 7 of the 64 games the closing line was a pick. Within our system, when a game is a pick the home team is our listed favorite
- In cases such as the PAC-12, which was known as the PAC-10 during part of our history, we use the current name across all time frames
- When analyzing the ML and ATS data by Season no note worthy observations were made other than that for the 2010/2011 Season Ranked Away Dogs were 7-1 ATS
- For all games in all Seasons the Under has been 58.7% in the 64 games in this role
- When analyzing the data by Week no note worthy observations were made
- When analyzing the data by Conference Match-Ups Ranked Away Dogs playing within their Conference from the BIG-10, BIG-12, and the SEC were found to have success both ATS and straight up
- Games played between BIG-10 teams have gone Under the Total 7 times with only 1 Over and a Push
- Games played between BIG-12 teams have gone Under the Total 6 times with only 2 Overs
- Games played between SEC teams have gone Over the Total 8 times with only 2 Unders
- Points do not typically come into play in these games; Excluding 3 ATS pushes in only 5 of 61 games did points enter in to the ATS result
Daily Favorite/Dog & Over/Under Counts For All Leagues
Each morning we will updating this workbook with the prior days counts by League as follows:
- Money Line Record and Win Percent from the perspective of the Favorite
- ATS Record and Win Percent from the perspective of the Favorite
- Total Record and Win Percent from the perspective of the Over
In the embedded Excel workbook below, you will find the following worksheets:
- MLB – DAILY, WEEKLY, AND SEASON TO DATE COUNTS FOR BASEBALL
- NBA – DAILY, WEEKLY, AND SEASON TO DATE COUNTS FOR PROFESSIONAL BASKETBALL
- NCAAB – DAILY, WEEKLY, AND SEASON TO DATE COUNTS FOR COLLEGE BASKETBALL
- NFL – DAILY, WEEKLY, AND SEASON TO DATE COUNTS FOR PROFESSIONAL FOOTBALL
- NCAAF – DAILY, WEEKLY, AND SEASON TO DATE COUNTS FOR COLLEGE FOOTBALL
Grey Matter Stats 