You know that feeling when you see the perfect ball? You may not even see who the bowler is from the camera angle, but you see the ball, and it’s… beautiful and lethal and just. Like a song that hits the spot. It’s the physical manifestation of joy.
So when a bowler bowls such a ball, is that because they are in really good form, or is that just how they bowl in general? That has to be different for every bowler, right? And yes this is about bowlers because I just saw Mitch Starc bowl and the bowling. The bowling. Poetry.
This piece asks a rude question: If you took a bowler whose underlying ability wasn’t changing from match to match, and just let randomness do its thing, how often would you see those streaks anyway? Also, what does “form” mean for a fan watching from the outside, and what does it mean for the bowler inside the game?
Why is this about bowlers and not batters? When a batter scores runs, the runs are directly and unambiguously attributable to them. They chose the shot, they middled it or they didn’t, it went where they hit it or it didn’t. A batter who scores 80 runs scored 80 runs. The metric accumulates continuously across the innings- every ball is a data point, not just the ones that produce wickets. So in a single innings you might have 150-200 data points building toward the final score. That’s a meaningful sample size from one performance.
A bowler’s primary success metric- wickets- is a joint event. It requires the bowler to produce a good delivery AND the batter to fail to handle it. Even a perfect delivery can be survived if the batter gets a thick outside edge that falls short of slip. A rank bad ball can produce a wicket if the batter top-edges a slog. The wicket isn’t just measuring the bowler. It’s measuring the bowler plus the batter plus the fielding plus a slice of luck.
And wickets are rare. A good Test bowler might take one wicket every 40–60 balls on average.12 That means in a full spell you might have one, maybe two wickets to evaluate. That’s almost no data, and like I said above, the noise in a single wicket is enormous relative to the signal because it’s a joint event.
You might think economy rate solves this because it’s not as rare as wickets because it accumulates ball by ball like a batting score. But economy rate is contaminated by things the bowler doesn’t control: fielding (a misfield gives away four runs the bowler didn’t deserve), the batter’s attacking intent (a batter in T20 mode will score off good balls that a Test batter would defend), and conditions (a wet outfield makes everything travel faster to the boundary). A batter’s score is more directly their own than a bowler’s economy rate is their own.
A batter who scores a hundred has, by definition, not gotten out for the entire duration of that hundred. Getting out removes them from the sample. So a large batting score has a built-in quality filter because the batter proved they could handle everything thrown at them for that entire period. A bowler doesn’t have an equivalent filter- we’ve all seen instances of bowlers getting absolutely pounded, but also of bowlers just not bowling even when they are available because the captain doesn’t trust them. Also, batters can get out and end their performance, but a bad spell stays in the data rather than ending it.
Batting produces a continuous, accumulating, directly attributable metric with a survivorship filter. Bowling produces a rare, jointly caused metric with high per-event noise and no survivorship filter. They could have the same amount of underlying skill variation, but batting gives you better and more frequent measurements of it. So the signal-to-noise ratio is structurally worse for bowling than for batting, even before you account for the process/outcome problem with great balls going for four.
So there are two questions tangled up in that one perfect ball. One: how much does a bowler’s true underlying state actually move around over time? Two: given how noisy bowling outcomes are, how much of what we call a purple patch is just random clumps sitting on top of the former?
Streaks,Clumpsand Slumps Remember that time we kept losing coin tosses across formats, tournaments, venues and captains? If not, you can read more about it here and here. It was exasperating, but it is just something that happens naturally with numbers. In any long sequence of random outcomes, you will see streaks. Not because something changed, but because that’s just what randomness looks like. The longer the sequence, the longer the streaks you’d expect just from chance. Cricket careers are long sequences. Impressive-looking purple patches will appear in random data.
