Program Building Archives - Football Toolbox

The Most Overlooked Tendencies That Make a Difference in Scouting

September 21, 2022 by

With the ability to add your own custom columns to the Hudl Beta, consider tracking these underutilized data points in your scouting workflow.

The Hudl Beta is allowing coaches to work even quicker this season as we all hit the ground running. And now with the ability to add your own custom columns to this scouting Beta, the possibilities are limitless.

When it comes to what data points coaches track in Hudl, there are rarely two coaches using the same workflow. That’s why customization is such a game-changer for the beta.

When you add custom columns to your grid, they automatically populate under in your Hudl Beta under the “Other” section.

Moving them to another section, such as Offensive Tendencies, is easy. Just open the card, and click where you want it to go.

I spoke with a handful of coaches that are devising custom scouting tags in Hudl to make their scouting methods more definitive and, in turn, getting a leg up on their opponents.

We came across some popular examples, such as home bench tendency for offenses that like to run certain concepts to the sideline. But we also found lesser-used tags like these ones below can be instrumental in exposing crucial tendencies that may normally fly under the radar.

The ‘Next’ Custom Tag

Rob Everett
Head Coach
St. John Paul II High School
Huntsville, Ala.

When scouting his next opponents’ offense during game week, Everett will create a custom column labeled “next”, where he will input what happened on the previous play from scrimmage.

For the first offensive play of the game, he’ll tag the word “Game” in the next column. If the quarterback throws an incomplete pass on that first down, he’ll tag “incomplete” in the next column on the second play, signifying the previous play.

During the course of his breakdown, he will use the following tags:

Tackle for loss
Sack
Complete pass
First down completion
First down run
Turnover
Penalty
End of game
End of half

When this data is filtered and analyzed with all other important situations like down and distance and field zone, it gives good situational insight into an offensive play-caller’s rhythm.

“Now you can get a really strong insight into the play caller and what he likes to do in those fluid situations,” said Everett. “When you compare those numbers with their generic overall numbers from personnel and formation, you can zero in and capitalize on those specific situations.”

Virtual Alignments

Steve Erxleben
Defensive Coordinator
South River High School
Edgewater, Md.

On top of traditional data points like play concept, field zone and down-and-distance, the defensive staff at South River charts both the width and depth of offensive linemen’s splits. This comes in handy particularly on early, run-heavy downs such as first and 10, second and medium, and second and short.

The goal is to identify a tendency towards a particular run scheme. Using the end zone cut, they create a custom tag with the labels “wide”, “tight” or “normal.” They’ll work through the same procedure with running back location in shotgun alignments using the tags “deep,” “sidecar,” and “wide.”

Once these data points are filtered with the specific play concept, they’re able to make accurate predictions on alignment and concept marriages.

For Erxleben, the importance of tracking these data points lies in the productivity of his no-huddle defense, where calls are predominantly made from the sideline and in the booth.

“We tend to check our pressure based upon certain alignments, which comes from the booth first,” he said. “Those alignments can often dictate our calls because our booth staff is identifying them pre-snap and making the right calls accordingly.”

P.J. Fleck’s ‘78 Percent’ Matrix

Jeremy Plaa
Head Coach
Thomas Downey High School
Modesto, Calif.

University of Minnesota head coach P.J. Fleck swears by his “78 Percent Rule”. The rule says that you have a 78 percent chance of winning the game if you win one of three stats: explosive plays, turnovers or missed/broken tackles.

If you win two of those stats, Fleck says your chances improve to 90 percent. All three? You can probably guess.

Plaa has not only altered his focus in practice to addressing three elements, but also started charting each of these categories for his opponents for both sides of the ball. This fall, he’s taking extra time studying how takeaways occur situationally, then he builds in his defensive practice plan to devise reps to attack those weaknesses.

If a quarterback routinely has deflected passes, Plaa will spend more practice teaching defenders how to bat passes and corral them. From an offensive perspective, he’ll study all of the explosive plays (20 yards or more) the opponent has surrendered and work to mirror each of those scenarios and build a game plan around it.

