Limited biographical data is available for Big E’s independent profile, but the numbers paint a career that has been anything but small. Across 1,274 total recorded matches, Big E has compiled a 741–520–13 career record—an enormous sample size that suggests longevity, heavy usage, and an ability to stay relevant through multiple cycles of opponents and storylines. In an era where many wrestlers build “highlight careers” on short runs and curated schedules, Big E’s ledger reads like a throwback: show up constantly, take on everyone, and let the win-loss record tell the story.
That record also frames Big E as a wrestler who has lived in the grind. A 58.2% overall win rate is not the kind of number that happens by accident over more than twelve hundred matches. It implies that, over time, promoters and matchmakers have consistently positioned him as a reliable winner—often a featured act—while still trusting him to take losses when the story demands it. The presence of 13 draws adds a small but meaningful layer: Big E has been in enough competitive situations (time limits, chaotic finishes, protected outcomes) that the “no-contest” style booking has touched his career, even if it’s not a defining trait.
If the biographical details are sparse, the competitive profile is clear: Big E is a high-volume performer with a winning baseline, capable of sustaining momentum in bursts, and experienced enough to have developed clear “problem opponents” and “favorable matchups.” Those patterns—who he dominates, who dominates him, and how he trends in short windows—are where the analytics start to reveal the contours of his career journey.
Without a provided classified style label or a confirmed move list in the dataset, MoneyLine Wrestling can’t responsibly tag Big E with a specific archetype (powerhouse, striker, technician, hybrid) or attribute specific signature maneuvers as “known moves” from this data alone. What can be analyzed, however, is how his results behave across opponent types and rivalry clusters—because win-loss splits often function as a proxy for style compatibility.
Big E’s head-to-head record shows extreme polarity: against some opponents he is overwhelmingly successful, while against others he is almost completely shut out. That kind of variance typically appears when a wrestler’s strengths are highly leveraged in certain matchups and neutralized in others. In practical terms, it suggests a performer whose approach—pace, positioning, risk tolerance, and finishing sequences—either matches up perfectly with an opponent’s structure or runs into a stylistic wall.
For example:
So while the dataset doesn’t allow us to list signature moves, it does allow a style conclusion grounded in outcomes: Big E’s career is defined by matchup-driven volatility at the top end. He wins a lot overall, but certain opponents consistently force him into low-percentage paths—either by controlling the pace, disrupting his timing, or neutralizing whatever his primary win condition is in these series.
Big E’s career numbers are the kind analysts love because they’re both large enough to trust and nuanced enough to interpret.
Career record: 741 wins – 520 losses – 13 draws
Total matches: 1,274
Overall win rate: 58.2%
A 58.2% win rate across 1,274 matches implies a career spent more often in winning positions than losing ones, but not in a protected “invincible” tier. It’s the profile of a wrestler who can be credible in main events and programs without needing to be booked as unbeatable. Over a sample this large, the win rate becomes a statement of identity: Big E is a consistent winner, but he’s also a credible opponent for other featured talent.
Where the profile gets more interesting is in the short-window performance metrics:
Even without the full list of those matches, the trend is clear: Big E’s results improve as the window expands from 5 to 20. That’s a notable curve. Typically, if a wrestler is cooling off, the longer window drags down the shorter one; if they’re heating up, the short window spikes first. Big E’s pattern—60% (last 5), 70% (last 10), 85% (last 20)—suggests that he has been operating in a broader stretch of strong form, with the most recent handful of matches being slightly less dominant than the 10–20 match baseline.
This is the kind of shape analysts describe as strong underlying form with mild recent regression. It doesn’t scream “slump,” but it does suggest that the most recent outcomes include at least a couple of results that prevent the last-5 number from matching the last-10 and last-20 strength.
Another key point: the dataset lists Recent Form (last 10): None, which indicates that a standardized “form” label isn’t available here. But the win-rate windows provide a better, more quantitative substitute anyway.
From a trajectory standpoint, Big E’s career win rate (58.2%) is meaningfully lower than his last-20 win rate (85.0%). That gap is enormous. It implies that at some point—recently enough to influence the last 20—Big E has operated at a level far above his career baseline. Whether that’s due to favorable matchmaking, a strong storyline push, or simply a run of stylistic matchups that suit him, the numbers say he has shown a ceiling much higher than his long-run average.
Big E’s top rivalries are where the data becomes most diagnostic. These aren’t just opponents; they’re recurring tests that reveal what kinds of wrestlers he can solve—and which ones solve him.