A signal is the meaningful, underlying information or pattern within a dataset that conveys useful information about a phenomenon.3 In statistics it is the meaningful information, true pattern, or underlying trend hidden within a data set. It is the “message” you are trying to find, separate from random irregularities, which is called noise, which is random, unwanted, and unpredictable fluctuations or variability in data that obscure the underlying signal or true pattern.4 Think of information vs. data, or someone singing under their breath in an otherwise busy room.
Any observed performance is a mixture of signal (the bowler’s actual underlying ability on that day) and noise (luck, conditions, batter quality, fielding, the specific random variation of where each ball lands). The question isn’t whether good performances cluster- they do. The question is whether the clustering is bigger than the noise would produce on its own. This requires knowing how much noise there is in cricket outcomes.
If real form exists, if something genuine changes in a bowler’s body or mind that persists across matches, then knowing how they bowled last match should help you predict how they’ll bowl this match. That’s called autocorrelation567: the extent to which a value in a sequence is correlated with the value before it. If form is real, you’d expect positive autocorrelation in performance sequences. If it’s just randomness, autocorrelation should hover near zero.
Also there is a caveat: even if real form exists as a statistical signal, most cricket careers may not be long enough to detect it reliably. A bowler might play 50 Tests. Each Test gives you a handful of spells at a maximum. Separating signal from noise in 50-100 data points, when each data point contains substantial outcome variance, requires a very strong signal.
Regression to the Mean Mean8 is a statistical word for average (sum all your data points, divide the sum by the number of data points, what we used to do in school). There’s a related concept that’s even more important for understanding how we perceive form, and it’s called regression to the mean(statistical phenomenon where extreme, unusual, or outlier measurements tend to be followed by measurements closer to the average9).
Extreme performances, either very good or very bad, are partly skill and partly luck. After an unusually good spell, the most likely next result is something closer to average. Not because form dropped, or because the bowler did anything differently, but because the extreme outcome reflected an unusually lucky combination of skill and chance variation, and that combination is unlikely to repeat in exactly the same manner.
This creates a specific perceptual trap: Imagine a bowler takes wickets in four consecutive matches. Everyone says they’re in form. The next match is average. Everyone says they’ve lost their rhythm. What actually happened is: the four good matches were skill plus good luck, and the average match was skill without particularly good luck. The average is always more representative.
What looks like form peaking and then fading is often just an extreme performances being followed by more typical ones, because that’s how averages work.
Hot Hands In 1985, three psychologists, Gilovich, Vallone, and Tversky, published a paper about basketball players.10 They tested whether a player who had made several consecutive shots was actually more likely to make the next one, as coaches, players, and fans universally believed. The answer was no. When they applied proper statistical tests to shooting data, the streaks that looked like “hot hands” were completely consistent with what you’d expect from random sequences. The hot hand was, they concluded, a cognitive illusion- the human brain is extraordinarily good at finding patterns and just terrible at recognising what randomness looks like.
Then, in 2018, two researchers named Miller and Sanjurjo found a problem with it.11 There’s a subtle mathematical bias that appears when you look for streaks within short sequences — the way the original paper sampled the data produced an underestimate of the true streak effect. When they corrected for it, a small but real hot hand effect appeared in the data. Not large, not the dramatic momentum that commentators describe, but statistically detectable.
So: the hot hand probably exists a little, but there is probably a difference between what it means for the bowler themself (internal), the fan (external), and the statistician (mathematical).
Has this been tested in cricket?
A study titled Significant hot hand effect in the game of cricket specifically looked at ODI and Test performances.12 Unlike the basketball study, which found outcomes were independent, this research used self-exciting point processes (a fancy way of saying “success increases the probability of immediate future success”, I don’t know why researchers talk like this, it’s so annoying) and found:
Predictability exists: In both ODIs and Tests, individual performance sequences showed more clustering than random chance would allow.
The “60% Rule”: The researchers found that models accounting for the hot hand outperformed random-null models(a simplified, randomized version of real data used to test if observed patterns are due to chance. It keeps some data structure fixed (like totals) but randomises others to create a “baseline” for comparison) about 60-62% of the time, which is statistically significant(this means that the outcome is unlikely to have occurred by chance alone13).
