[SquareBetNoMore]

I've done a great job of capping games, but when I regularly find losses involve the team I'm backing committing 3+ turnovers. What techniques do any of you use to cap turnovers for college football games? If my team keeps the turnover battle to -1 or better I find I usually win at a fair rate. Let me know what you guys think!

[magyarsvensk]

College football is the most balls to the wall sport to try and cap. There are 12 regular season games and each team's talent level is in flux throughout the season. In other words, you have very little reliable information to go off of and even less information to use to confirm whether you are right or wrong.

If you come out with a nice profit after say 300 bets, then don't look a gift horse in the mouth. Enjoy the winnings.

[nash13]

If you keep tracking turnover margin.
turnover margin < 0 gives you an 71% edge on the ATS.

[Optional]

Maybe check biorhythms for the ball carriers and see if there is any correlation with turnovers.

[PerfectGrape]

The strongest indicator of how a college football team will perform in the upcoming season is their performance in recent seasons.


It may seem strange because graduation enforces constant player turnover, but college football teams are actually much more consistent from year to year than NFL teams. Thanks in large part to consistency in recruiting, teams can be expected to play within a reasonable range of their baseline program expectations each season. Our Program F/+ ratings, which represent a rolling five-year period of play-by-play and drive efficiency data, have an extremely strong (.76) correlation with the next year’s F/+ rating.

The strongest indicator of how a college football team will perform in the upcoming season is their performance in recent seasons.
It may seem strange because graduation enforces constant player turnover, but college football teams are actually much more consistent from year to year than NFL teams. Thanks in large part to consistency in recruiting, teams can be expected to play within a reasonable range of their baseline program expectations each season. Our Program F/+ ratings, which represent a rolling five-year period of play-by-play and drive efficiency data, have an extremely strong (.76) correlation with the next year’s F/+ rating.

http://www.footballoutsiders.com/info/fo-basics

[PerfectGrape]

http://www.footballoutsiders.com/sta...bility-defense

[KVB]

The strongest indicator of how a college football team will perform in the upcoming season is their performance in recent seasons.


It may seem strange because graduation enforces constant player turnover, but college football teams are actually much more consistent from year to year than NFL teams. Thanks in large part to consistency in recruiting, teams can be expected to play within a reasonable range of their baseline program expectations each season. Our Program F/+ ratings, which represent a rolling five-year period of play-by-play and drive efficiency data, have an extremely strong (.76) correlation with the next year’s F/+ rating.

The strongest indicator of how a college football team will perform in the upcoming season is their performance in recent seasons.
It may seem strange because graduation enforces constant player turnover, but college football teams are actually much more consistent from year to year than NFL teams. Thanks in large part to consistency in recruiting, teams can be expected to play within a reasonable range of their baseline program expectations each season. Our Program F/+ ratings, which represent a rolling five-year period of play-by-play and drive efficiency data, have an extremely strong (.76) correlation with the next year’s F/+ rating.

http://www.footballoutsiders.com/info/fo-basics

Interesting info and take on it PG.

After reading the second half of the post I got this strange feeling I had seen this info before.

[PerfectGrape]

really wanted to stress it.
the second article is written by some random programmer guy, just his take.

http://www.slate.com/articles/sports..._the_game.html

We gradually realized that the official play-by-play had serious limitations. Statistics like yards after catch and quarterback hurries would show up on NFL telecasts but were nowhere to be found in the league's stat packages. There were also very few statistics for defensive players and none for offensive linemen.


Since the NFL wouldn't provide the details we needed, we started providing them ourselves. Thus began the Football Outsiders Game Charting Project: Over the past two seasons, more than 50 volunteers have taped and analyzed every game broadcast, tracking everything from pre-snap formations and blitz patterns to yards after catch. To put our project into perspective, the NFL provided more than 54,000 lines of play-by-play information last season. Our goal is to add several layers of detail to nearly all of those 54,000 lines.



These guys have volunteers watching games compiling stats that don't show up in the play by play. I'd imagine oddsmakers have access to data that the public does not. do you guys plan to scrape any advanced football sites for more stats than just the traditional ones?

[Buffalo Nickle]

Turnovers in football are largely considered random by the math guys and losing due to turnovers is variance. If you are winning statistically but losing on turnovers, it just means you were unlucky.

[PerfectGrape]

sack rates have a minor correlation?

http://thepowerrank.com/2014/01/31/h...ising-science/

The components for S&P+ reflect the components of four of what Bill Connelly has deemed the Five Factors of college football: efficiency), explosiveness, field position, and finishing drives. (A fifth factor, turnovers, is informed marginally by sack rates, the only quality-based statistic that has a consistent relationship with turnover margins.)

[ScreaminPain]

Some agree that a turnover is worth 4 points and it's been shown that 80% of all turnovers are caused by LUCK. Therefore, one could assume that to quantify a turnover it may be possible to determine the turnover differences between two teams and multiply by 3.2 (4 points x 80%) divided by games played, adding half to the + team and subtracting half from the - team.

Team w/+ turnover diff.=points-+(1.6 x turnover differential / games played)
Team w/ - turnover diff. =points - (1.6 x turnover differential / games played)

[lawnman33]

The % of these games going under is mind blowing. Go research it. Amazing

[solring]

We gradually realized that the official play-by-play had serious limitations. Statistics like yards after catch and quarterback hurries would show up on NFL telecasts but were nowhere to be found in the league's stat packages. There were also very few statistics for defensive players and none for offensive linemen.

This is part of the point of this Sport's Illustrated article on tackles --> http://www.si.com/nfl/2015/09/18/nfl...e-david?page=4