This is the most lopsided rivalry in the dataset, and it’s the clearest example of a “hard counter.” Winning 1 out of 14 is a 7.1% win rate in the series, and the lack of draws means Big E rarely even escapes with a protected outcome. When a rivalry looks like this, it usually means one of two things: either booking consistently favors the opponent, or the matchup itself repeatedly funnels Big E into losing sequences.
From an analytics perspective, this rivalry is a red flag for future projections. If Big E is scheduled against a Rusev-like opponent profile—someone who historically replicates that same control pattern—models will heavily discount Big E’s baseline 58.2% career win rate.
Big E’s 10–3 record (a 76.9% win rate in the series) is the opposite of the Rusev story. Over 13 matches, randomness fades; this is a meaningful edge. It suggests Big E has a reliable game plan against Rollins—something he can execute repeatedly even as matches change stipulations, pacing, and narrative stakes.
What makes this rivalry especially valuable is that it intersects with the recent match log: Big E has recent results against Rollins, including both a win and a loss in the provided history. That tells us the rivalry isn’t just ancient history—it’s active enough to matter to current momentum.
An 0–8 series is brutal because it removes the “small sample” excuse. Eight matches is enough to establish that, for whatever reason, Big E has not found a consistent path to victory here. Even if individual matches were competitive, the outcome pattern is decisive.
For analytics, this is another opponent archetype warning. If Big E is facing someone with Orton-like traits—someone who can force mistakes, control key moments, and win without needing to dominate every minute—Big E’s upset probability shrinks dramatically.
Big E’s 7–1 record (an 87.5% win rate) is his most dominant favorable matchup among the listed rivals. This is a series where Big E not only wins, but wins consistently. It’s the kind of rivalry that boosts confidence metrics and suggests that when Big E can dictate match structure, he converts at an elite rate.
This is the most “coin-flip” rivalry in the set: 4–3 is close enough that any single match can swing the narrative. Big E has the edge, but it’s narrow—57.1% in the series, almost identical to his 58.2% career win rate. In other words, Sheamus represents the “true baseline test”: competitive, physical, and not easily gamed by matchup quirks.
Both series sit at 66.7% for Big E. These are solid advantages but not dominance. They indicate that Big E tends to win these programs more often than not, but the opponent has credible counterplay.
Overall rivalry takeaway: Big E is not a uniform performer across opponents. He has elite edges (Rollins, Miz), competitive series (Sheamus, Cardona, Crews), and severe matchup problems (Rusev, Orton). That spread is exactly what betting models and predictive engines key on: not just “is he good,” but “is he good against this kind of opponent.”
The provided recent match history spans late 2021 into early 2022 and includes 10 listed matches:
From these results, Big E goes 7–3 in the listed stretch, which aligns perfectly with the advanced stat showing a Last 10 win rate of 70.0%. That’s not just “good form”—that’s contender-level week-to-week output.
The Kevin Owens mini-series inside this run is particularly revealing:
That’s 3 wins in 4 against Owens in a tight time window, suggesting Big E and his camp made adjustments after the 11/29 loss and then tilted the series back in his favor. In wrestling terms, that reads like a champion’s arc: take a punch, recalibrate, and stack wins.
The other notable data point is the split against Seth Rollins:
Given the broader head-to-head advantage Big E holds over Rollins (10–3 all-time in the dataset), this recent loss doesn’t erase the matchup edge—but it does matter for momentum. It’s evidence that even in favorable rivalries, the margin for error can tighten as opponents adapt.
The loss to Roman Reigns on 2021-11-21 is also a momentum checkpoint. In the middle of a mostly winning run, Big E took a high-profile loss, then immediately returned to winning form afterward. That pattern—absorbing a marquee defeat without spiraling—often correlates with strong underlying performance stability.
Finally, the advanced trend line (60% last 5, 70% last 10, 85% last 20) suggests that while this 7–3 run is strong, the most recent handful of matches may be slightly less dominant than the broader 20-match stretch. In practical terms: Big E is still winning more than he loses, but the “peak streak” may have cooled a touch.
The dataset is blunt here:
Those zeros should not be interpreted as “Big E loses every PPV and TV match.” Instead, they most likely indicate that PPV/TV classification data is unavailable or not captured in this specific dataset slice. MoneyLine Wrestling can’t infer a split that isn’t present, and it would be irresponsible to retrofit narratives onto missing classifications.
