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Football Game Estimator
  Estimate #1 Estimate #2 Rushing Passing Total Turnovers
Teams Score Edge Score Edge ATT-YDS YPR ATT-YDS YPA ATT-YDS YPP FL-INT
PHILADELPHIA 23   25   23-100 4.4 38-287 7.6 60-387 6.4 1-1
KANSAS CITY 21   22   28-127 4.6 35-244 7.0 63-372 5.9 1-1

StatFox.Com has searched its database for all past games where the posted line or total were similar to this game's and where the final game statistics were comparable to the estimator's projections. (Yards/Play and turnovers) Here are the results against the spread, against the total, and straight up:
In past games, the underdog covered the spread 17 times, while the favorite covered the spread 8 times.
No Edge.
In past games, the underdog won the game straight up 16 times, while the favorite won the game straight up 9 times.
19 games went over the total, while 14 games went under the total.
No Edge.

Potential StatFox Power Trends to watch out for:
Potential StatFox Power Trends based on estimated statistics favoring PHILADELPHIA to cover the spread
PHILADELPHIA is 26-9 ATS (+16.1 Units) when they score 22 to 28 points since 1992.
The average score was PHILADELPHIA 25.1, OPPONENT 16.8
PHILADELPHIA is 9-2 ATS (+6.8 Units) when they gain 6 or more total yards per play over the last 2 seasons.
The average score was PHILADELPHIA 33.4, OPPONENT 15.1
KANSAS CITY is 2-10 ATS (-9.0 Units) when they allow 22 to 28 points over the last 3 seasons.
The average score was KANSAS CITY 22.4, OPPONENT 24.8
KANSAS CITY is 17-35 ATS (-21.5 Units) when they allow 350 to 400 total yards since 1992.
The average score was KANSAS CITY 20.6, OPPONENT 23.7

Potential StatFox Power Trends based on estimated statistics favoring KANSAS CITY to cover the spread
PHILADELPHIA is 11-25 ATS (-16.5 Units) when they allow 22 to 28 points since 1992.
The average score was PHILADELPHIA 19.6, OPPONENT 25.4
KANSAS CITY is 32-13 ATS (+17.7 Units) when they allow 75 to 100 rushing yards since 1992.
The average score was KANSAS CITY 24.9, OPPONENT 18.0
KANSAS CITY is 36-15 ATS (+19.5 Units) when they score 22 to 28 points since 1992.
The average score was KANSAS CITY 25.3, OPPONENT 18.3

Potential StatFox Power Trends based on estimated statistics favoring the OVER against the total
KANSAS CITY is 17-2 OVER (+14.8 Units) when both teams score 20 or more points over the last 3 seasons.
The average score was KANSAS CITY 31.2, OPPONENT 30.5

Potential StatFox Power Trends based on estimated statistics favoring the UNDER against the total
PHILADELPHIA is 6-0 UNDER (+6.0 Units) when they gain 350 to 400 total yards over the last 3 seasons.
The average score was PHILADELPHIA 23.7, OPPONENT 13.3

 

Overview

The FoxSheets Game Estimator attempts to project the final score and games statistics for each team. It factors in recent statistical averages, schedule strength, and home field advantage into each simulation. The Estimator does not factor in injuries, or any other type of non-statistical motivation. Where an estimated score differs significantly from the current line or total, the side with the edge is indicated. There are two different score estimates. The first factors in a team's estimated yardage gained with their yards gained per point ratio. The second estimate is derived by cross-referencing the yards per play estimates and turnovers with past games with similar stats. In addition to the estimated scores, watch out for any highlighted stat fields – red=bad, green=good. This may indicate a potential performance advantage or disadvantage in a given category. The trends in the StatFox Game Estimator section are called potential trends because these are the performance records of the teams when they’ve gained or allowed similar yardage to that projected by the estimator.

How do I use this?

Along with the Super Situations and Power Trends, the game estimator is one of the three most popular sections on the FoxSheets. The simplest way to use the estimator is to look for the green star edges in the game. However, this doesn't always tell the whole story. It is important to look beyond the projected scores and examine the statistics that are projected in the game. You should look for spots where a team's projected statistics in given area draw a green or red flag. Try to visualize how the game is going to play. ex. If a good rushing team matches up against a poor rushing defense, then that fact will be reflected in the team's projected rushing statistics. Look for spots where a team is projected to dominate in one or more areas that may not be reflected in the score. Also look for spots where an underdog might be more competitive statistically than the oddsmakers make it appear. ex. If an underdog projects to green statistics in offensive yards per play, then that is a good indicator that the will be able to move the football enough to stay in the game. Conversely if a favorite holds a huge edge in projected yards per play, then that is a sign that they may be able to totally dominate the game. Regardless of the evidence you point to, the point is that the projected score itself may not tell you the whole story.

Some teams rely on success in certain areas more than others. In the example above, the Eagles were 9-2 ATS when they gained more than 6 yards per play offensively. In other words, if the Philly offense is clicking they usually cover. One would assume that their defense performs more consistently and their success usually hinges more on the offense. Other teams may have the exact opposite situation. For example, there is a very strong trend in college football indicating that Ohio State is nearly a guaranteed cover if they allow less than 14 points in a game. certainly many of these trends will seem like common sense. If a team performs well in one or more stat categories, odds are high that they should do well against the spread. However, as you did deeper and filter through these trends you will notice performance patterns in certain teams. You will see if a team needs turnovers to win or if they have to stop the opposition's running attack in order to cover or if they need to pass efficiently in order to go over the total. All of these things will become more apparent when you analyze the estimator trends.

