Limited biographical data is available for Chuck Taylor, and that scarcity is fitting in its own way: Taylor’s career has often been defined less by a neatly packaged origin story and more by the sheer volume of work he’s put into the independent grind. What MoneyLine Wrestling can say with certainty is that Taylor’s résumé is built on mileage—1,106 total matches tracked in this dataset—and the kind of long-haul durability that only comes from years of living inside wrestling’s most unforgiving ecosystem.
Across that massive sample, Taylor’s career record stands at 501 wins, 594 losses, and 11 draws, good for an overall win rate of 45.3%. Those numbers don’t read like the typical “protected” star profile—and that’s exactly the point. Independent wrestling careers often function like ecosystems, not hierarchies. Wrestlers move between promotions, roles, and eras, sometimes as featured attractions and sometimes as the glue that holds cards together. Taylor’s statistical footprint suggests a performer who has spent significant time in competitive environments where outcomes are volatile, opponents are diverse, and the job is as much about delivering consistent performances as it is about stacking wins.
Even without confirmed hometown, birth information, or explicit “years active” metadata in the provided bio, the match count alone speaks to experience. A 1,106-match sample implies a career long enough to include multiple stylistic eras, changing audiences, and repeated reinventions—especially for a wrestler operating primarily in the independent sphere, where adaptation is often the difference between longevity and disappearance.
The most telling part of Taylor’s profile is that he’s not a statistical outlier in one direction—neither a dominant finisher nor a perpetual underdog by win rate. At 45.3%, he sits in the wide middle where many true independents live: credible enough to beat anyone on the right night, battle-tested enough to lose without losing value, and experienced enough to be placed anywhere on a card. In analytics terms, that’s not mediocrity—it’s utility, and utility is one of the most underrated currencies in wrestling.
The dataset provided does not include a classified wrestling style label or a list of signature moves, so MoneyLine Wrestling will not invent them. What can be analyzed, however, is how Taylor’s results profile behaves—because over a sample of 1,106 matches, a wrestler’s statistical tendencies often mirror the role they’re asked to play and the kind of matches they’re typically involved in.
Taylor’s overall 45.3% win rate is consistent with a wrestler who is frequently positioned in competitive matchups rather than squash-heavy booking. In many independent contexts, that usually correlates with a performer trusted to work with a wide range of opponents: veterans, prospects, specialists, and visiting names. The record itself—501–594–11—also suggests a career with plenty of close, high-variance outcomes. Draws are rare in modern wrestling data; Taylor has 11 of them, a small fraction of the whole, but notable in that it hints at match structures where time limits, non-finishes, or protected outcomes have been part of the toolkit.
Without move data, the most responsible “style analysis” is to interpret the competitive shape of Taylor’s career:
In other words: even with limited stylistic metadata, Taylor’s numbers describe a wrestler who has survived by being plug-and-play—capable of fitting into different match narratives, different opponent strengths, and different crowd expectations. That kind of adaptability is a style in itself, and it’s one of the reasons high-volume independents can remain relevant across multiple cycles.
Chuck Taylor’s career numbers are large enough to be meaningful—and that’s crucial. In analytics, sample size is everything. A wrestler with 30 matches can look like anything. A wrestler with 1,106 matches leaves a footprint.
Here’s the baseline:
A 45.3% win rate across more than a thousand matches indicates a career spent in legitimate competitive positioning rather than heavy protection. It also suggests Taylor has often been booked in roles where he can credibly win but is also trusted to take losses to elevate others or to maintain storyline direction. In independent wrestling, that’s a sign of reliability: promoters don’t repeatedly book wrestlers they can’t count on, and they don’t repeatedly put wrestlers in meaningful matches if they can’t deliver.
Taylor has 93 more losses than wins (594 losses vs. 501 wins). That differential matters, but it must be interpreted correctly. In a closed league, negative differential can signal low tier. In the independents, it can signal something else: a wrestler who is frequently matched “up” against higher-profile opponents, or a wrestler who is used to give credibility to emerging talent.
The 11 draws are also worth highlighting. Draws represent about 1.0% of Taylor’s total matches (11 out of 1,106). That’s small, but in modern booking patterns, draws are uncommon enough that their presence can imply Taylor has been part of match structures designed to protect both sides—time limits, contested finishes, or angle-driven outcomes. Over a long career, that’s a marker of being trusted in matches where the promotion wants something other than a clean win/loss.