Real vs. Casual A famous Yale study14 on bowling (ten-pin bowling, that is) data found something similar: the hot hand is real but not causal. One strike doesn’t magically cause the next; instead, players go through high‑ and low‑performance states where every ball in that window is a bit more or less likely to work.
So, a player isn’t “hot” because they just took a wicket; they are “hot” because they are currently in a high-performance state where the probability of a wicket is higher for every ball in that window.
What Does “Normal” Look Like for This Bowler? Here’s the idea: pick a bowler, and choose a stretch of their career where they feel like roughly the same player- same role, same format, similar fitness, no huge technical overhauls, then take the average of all their performance numbers. The result, is what you’d expect from this bowler on a typical day in this phase of their career, which means it is the baseline- the normal level of this bowler in the period you care about.
Why does version control(called non-stationarity in statistics15) matter? Because different versions of the same person should not be put in the same streak of matches, because an early Mitch Starc and present day Mitch Starc are completely different bowlers. So they produce maybe the same looking ball, but the process and consistency must be completely different (maybe, I think), and in that way that is a different ball altogether.
And also, as with any average, the larger the sample size, the more representative it will be of the next ball that will be bowled.16 This is why we want a reasonable sample, so please think dozens of matches, not 3-4.
Now we want to know, game by game, whether the bowler was better than their own usual level or not, and because we know this, we can find out for each match how much they deviated from this average. This is straightforward subtraction- if the Average is A, and the new data point (the performance from the current match) is B, then if:
A>B, the bowler didn’t bowl as well as the recent most applicable average,
A<B, the bowler bowled better than the recent most applicable average, and
A=B, the bowler bowled as well as the recent most applicable average.
We can take this as:
A>B as a score of -1,
A<B as a score of +1, and
A=B as a score of 0- that is, they are bowling on average neither better nor worse than the current average.
So,
+1 = better than usual
0 = roughly normal
−1 = worse
Which means that over ten matches one might see: +1,0,−1,+1,+1,0,+1,−1,+1,+1. That’s a crude form diary for this bowler in this phase of their career.
What randomness actually looks like Imagine a bowler whose underlying ability is completely fixed- same skill, same fitness, same everything, match after match. No slumps, no golden periods, no form at all. Just a consistent underlying level of performance with some random variation in outcomes from match to match, because cricket is not a controlled experiment and outcomes are noisy.
Now watch that bowler for fifty matches.
You will see streaks. Strings of matches above their average. Strings below. At some point you will see five good matches in a row and think: they’re in form. At some point you will see four mediocre matches and think: they’ve lost it. Neither conclusion would be correct. You’d be reading patterns into randomness.
In statistics, this is called a ‘run’. A statistical run is a streak of similar outcomes17, so above average, above average, above average is a run of three. The Runs Test18 asks: given this sequence of above-and-below-average performances, does the pattern of runs look like what you’d expect from pure randomness, or is there more clustering (or more alternating) than chance would produce? You don’t need the formula. The logic is: count the runs, compare to the expected number if the sequence were random, and ask whether the difference is bigger than chance alone would explain.
But to know what is above average, first we need to know what is average for that bowler.
The Poetry is the Signal So, is a bowler who scores +1,0,−1,+1,+1,0,+1,−1,+1,+1 in good form or average form?
As far as I can see, there are three types of form in cricket bowling:
Type 1: Physical/biomechanical state: The bowler’s body is working or it isn’t. Rhythm, run-up, shoulder position, wrist at release. This is internal and real and the bowler feels it immediately. A niggle, a slight change in action, fatigue, just their mental state, these affect the actual delivery. This is the closest thing to true form.