“For example, one of our former opponents likes to play seven in the box and play loose cover zero,” said Plaa. “So, one team last year hurt them with a mirrored Post-Wheel combo. The safeties on both sides would freeze their feet and react to the inside receiver’s route. We throw a lot of posts in our offense and we made sure we have to have this play call all over our play sheet.”

And because there is a significant correlation between yards/first downs given up and missed tackles, he will create a custom column to chart his defenses missed tackles. Then he can easily sort and create a playlist on the types of missed tackles (in the hole, sideline, open field, etc.) with the intent of devoting more time on those scenarios in-season. He has also started to track his player’s broken tackles to reinforce the 78 percent matrix.

Pass Pro Efficiency

Nick Davis
Defensive Coordinator
Rose-Hulman Institute of Technology
Terre Haute, Ind.

At Rose-Hulman Institute, Davis created a “Pass Pro” category in Hudl when devising his weekly game plan. He’ll study each pass concept from the opponent’s offense, then add a column tracking whether or not the quarterback completed the attempt and if he was moved off his spot. He’ll quantify these numbers and compare their efficiency to make determinations on creating pressure.

For example, if the quarterback shows he is 90 percent efficient when standing in his intended spot, Davis will design most of his rush patterns to get the quarterback on the move. Conversely, if the quarterback is 85 percent efficient when he is either hit or moved off his spot, he might devise a controlled rush plan instead. The goal is to get the quarterback off his spot on more than 50 percent of snaps.

***

Football has always been a copycat game, and good scouting is a byproduct of studying how opponents’ deficiencies get exposed during the course of the season.

Each opponent has flaws, either by personnel or scheme, and it’s our job as game planners to identify and exploit these weaknesses. And as we continue to navigate through the most uncertain period in our coaching tenure, utilizing custom tags like the ones above can provide stability in your game planning methods.

Log in to your account and start adding these ideas to your data workflow. Then, watch how quickly you pick up on these key tendencies in the Hudl Beta.

Creating a Collaborative and Efficient Defensive Gameplan

August 15, 2022 by

Be sure to use these field sets listed below in your data entry to maximize your gameplanning efficiency.

Twenty years ago, the laborious and time-consuming process of padding games was the norm in game-planning. Staff would painstakingly and meticulously write down every formation, down, distance, and play by hand. But getting the data down was only half the battle. The real challenge came after the padding. That is when forensics began.

Coaches would share the role of looking for tendencies, takeaways, and telltale signs of the scouted team. No stone was left unturned, but in its wake were countless wasted man-hours and, of course, many yellow legal pads.

Football has come a long way, and the advent of Hudl has given coaches and players across the country film review, gameplans, and presentations at their fingertips. Now, new Hudl has taken the evolution of the game one step further and given us user-friendly, real-time results that allow the entire offensive or defensive staff to break apart opposing teams in a fraction of the time.

Here’s how you can utilize new Hudl to create a collaborative, effective, and efficient game-planning model that all programs can implement immediately.

Create your organizational workflow

At St. Charles North, we asked ourselves a few key questions.

How can we use our game planning to yield more R.O.I. on our practice and games?
How can we, as head coaches, create a system that makes every coach on our staff an expert in one area of the game plan?
How can we streamline our game-planning duties to a finite focus?
How can we create individual coach ownership over the game plan?
How can we create clear expectations and workflows that will allow staff not to live in the office?

Divide and conquer is the name of the game when creating a game-planning model on new Hudl. Each coach on your staff is assigned a specific aspect of the game plan to become the “expert” on. For the sake of this article, we’ll look at the defensive side of the ball. Before you begin the actual data entry, it is important to identify these roles and then create field sets for each coach that includes only the columns that they’ll need to enter data to yield their desired tendency results.

Here is an example of how our staff divides the defensive game plan and a designated field set:

We have a few non-negotiables for establishing our game-planning model:

The weekly responsibilities of each coach will not change.
Coaches are not allowed to manage any area that’s not their own. Categorizing the game plan will allow for deep thinking in your content area and limit the armchair quarterbacking between staff members.
Timelines and due dates are assigned to each aspect of the game plan.
The completion schedule must be adhered, to because the individual aspects of the game plan are not mutually exclusive. If one part lags, it hinders the progress in other aspects of the game plan model.

