NFL football seems always in a state of flux and the Los Angeles Rams must keep up with current trends and movements. At the least, they risk being behind the curve, or worse, just left behind. How we fans track and evaluate the team must also keep up with the times.
Year-round and specialized conditioning programs have made players are bigger, faster, and stronger than ever. All the hybrids of west coast, run-and-shoot, and spread offenses out of the shot gun formation are throwing the football 60+ percent of the time, the NFL sanctions this by passing bylaws that continually handcuff defenses, and positions (running back and linebacker) that were once deemed essential and filled with star power are now looked upon as cost-cutting areas.
Why not add a GPS chip to the football and shoulder pads to record and get a better understanding of the ball and player movements?
It need not be a fiery debate. The game of football is not an exact science and while the inclusion of advanced metrics/analytics may enhance how we measure play on the field and the grading players, both established and prospective, it will not completely replace time-tested methods of evaluation. Football is simply too subjective to outside elements to ever find an objective truth.
Why not incorporate the best of all three evaluation/analyzation tools?
The old school way in the measurement of on-field production and I would add the speed, explosion, and short area agility numbers of the NFL Combine and Pro Day’s into this grouping. A good stat site like Pro Football Reference has a myriad of interesting stats to absorb and is constantly upgrading and reaching further back into history. Although the game is constantly evolving, it is interesting nonetheless to be able to compare players through the generations. All for zero cost.
While individual stats are more indicative of team performance, stats sites are digging deeper into team stats and offering perspective into their success of failure. But In far and away more cases, production, size and speed are the dominating traits of individual NFL players.
As far as analytics replacing the Combine, not anywhere in the near future. Surprisingly, not enough colleges have advanced metric access, you would think they would all have at least some statistical analysis program presence. To my knowledge, of the major college all-star games, the Senior Bowl is the only one with a strong analytic presence. Advanced metric-based GPS top speed numbers that can be fine-tuned for each yard of the run may very well give a truer estimate of play speed, but the 40 and particularly its 10 and 20 yard splits will continue to be relevant until everyone is under a system.
The eye test is something all fans can use, no math prodigy skills, subscriptions, or deciphering and memorizing multiple acronyms. See it and say it. “I saw his film against ‘Bama and that cat can flat play.”
In just a little film, we can see a offensive lineman bending at his knees or lunging at his foe, a wide receiver who gets into proper position for his breaks or rounds off his cuts, a running back with good/bad vision or contact balance, and a quarterback with a strong arm and can extend plays with his feet, but is off target in his ball placement.
One thing we can appreciate on the eye test are intangibles. Sometimes it’s the dirty work that necessary and others it’s the big play that comes from reading the action. It could be a defensive lineman locking up two blockers to allow a mate to loop around him, a wideout who is continually running clear out routes and blocking with effort, or a defender in coverage who gets good depth and forces a high throw that can be be intercepted. Other than the basic stats of the outcome, it’s difficult to give much more than an “atta boy” to the player doing the dirty work.
A field that is relatively young and growing exponentially. Analytics give not only nuance to on-field production and the eye test, but a fresh look at it. Stripped down to its basics, it’s stats put under a microscope, giving an expanded look at some, bringing others into into view and a taking huge pile of eye test data points, separating them into sets. It takes stats and eye test and attempts to turn them into competitive advantage and then when applied, to become wins.
Of course, nothing is guaranteed in the NFL. Not bounces, not officiating, and certainly not decisions based purely on the highest percentage of success. Decisions, by their nature, are an inexact science, the best thing to raise odds for their success is information. Information is power, the proper tool to be used in the proper situation.
There are many different advanced metric formulas each with an acronym, but again stripping it down to it’s basics, Expected Points (EP) and Expected Points Added (EPA) are a way to measure the value of a play or player and how successful they are in certain scenarios. EP sets a baseline and EPA provides the measurement of varying success or failure against it.
Aaron Schatz, Pro Football Focus, SIS Datahub, and Next Gen Stats are some of the big names. But, each season, bright young minds are coming up with formula’s that strive to make a subjective process more objective. This year marks the sixth year of the NFL’s Big Data Bowl, a sports analytic contest that is daring to re-think the evaluation and analyzation of football performance. This year’s theme is tackling performance.
The crowd-sourced competition uses data and technology to spur innovation that results in creating new insights, making the game more exciting for fans and protecting players from unnecessary risk.
How do you analyze the game?
And can/would you be consistent in the applications. Would you blindly follow the book when making decisions on fourth downs, extra points, short yardage run/pass plays? Or do you think emotion, momentum, and/or “feel” should be weighed in? While the results of a play in the early/mid part of a game can be just as telling on the final score, should some weight be put on being aggressive early and conservative late? Vice versa? Or is “the book” of advanced metrics the gospel, an infallible guiding doctrine?
As for me, l prefer the consistency of set thinking on fourth downs and two point conversions all throughout the game, whatever gives the best expectation of success. On whether to use pass or run, some freedom demands to be warranted to take consideration of distance needed and flow of the game.
Draftniks are in the heart of player evaluations and how they might fit into individual teams and schemes. Which path should be taken?
On my draft evaluation, it’s more of a mixed bag. Eye test certainly gives perspective on how candidates navigate the game. Although statistics can be inflated, on-field production cannot be denied and draft history shows that the stellar physical traits, size, speed, length get drafted, very often above their performance. While, I do not subscribe to any analytic services, they are sought after voraciously in articles, on twitter, and in other published draft profiles. There is much open source information available.
So, let’s hear it. What is your chosen method of evaluation/analyzation?