Stats you can trust

Oct 15, 2002 1:35 AM

   Handicappers often fall into one of two camps. Some like traditional and base their wagers on examining at points, yards, first downs and other conventional NFL stats.

   Others choose to bet armed with situational factors like injury reports, motivational analysis, angles, spread records, and head to head history

   Another way is to try and create better numbers — our own statistics and ratings. These would better reflect the true level of teams’ performances and prove more accurate and predictive in projecting scores for upcoming games.

   An analogy can be found in what has happened in horse racing over the years. For a long time people would look at a horse’s final time and use that as a guide to ability. Then along came a number of smart people (including of course Andy Beyer) who realized that the final time is not very accurate.

   Tracks vary in their general characteristics and the condition of a given track can change depending on water, sand, harrowing and the like.

   These days the sophistication applied to calculating speed ratings is tremendous. Some organizations incorporate wind velocity, post position bias, weight carried, pace effects and other data to stay one step ahead of the general horse betting populace.

   There are many reasons to believe something similar can be done for the NFL. Consider the following examples of how typical information can distort the truth.

   "Non-plays" in averages: This is most commonly seen with the QB "kneel-down" at the end of the game to run time off the clock. Every time the QB sits down, his team gets charged with a rushing play for -1 or —2-yards. Also, QB spiked passes to stop the clock in the two-minute offense count as incompletions.

   Not considering penalties: They are a significant factor, but are treated separately from the main stats. Defensive pass interference calls often go for big yards, and yet they don't show up in a team's passing statistics. At the same time, negative yards from holding infractions often aren’t factored.

   Special teams / defensive scores: These events can inflate a team’s offensive numbers (or defensive ones for the team giving up the TD).

   Situation alters stats: If it's third down and 20 and a called draw play gains eight, the result is statistically deceiving. The defense is happy to concede the eight and force a punt. On the other hand, if it's fourth and goal at the one and my team powers into the end zone, it means much more than a 1-yard TD.

   In light of these and other "mistakes," we seek to create more relevant stats for predicting future outcomes. The “new breed” of stats could begin with Drive Charts.

   The important outcomes to drives are how often a team scores a touchdown, kicks a field goal, and commits a turnover. With this information, it’s possible to measure a team’s efficiency to score and play defense.

   Take a look at this example from the 2000 season NFC Championship game:

   Minnesota was much more potent on offense, but they allowed TDs more often on defense, as well as yielding more field goals. In addition, the Giants’ defense was much better at forcing turnovers (16 to 11 percent).

   With this data in hand and considering the Giants had the additional benefit of home field advantage, New York was the better bet as a 2½ to 3-point underdog.

   You can be certain that NFL teams are tracking their tackle percentages and missed blocks as significant statistics. So, it’s not unreasonable that soon sports gamblers do the same in deciding wagers. features innovative statistical coverage of the NFL.