What can be said is this: because both PPV and TV win rates are listed as 0.0%, the model cannot use event-type performance as a differentiator for Big E in this profile. That removes one common predictive lever—some wrestlers demonstrably “play up” on big events or rack wins on weekly television while struggling on premium shows. Here, the available data does not support that type of conclusion.
So the evaluation has to lean more heavily on what is robust: the 1,274-match career sample, the 58.2% overall win rate, the short-window win rates (60/70/85), and the head-to-head rivalry map.
MoneyLine Wrestling’s predictive framing for Big E starts with a simple truth: with 1,274 matches on record, his baseline is statistically meaningful. A 58.2% career win rate is not noise—it’s a stable indicator that, on average, Big E is more likely to win than lose.
From there, the model would typically weight four major factors that are actually supported by this dataset:
At 58.2%, Big E profiles as a consistent favorite against true mid-card or evenly matched opposition, but not an automatic lock against elite or stylistically difficult opponents. In betting terms, he’s the kind of wrestler who wins “the matches he’s supposed to win” often enough to be profitable—until the matchup profile shifts.
The advanced splits are loud:
This suggests Big E has been operating above his career baseline in the broader recent run, with a slight taper in the most recent five. A model would treat him as a wrestler with positive underlying momentum, but not necessarily at the absolute peak of that run right now.
Importantly, the provided match log supports the 70% last-10 number directly: 7 wins in the last 10 listed matches. That’s the kind of alignment between “advanced stat” and “visible results” that increases confidence in the signal.
This is where Big E becomes especially model-sensitive. Against certain opponents, his win probability should be adjusted sharply.
In other words, Big E is not a one-number wrestler. A generic 58.2% expectation is useful for first-pass forecasting, but the head-to-head map indicates that matchup context can swing him from “strong favorite” to “major underdog.”
In the recent history, Big E takes losses (Roman Reigns, Kevin Owens, Seth Rollins) and returns to winning. That pattern matters because some wrestlers show streak dependency—once they lose, they keep losing. Big E’s listed run doesn’t show that. It shows a wrestler who can rebound quickly, which models often interpret as a sign of stable booking position and consistent performance.
Using only what’s in the dataset, the cleanest projection is:
The most interesting “swing” opponent in the dataset is Seth Rollins: Big E is historically excellent (10–3), but the most recent match listed is a loss (2022-01-10). That combination often creates value opportunities in analytics-driven forecasting—public perception can overreact to the latest result, while the larger sample still favors Big E. In a pure data-driven view, Big E’s long-run edge over Rollins remains one of his strongest statistical arguments.
Bottom line: Big E’s profile is built on volume, a proven winning baseline (58.2% across 1,274 matches), and a recent run that trends strongly positive (up to 85.0% over the last 20). But he is also one of the clearest examples of a wrestler whose outcomes are deeply matchup-dependent—dominant in some rivalries, overwhelmed in others. For an AI prediction engine, that’s not a weakness; it’s an instruction: don’t forecast Big E in a vacuum. Forecast him in context, because the context is where his numbers become extreme.
| Opponent | Matches | Wins | Losses | Draws | Win% |
|---|---|---|---|---|---|
| Rusev | 14 | 1 | 13 | 0 | 7% |
| Seth Rollins | 13 | 10 | 3 | 0 | 77% |
| Randy Orton | 8 | 0 | 8 | 0 | 0% |
| The Miz | 8 | 7 | 1 | 0 | 88% |
| Sheamus | 7 | 4 | 3 | 0 | 57% |
| Matt Cardona | 6 | 4 | 2 | 0 | 67% |
| Apollo Crews | 6 | 4 | 2 | 0 | 67% |
| Date | Result | Opponent | Finish | Rating |
|---|---|---|---|---|
| 2022-01-10 | Loss | Seth Rollins | — | — |
| 2021-12-11 | Win | Kevin Owens | — | — |
| 2021-12-06 | Win | Kevin Owens | — | — |
| 2021-11-29 | Loss | Kevin Owens | — | — |
| 2021-11-22 | Win | Austin Theory | — | — |
| 2021-11-21 | Loss | Roman Reigns | — | — |
| 2021-11-08 | Win | El Grande Americano | — | — |
| 2021-11-01 | Win | Kevin Owens | — | — |
| 2021-10-21 | Win | Drew McIntyre | — | — |
| 2021-10-10 | Win | Seth Rollins | — | — |