New Hudl Field Set Details

The field set columns you create for your program can be unique to your desired results for the game-planning model. This is what we look for, and how we assemble our differentiated game-planning field sets. Please note that some are found in the “My Columns”, while others are custom.

Formations
- Establish common vernacular/abbreviations etc:
- Back sets
- Personnel groupings
- Sets: 2×1/2×2/3×1, FIB, etc.
- Movements: Motions/shifts
- Notes: Overall Tendencies
Pass/Run Game Reports
- Down and distance
- Formation tendency
- Movements used
- Personnel: Who are the studs?
- Targets: Who is getting the ball where and when
- Scheme
- Routes
- Pass zones
- Personnel: Who to exploit, who to avoid
Pass Protection
- Pass pro: Identification of different types of pass protections
- Pass scheme: What scheme is associated with each pass protection?
- Down and distance tendencies
- Personnel: Who to exploit, who to avoid
Situations
- Opening offense (both first and second half)
- Four-minute offense report and cut-ups
- Two-minute offense report and cut-ups
- Sudden change
Field Zones
- Reports for typical zone
- Down and sitance
- Field or boundary tendency
- Hash tendency
- Separate red zone report
Down and Distance
- Overall tendency by distance
- Formation tendency
- Top runs and top passes
- Hash/field/boundary tendency
- Personnel
- Best calls based on opponent success rate analytics

Data Entry

Once the field sets are created, the next step is to input all the necessary data. In a collaborative game-planning environment, your data input is minimal and allows each coach to become the “expert” in their particular field. In new Hudl, the turnover of usable tendencies is completed in real time. Taking the data from new Hudl to the gameplan is a streamlined and seamless process.

Just Getting Started: Hudl Focus Outdoor Will Continue to Improve

July 27, 2022 by

Hudl’s outdoor sports camera already simplifies the recording workflow with powerful features. But that’s only the beginning.

Hudl Focus is already known for everything it can do: automatically record, clip and upload games; integrate with Hudl Sideline; provide flexible livestreaming and broadcasting options; and add context with scoreboard overlays.

But we’re only getting started.

What separates Hudl Focus Outdoor from other cameras is the auto-updating feature. Our smart camera is designed to hardwire into an ethernet port for added speed and sustainability.

This means that whenever Hudl releases new features for Focus cameras, your camera will automatically update to include those new features.

Focus Outdoor can do so much for teams today, right now. But the sky’s the limit for new features in the coming years.

“The way we’ve designed these cameras is we pack a ton of technical power into them that we’re not even using yet,” said Austin Nichols, product manager for American football at Hudl.

“It’s a smart camera, it has a computer inside of it. So you get it on day one, and by year three there’s an exciting new feature where maybe you get another video angle or even faster uploading. I think that’s one of the truly exciting and powerful things about a camera like this.”

In terms of planned updates coming down the pipe, nothing is guaranteed. But the possibilities are overwhelming.

One feature we’ve prioritized for coaches is the Focus Exchange Network. This network will share recorded game video from a single camera with both the home and away teams. No more lugging around extra equipment on the road!

That’s why coach feedback is so important for our team, not only for testing the camera to make sure it exceeds expectations today but because coaches can shape what features and tools we release in the coming years.

“The new camera specifically is exciting because of the power it has,” said Joel Hensley, Director of Engineering for Hudl Focus. “With that [power] we could give them information about the type of plays they’re seeing or formations. Other types of information that their competitors aren’t going to have during the game.”

Sports continue to grow and change, with new schemes and patterns emerging all the time. Just as coaches study these changes to stay ahead of the game, the Hudl Focus camera will evolve to match the ever-changing landscape. That means new features without you having to lift a finger.

Delivering the Best Film Quality Possible

June 7, 2022 by

Hudl’s outdoor smart camera was engineered to provide teams with the highest quality video possible.

Coaches have told us time and time again that crystal clear video is key to staying a step ahead of the competition. With Hudl Focus Outdoor, our goal was simple: provide coaches and teams with excellent video, automatically.