MoneyLine’s advanced snapshot provides rolling win rates:
These are significant because they diverge sharply from the career baseline. Taylor’s career win rate is 45.3%, but his last 10 and last 20 are both 28.6%. That gap indicates a cooling period relative to his long-term norm.
It’s also notable that the last 5 rebounds to 40.0%, which is still below career average but materially better than the last 10/20. That suggests either (a) the most recent slice includes a couple of wins that improved the short window, or (b) Taylor’s results have been uneven—capable of short bursts but not sustained momentum in the broader recent set.
Because the dataset also lists “Recent Form (last 10): None,” MoneyLine won’t infer a match-by-match last-10 sequence beyond the explicitly provided recent match history. Still, the rolling percentages tell a clear story: Taylor’s recent period has been statistically tougher than his career average.
Head-to-head data is where a wrestler’s career becomes personal. Taylor’s top tracked opponents in this dataset paint a picture of both opportunity and friction—matchups where styles, roles, and timing matter as much as skill.
PAC is Taylor’s most significant head-to-head presence here by volume, and it’s been a rough one: 0–2. Two matches isn’t a massive sample, but it’s enough to establish a pattern: this has been a matchup where Taylor hasn’t found the winning formula.
From an analytics standpoint, this is the kind of opponent who can define a ceiling in a given era. When a wrestler repeatedly loses to a specific rival, it often signals one of two things: either the opponent is positioned above them in the hierarchy, or the story being told requires the wrestler to chase rather than conquer. The data doesn’t tell us which, but the outcome is the same—PAC has been a consistent roadblock.
The Trent Beretta result is especially interesting because it’s also Taylor’s most recent match in the provided history: 2024-04-25: loss vs Trent Beretta. With only one tracked meeting, it’s not a “rivalry” statistically, but it functions as a modern reference point: a fresh loss that shapes the immediate narrative around Taylor’s momentum.
In a sport where recency bias is real—both for fans and for booking—this is the kind of result that can frame Taylor as either a veteran being tested by peers or a competitor trying to reassert himself.
Taylor’s single tracked match with Kip Sabian is another loss. Individually, it’s just one data point. Collectively, alongside the PAC and Trent results, it reinforces the idea that Taylor’s recent notable matchups have leaned toward the wrong side of the ledger.
Same story: a one-match sample, another loss. What matters is the cluster. When multiple “notable opponents” are losses, it often indicates Taylor has been used in a role where he provides credibility to others—taking defeats without being diminished as a performer.
This is one of Taylor’s bright spots in the head-to-head set: a clean 1–0 record. In a data profile where losses dominate the highlighted opponents list, the JD Drake win stands out as proof that Taylor can still convert opportunities into victories, at least in certain matchups.
Taylor is also 1–0 against Lee Johnson in the tracked set. Again, single-match samples are fragile, but the takeaway is important: Taylor’s ceiling isn’t gone. He’s not locked into one outcome type. He can win, and he has won, even in the modern slice of the dataset.
Based strictly on the provided head-to-heads:
The broader implication is that Taylor’s outcomes have been sensitive to opponent positioning. Against certain names, he’s been slotted as the one who falls short; against others, he’s been allowed to assert control and get the result.
Taylor’s recent match history in the dataset spans from 2020 to 2024, with a handful of key results:
In those seven listed matches, Taylor is 2–5. That’s not a complete “last 10,” but it’s a meaningful recent snapshot: more losses than wins, and losses clustered around some of his highest-profile opponents in the head-to-head list.
The rolling rates reinforce the same direction:
A 28.6% win rate is a steep drop from 45.3% career. When both last-10 and last-20 align at the same percentage, it suggests the downturn hasn’t been a tiny blip—it’s been persistent across the broader recent window.
However, the last 5 win rate is 40.0%, which complicates the story. That number implies Taylor has had at least some recent success relative to the last-10/20 trend. In momentum terms, this looks less like a freefall and more like a wrestler trying to stabilize: the broader recent period is down, but the most recent slice shows signs of improvement.
Still, the most current single data point is a loss—2024-04-25 vs Trent Beretta—and in practical terms, that’s the result that shapes the immediate narrative. Taylor isn’t entering the next chapter off a signature win in this dataset; he’s entering it off a setback.
