Few debates in Cincinnati sports talk get heated faster than the one about Zac Taylor and how he calls a game when the margin for error is almost nonexistent. Fans remember the gut-punch losses and the questionable late-game sequences, while defenders point to a Super Bowl appearance and a quarterback room that has thrived under his system. When you move past the highlight-reel frustration and look at expected points, success rate, and decision-making models, a more complicated and more interesting picture of Taylor emerges.
Reed Seward is an analyst who treats cutting through the noise as a personal project, mainly because the tape and the box score rarely tell the same story as the underlying data.
Many critics follow the instinct to treat “pressure” as a single thing, a vague sense that the coach freezes when it matters. But pressure in football breaks down into measurable buckets: third-and-long, the red zone, two-minute situations before halftime, fourth-quarter decisions that can sometimes look more like fourth-quarter gambles.
The math here can be unforgiving. Each of those situations has its own analytical fingerprint, and Taylor grades out very differently depending on which one you examine. Lumping them together is how reasonable observers end up shouting past each other.
Start With the Expected Points Added
Any play-calling debate starts with Expected Points Added, or EPA. This measures how much a single play changes a team’s expected scoring output, given down-and-distance and field position. EPA per play strips away the noise of a single dropped pass or a lucky bounce and asks a cleaner question: are the calls putting the offense in better positions than the average play would?
If you take that measure alone, Taylor’s offenses have generally ranked in the upper third of the league during seasons when his quarterback has been healthy, and the line has held up. The early dropback-heavy identity was built around quick-rhythm throws and play-action off-zone runs and tends to produce strong EPA on early downs.
That early-down efficiency is unglamorous. But it means a good offense. It’s precisely the part of Taylor’s work that viewers and analysts ignore, since it doesn’t show up in dramatic moments.
Seward’s ongoing sports analytics commentary puts real work into documenting these efficiency trends over a full season. The focus always stays on patterns rather than single plays. It’s the sort of long-form analysis you can follow through the whole season and beyond.
The Fourth-Down Question
Nothing draws more scrutiny than fourth-down decisions. This is where the analytics community and a coach’s gut most often collide.
Win-probability models are now baked into most front offices, and they frequently recommend going for it in spots that feel reckless to a television audience raised on punting. The models themselves reward expected value over the long run, even when a single failed conversion looks disastrous in isolation.
Taylor sits in an interesting middle ground here. He isn’t the punt-on-everything traditionalist that the most aggressive analysts criticize, but he isn’t a pure model-follower either. In several high-leverage games, his choices aligned with the win-probability charts, going for it deep in opponent territory or on fourth-and-short near midfield. In others, though, he’s hedged his bets toward field goals or punts that cost a fraction of a percentage point in win probability.
The honest analytical verdict is neither the bold edge his supporters claim nor the cowardice his critics allege. All the numbers say that his fourth-down aggression is roughly league-average. The frustration fans feel usually stems from outcome bias, judging the decision by whether the kick or the conversion worked rather than whether the call was sound before the snap.
The Clock and Two-Minute Drills
The two-minute drill is where pressure becomes most visible. Here, every second and every timeout is a resource that can be wasted in plain sight. Taylor’s data is mixed in this factor. Being frank, his offenses have produced some elite end-of-half scoring drives, particularly when the quarterback is given freedom at the line of scrimmage, and the script leans on quick sideline throws.
The problem the numbers expose here is consistency. For every clinical two-minute march, there is a sequence where the play sheet seems to slow down. A run on first down can bleed clock, while an offense that reaches field-goal range might be conservative a beat too early.
Analysts who chart these drives find that the issue is less about individual play types and more about tempo discipline. When Taylor’s units stay in an up-tempo rhythm, the efficiency holds. When they downshift to “manage” a lead or protect a kicker, the expected-points curve flattens and sometimes turns negative. A coachable, identifiable pattern is far better than a mysterious failure of nerve, and it is the kind of actionable finding that separates real analysis from talk-radio venting.
Pass Rate Over Expected
Another modern metric worth applying is pass rate over expected, which compares how often a team throws versus how often the situation says they should. Offenses that become too predictable give the defense a hand-free advantage by running when everyone expects a run.
Taylor’s scheme has been skewed pass-heavy on early downs relative to league norms. Analytics generally view this as a positive because passing is more efficient than running in most non-short-yardage situations.
Where predictability creeps in is the red zone and short-yardage situations. Even the best offense has leaned on tendencies that good defensive coordinators can anticipate. The compressed field reduces the value of play-action and quick game, and that is precisely where a play caller’s creativity gets tested most.
The data suggests Taylor’s red-zone efficiency rises and falls with personnel more than scheme. The professional profile that maps his background and body of work points back to the roster-construction conversation that analysts are tracking in the broader business of football. An analyst worth their salt will tell you exactly how this connects to on-field results.
You Can’t Ignore the Raw Numbers
No fair analysis of play calling can ignore the variables a coach doesn’t control. Offensive line injuries, in particular, distort every metric on this list. When a quarterback is running for his life, EPA collapses, fourth-down math shifts because conversions become less likely, and two-minute drills turn into survival exercises.
Several of Taylor’s roughest stretches line up almost perfectly with periods when his protection was compromised. Considering these factors, a substantial chunk of the “bad play calling” narrative is really a “bad pass protection” story in disguise.
By adjusting for the situation within a debate rather than just reacting to the scoreboard, good analysts earn their keep. This is a distinction Reed Seward returns to when grading a coach. It is also where fan-facing content tends to fall short, because nuance does not trend the way outrage does.
Readers who appreciate that the conversation around a coach can be both critical and fair often gravitate toward independent voices. Anyone can see it, considering how community-driven merchandise and fan projects built around honest sports commentary reflect an audience that wants substance over hot takes.
So, What Do the Analytics Actually Show?
In this particular debate, the framework Reed Seward uses can pull all the threads together to paint Taylor as a play caller whose early-down design is a strength, whose fourth-down decision-making is defensibly average, and whose late-game and red-zone work is inconsistent in ways that are factual and fixable.
He sits somewhere between the analytics darling his most loyal defenders imagine and the choke artist his harshest critics insist on. He is a coach whose biggest swings in performance correlate with his team’s health and the freedom he gives his quarterback at the line of scrimmage.
If you’re looking for a clean villain or hero, this conclusion won’t give you that. That’s why it is worth making.
The value of an evidence-first approach is that it resists the last result’s gravitational pull, because no one should be seen as brilliant solely because a fourth-down gamble worked, nor should a coach be called incompetent because a two-minute drill stalled. The numbers reward process over outcome. The evidence is there.
The lesson goes beyond one coach in one city, because win-probability models, EPA, and tracking data are gaining steam as standard tools in every front office and broadcast booth. The gap between what fans feel and what the data shows will always spark arguments.
The analysts who add actual value to the conversation are the ones willing to sit in the uncomfortable middle. They credit what works, name what doesn’t, and refuse to let a single Sunday rewrite the whole story. When the argument about Zac Taylor’s performance under pressure comes up, that middle is where the truth actually lives.