Unlike our indoor solution, which records under a consistent environment in gymnasiums, the outdoor camera has to deliver high quality video while overcoming additional challenges.

From the angle of the sun and stadium lights to extreme weather and varying stadium sizes across the country, Focus Outdoor must overcome and adapt to all these variables to record high-quality film for outdoor sports.

And when it comes to high-quality film, HD is an absolute must.

In 2019, we upgraded the Hudl platform to feature video playback in high definition. Admittedly, it was a change that was long overdue. Our smart camera couldn’t offer anything less—our coaches deserve and expect the best.

And no one has higher standards for film than American football coaches.

“We are building a camera for football coaches, who have the highest standards of anyone I’ve met,” said Joel Hensley, Director of Engineering for Hudl Focus. “They want perfection. They demand perfection. So they are going to have a keen eye for anything that doesn’t look great. We have to make sure that the video quality we’re delivering meets their needs.”

Coaches were instrumental in providing feedback that propelled us toward that goal.

Lake Travis high school football head coach Jonathan Coats said his program was willing to splurge on expensive cameras and equipment if it meant capturing the highest quality video possible. As part of the Focus Outdoor beta program, Coats said initially that the quality wasn’t better than what he could capture with his existing cameras.

Based on feedback from Coats and other coaches in the beta program, our engineers lasered in on improving video quality.

Coach feedback helped the engineers create a rubric for grading video quality to ensure the video would surpass expectations. Key factors to coaches were things like the consistency of video playback—meaning no stuttering, no dropped frames, etc.—and that the camera accurately followed the play without ghosting (players looking blurry or “teleporting” due to missed frames) or blurred images between from one camera lens to the next. It emphasized low image noise, strong color and sharpness.

“We vetted a couple different types of lenses to make sure […] the distance was good and the clarity was good,” said Quality Assurance Director for Hudl Focus Ashely Shubkagel. “We test our lenses right after we get them from our supplier. Then once they’re in the cameras, we test them again to make sure there’s no point of blurriness on the field.”

Thanks to feedback from users, we improved our processes all the way down to how we assemble the cameras. Because quality isn’t just our goal. It’s our passion.

Hudl Focus Outdoor is available as part of an athletic department package. Contact Hudl to learn how to secure your camera.

Football Coaching Personality: The Accountant

May 27, 2022 by

Banker by day, assistant football coach by afternoon, Jeremy Fisher first built his complex analytics database for this small Northern Kentucky program nearly two decades ago. And that intense dedication to data has had three-time defending state champ Beechwood punching above its weight class ever since.

A visit to Pro Football Focus’ palatial Cincinnati mega-lab two years ago did wonders for Beechwood High School’s staff, including its intensely-driven analytics guru Jeremy Fisher. But oddly enough, it was more for what it confirmed rather than revealed.

Over the course of a day, this small school out of suburban Fort Mitchell, Kentucky was shown virtually every step of how the magic is made. The revered football analytics data-miner is majority-owned by Sunday Night Football analyst Cris Collinsworth and counts more than 60 major Division I football programs and all 32 NFL teams among its clientele. Fisher and his fellow coaches periodically found themselves chuckling amongst themselves throughout the demonstrations — when asked what was so funny by PFF staffers, they replied, “Oh nothing, we’ll show you at the end.”

The end came about. Now it was Fisher’s turn to take the sabermetric wizards through his workflow process. Project manager for Citibank by day, football coach by afternoon, Fisher has melded those two disciplines into a remarkably efficient database that has kept dozens upon dozens of data columns on every single one of the Tigers’ plays for nearly two decades. And the data-hunting process — the tendencies, the acute attention to details on formations and positioning — nearly mirrored PFF’s own.

The first thing the PFF staffer remarked? “You guys don’t really need us, do you?”

The second thing was, “Do you want a job?”

And, well, that’s just the thing. Fisher, who specializes in Management Information Systems and database designs for one of the world’s largest banks, loves his day job. Loves the numbers. Loves what he can do with the numbers. Loves the limitless possibilities they hold.