When used properly, fully utilizing the strategies above, the Game Estimator is probably the one section on the FoxSheets that can be used to handicap games by itself. Of course, when you combine it with injury information along with situations and trends to help you determine motivation, you have a formula for success.

FAQ

Q: Why are there two score estimates?

A: As mentioned in the overview above, the two score projections are determined by two different calculations - two different ways of translating projected stats into scores. Score Estimate #1 takes the projected yards total for each team and converts that into an expected score using the team's offensive yard per point average and their opponent's defensive yards per point average. There are many teams that exhibit "bend but don't break" tendencies. (Ray Lewis and the Baltimore Ravens come to mind.) Other teams can move the ball up and down the field, but can't punch it in for scores. Score estimate #1 factors in these tendencies.

The second score estimate is determined by cross referencing the team's projected offense (yards per play) and project turnovers with all past games where the team had "similar statistics". The average score of those teams is used as the projection for the current team. Score Estimate #2 assumes that the "fluky" plays that affect a team's yards per point average will even themselves out. (ex. Long interception, kickoff, punt, and fumble returns. Turnovers inside the red zone. Missed field goals, etc.)

Q: What do the abreviations in the stat projections table mean?

A: See the key below:
  • Score - Project final score (or score at the end of the first half).
  • Edge - Indicator where the projected score differs significantly from the posted line or total.
  • ATT-YDS (under rushing) - Projected rushing attempts, rushing yards gained.
  • YPR - Projected rushing yards gained per rushing attempt.
  • ATT-YDS (under passing) - Projected passing attempts, passing yards gained.
  • YPA - Projected passing yards gained per passing attempt.
  • ATT-YDS (under total) - Projected number of plays, total yards gained.
  • FL-INT - Projected fumbles lost and interceptions thrown.
Q: What are the key projected statistics to look at?

A: In general you want to focus on any green statistic and view it as a possible matchup advantage for a team. Above that, there are several statistics that serve as key indicators in the various leagues. In the NFL, yards per passing attempt, interceptions thrown, and rushing yards are good indicators. Yards per passing attempt is a far more important indicator in the NFL than passing yards. An efficient passing game opens up the running attack and generally results in fewer interceptions thrown. Total passing yards, in many cases, is only an indicator of a bad team forced to pass only because they are behind on the scoreboard.

In college football, YPR, YPA, and YPP - stats that indicate offensive efficiency - are important. Look for games with exceptionally high (or low) projections in those areas. Also focus in on college football games where there is a huge disparity between the two teams in one of those areas. More than any other sport, college football features games where one team is physically incapable of matching up with their opposition. It is also the only form of football where a one-dimensional team can still whip their opponent. (ex. Navy can't pass a lick but has still managed bowl appearances on a regular basis.)

Arena football is first and foremost a passing game. (>80% of the play calls are passes) As such, yards per passing attempt and interceptions are key indicators. The Canadian Football League (CFL) is more analagous to the NFL.

Q: Are injuries factored into the estimator?

A: The FoxSheets do not directly factor injuries into the game estimator. The reason is that in the game of football, guessing how much a player's abscense and their substitute's insertion into the lineup will affect the final score and stats is just that...guess work. Some competitor services have claimed the ability to adjust their simulators for injuries. However, considering that most of the backup players have limited playing time and statistics to guage their true value, you should be very skeptical. Rather than make these assumptions, the FoxSheets use an approach of "red-flagging" games where there is a significant injury. For a select few superstar players, we will not display a star edge on any game if there is a decent chance that they may not participate in the game. The reason for the red flag will always be noted in the Key Game Information section at the top of the FoxSheet.

Q: Are there any circumstances where you should use caution with the Game Estimator?

A: Like mentioned above, key injuries can throw off projections. In addition, you should also use caution when using the estimator early in the season. During the first few games of the new season, the game estimator will factor in statistics generated from the prior year. For teams whose personnel is basically intact from the prior season, this is no big deal. However, if a team dramatically changed over their roster, you should wait a few weeks to let the current season results factor themselves into the estimator calculation. (ex. Make greater use of the Super Situations, Coaching Trends, and Line Trackers during this time.)

In college football, you should use extreme caution in the first couple weeks of the season. There are many college teams who will lose 75% of their starters from one season to the next. It is important that you disregard simulator results early in the year if one of the teams in the game returns less than 10 starters. The FoxSheets list both team's returning starter totals at the top of the report.

As you move further into the season, the Game Estimator becomes a more powerful indicator, culminating in the post season, where it has achieved great success in recent years.

Q: What does this statistic mean? "In past games, the underdog covered the spread 17 times, while the favorite covered the spread 8 times."

A: Given the current line, along with projected statistics and turnovers, the FoxSheets cross-references the historical database to find all games with a similar closing line and final statistics to these projections. It then tallies up the number of times the favorite and underdog covered the spread, how many times each team won the game straight up, and the number of games that went over and under the total. When one side holds a significant advantage in the count, the edge will be indicated in bold letters.

Q: Why don't the Estimator trends have star ratings?

A: Most of the Estimator trends will simply report what is expected, given the projected statistics. They are not meant to be the basis of a pick itself. Considering the fact that these trends rely on the game playing out similar to the Estimator projections, we choose not to display star ratings. Estimator trends are effectively two steps removed, as opposed to the other types of trends, where the factors going into the game are actually a 100% certainty as they're displayed.
 

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