The PPV and TV splits in the provided data are stark:
Those numbers should not be misread as “Taylor can’t win on big stages.” They mean that within the dataset provided, there are no recorded PPV or TV wins for Taylor—and likely, based on the same dataset context, either (a) his tracked matches in those categories are minimal, or (b) the dataset’s PPV/TV labeling does not capture much of his independent work in those formats.
Analytics interpretation has to be careful here. A 0.0% rate can mean two very different things:
Because the underlying counts of PPV and TV matches are not provided, MoneyLine Wrestling will not assume which is true. What can be said is this: there is no statistical evidence in the provided splits that Taylor has translated his broader career volume into tracked PPV/TV success.
If Taylor is evaluated purely through the lens of this dataset, his “big-event” and “weekly TV” performance is a blank space—either because the sample is empty or because the outcomes have been unfavorable. Either way, it creates uncertainty, and uncertainty matters in predictive modeling.
MoneyLine Wrestling’s prediction lens starts with three pillars: baseline performance, opponent sensitivity, and momentum. Chuck Taylor’s dataset provides clear signals in all three—just not all positive.
Taylor’s career baseline is 45.3% across 1,106 matches. That’s a stable number because the sample is huge. Models tend to trust large-sample baselines more than small-sample spikes.
In practical terms, a 45.3% baseline suggests:
The strongest negative signal in Taylor’s profile is the recent trend:
That’s a meaningful deviation from 45.3%, and models treat sustained deviations as real until proven otherwise. Even with the last 5 at 40.0%, the broader recent sample is still poor enough to drag projections downward.
If MoneyLine were building a probability estimate for Taylor in an upcoming match, the model would likely apply a “recent form penalty” relative to his career baseline—especially if the opponent has stable or improving recent rates.
The head-to-head data suggests Taylor’s outcomes are highly sensitive to opponent profile:
Even with small samples, the directional message is consistent with a wrestler who can win in the right lane but struggles when matched against a particular ceiling opponent (PAC being the clearest example in this dataset).
In modeling terms, that implies Taylor’s win probability is likely to swing more dramatically based on opponent quality/positioning than it would for a more protected, more consistently booked wrestler.
With 0.0% PPV win rate and 0.0% TV win rate in the provided splits—and without match counts—Taylor carries a “context uncertainty” flag. Models dislike missingness because it reduces confidence. If an upcoming match is explicitly labeled as a TV or PPV environment, the model can’t point to proven success in those buckets from this dataset.
That doesn’t mean Taylor can’t perform there; it means the model has no evidence here that he does.
If Taylor is booked against an opponent with comparable baseline numbers and no strong recent momentum, his 45.3% career win rate keeps him in the fight—an underdog, but not a write-off. If he’s booked against an opponent with strong recent form or a history of “ceiling” positioning (as PAC appears in this dataset), Taylor’s projection would drop sharply, because the combination of head-to-head outcomes and recent win rates points to difficulty converting in higher-leverage matchups.
That’s the Chuck Taylor profile through the MoneyLine lens: a high-volume independent veteran with a massive career sample, a competitive but sub-.500 baseline (501–594–11), and a recent statistical downturn (28.6% over both the last 10 and last 20) that he’s trying to pull out of—one matchup at a time.
| Opponent | Matches | Wins | Losses | Draws | Win% |
|---|---|---|---|---|---|
| PAC | 2 | 0 | 2 | 0 | 0% |
| Kip Sabian | 1 | 0 | 1 | 0 | 0% |
| Blade | 1 | 0 | 1 | 0 | 0% |
| JD Drake | 1 | 1 | 0 | 0 | 100% |
| Lee Johnson | 1 | 1 | 0 | 0 | 100% |
| Trent Beretta | 1 | 0 | 1 | 0 | 0% |
| Date | Result | Opponent | Finish | Rating |
|---|---|---|---|---|
| 2024-04-25 | Loss | Trent Beretta | — | — |
| 2021-07-21 | Loss | PAC | — | — |
| 2021-06-26 | Loss | Blade | — | — |
| 2021-03-03 | Win | JD Drake | — | — |
| 2020-11-04 | Win | Lee Johnson | — | — |
| 2020-04-15 | Loss | Kip Sabian | — | — |
| 2020-03-04 | Loss | PAC | — | — |