And playing with numbers all day has only inflamed his passion for football analytics over the years.

The marriage of these two principles goes all the way back to 2002, when a coaching change elevated then-defensive coordinator Noel Rash into the head coach role. Rash came from a vastly different background than his predecessor — an assistant at one of the most storied high school programs in Ohio state history, Archbishop Moeller — and wanted to look at things in a new way.

He wanted to take a deeper dive into the data, and then he wanted to look at it from a different perspective. To Fisher, Rash laid out all of his thoughts one day, and then said the magic words, “Can you make this work?”

Goodness gracious, did he ever.

Years before Hudl had even gotten its footing in the market, the Beechwood staff was already keeping anywhere from 20 to 44 pieces of data on every single play, exporting the information into a Microsoft Access database that hosted all specific play data obtained in breakdowns going back to 2006. From there, Rash got a reporting platform with all the information in the exact format he wanted. And with Fisher’s background in a plethora of reporting software, Rash could get this information however he wants, with whatever fancy visuals he tastes.

Fisher was then (and still is) challenged by his superiors to go a little further down the rabbit hole. That means going beyond the box score to chart out a number of additional items ranging from the simple (field vs. boundary, strong/weak running by formation and down) to the complex (charting individual player touches by position, formation and targets). Fisher even goes as far as to use a stopwatch app on his computer to time how long it takes the quarterback to release the ball once it’s snapped. The Tigers adjust their pass coverage based on the length and timing he measures.

By any standard in the high school stratosphere, what the Tigers have in place is astonishing. Thanks to an acute attention to tendencies and tells, they often find they know what to expect when opponents break the huddle. In 2016, their first of three straight state championship-winning seasons, Fisher estimates that his defensive staff accurately guessed their opponent’s exact play nearly 63 percent of the time.

The next season, that number dipped to 48, and then last year it was 52 as they made it a Class 1A three-peat.

Just how valuable is that information? Consider the Tigers’ final two opponents of the 2018 season.

In the Class 1A state semifinals, their touch-tracking data, which Fisher typically compartmentalizes into personal touches, position touches and formation touches (including targets into those figures), concluded that Campbellsville’s star athlete touched the ball on 80 percent of the offense’s snaps. By the end of the first half against Beechwood, that star athlete had totaled minus-24 yards from scrimmage, as the Tigers went on to win in a romp.

The next week, in the 1A state final on the University of Kentucky campus, Fisher’s data found that Pikeville’s star quarterback was not only an exceptional runner who got the ball 70 percent of the time, but was also used aggressively to command pace early. Pikeville’s average game-opening drive lasted only six plays, with their star getting five touches. But against the Tigers, their first series ended in a three-and-out — and no touches for their primary playmaker. Pikeville’s QB also never kept the ball on third down, which influenced Beechwood to show completely different packages on first and second downs. All of it added up to a nail-biting 21 – 20 win.

To harden itself for the state playoffs, the Tigers will routinely schedule opponents during the regular season that are three or four classes above them. And while in some years they may have luxuries in size or athleticism, those are mostly exceptions. Often, they are undersized against opponents. But this deep well of information allows them play fast, without having to think too much out there.

“We don’t want to come across like we feel we’re better than anybody,” Fisher said. “But at the same time, we also don’t want people to realize how much information we really know and understand. There are very few games that we go into and say, ugh, we don’t have a chance.”

Fisher estimates that the Tigers’ database has data on more than 50,000 individual plays going all the way back to 2002. As the game continues to evolve in so many abstract ways, and as your typical high school offense becomes less and less predictable in this age of mega-data, the Tigers will continue to tweak and enhance this elaborate workflow.

“I hate to come across as though I have some sort of specific knowledge,” Fisher said. “But I’m not gonna lie, I’m fairly proud with myself of the fact that I’ve been able to find some success relating between the two jobs that I have, to take what I do at Citibank and be able to apply data analysis, to be able to interpret results and information, and be able to apply it to football.”

With the ability to add your own custom columns to the Hudl Beta, consider tracking these under­uti­lized data points in your scouting workflow.