Type 2: Outcome form: What the scorebook says. Wickets, economy, match figures. This is what fans and selectors see. It’s a noisy, delayed, jointly-caused signal that reflects Type 1 form plus batter quality plus fielding plus luck. It can diverge wildly from Type 1- a bowler can be in beautiful physical form and get hammered because the batters are brilliant that week, or be slightly off and take a five-for because edges keep flying to hand.
Type 3: Perceived form: What fans, commentators, and sometimes selectors believe based on Type 2. Subject to all the cognitive biases described- hot hand illusion, regression to the mean misread as form loss, pattern-finding in noise.
But bowlers are not coin tosses. People are not numbers, so bowlers remember the last ball, they feel their front leg blocking well or not, they sense whether the seam is landing upright, they know if their shoulder is sore. Those things change the underlying probability of a good ball in a way no simple random model can capture.
The hot‑hand studies in other sports end up in a similar place: they find real fluctuations in a player’s underlying performance level over time, but very little of it is the magical one-success-causes-the-next momentum commentators seem to love.
So,
Individual bowlers do have better and worse phases. There is some persistence in performance beyond pure randomness.
But bowling outcomes (wickets, runs) are so noisy and so joint that even a completely flat bowler would eventually generate streaks that look like form.
The “hot hand” we see on TV, such as wickets in clumps, commentators rhapsodising, is mostly our brain misreading random clumps as deep narrative, with a thin layer of real underlying changes.
For the bowler inside the game, “form” probably means something more process‑y: how their body and action feel, whether they can hit the length in their head, whether their corrections are working. The scorecard is a crude, laggy, sometimes unfair reflection of that.
The “Signal” isn’t the wicket. The wicket is the Outcome, and the Outcome is noisy, messy, and shared with ten other people. The “Signal” is that feeling I had watching Starc bowl. It’s the Process– the perfect snap of the wrist, the late tail of the ball, and only then, sometimes, the sound of the stumps.
This post is inspired by Indian Men’s Test Cricket Captain Shubman Gill, who’s suffered three separate head/ neck injuries in 36 days, as well as my friend Sanchita who asked how can such injuries be reduced when I posted about the Skip’s poor run of luck.
Before we proceed, I understand this post has turned into a bit of a book, so here’s a list of sections as well as what they talk about in a line. Feel free to jump to whichever section you wish to read:
A primer on these injuries: explanations of head/ neck injuries
Concussion vs non-concussive impacts: a discussion on injuries that result in a concussion and those that don’t, and their impacts on athletes.
Feeling all wrong in the head: The psychological impacts of getting hit in the head/ neck/ face.
Cumulative trauma and CTE: More about the cumulative load of multiple head hits over the course of a life.
ICC’s concussion guidelines: self explanatory.
Workload management: a discussion of workload management in cricket and why its an important part of this discussion
A bit about helmet design: about cricket helmets.
The technology cricket isn’t using: available helmet technology we could be using but are choosing not to.
Risk Compensation: Humans take more risks if they have more protection.
So what to do?: My solutions.
In conclusion: …the, you know, conclusion to the post.
Appendix 1: No surprises: ACWR calculations for Gill with lots and lots of assumptions and no actual data
Appendix 2:Comparison table between helmets used in F1, NFL, and international cricket: You know… a tabular comparison between helmets used in F1, NFL, and international cricket.
Now back to Shubman, who was injured in three different ways:
10 October 2025, he collided with West Indies keeper Tevin Imlach.12
31 October 2025, he was struck on his helmet by a Josh Hazlewood snorter that seemed to ricochet off his bat.34 This was also immediately after both teams observed a moment of silence for the death of 17 year old Ben Austin after he was struck in the neck while practicing,56 and I wonder what effect that had.
15 November 2025, he suffered a neck spasm (?- I don’t know what the actual diagnosis is, this is just what the media is calling this injury) seemingly due to hitting the ball with great force.78
Gill’s extraordinarily rancid luck has given him a near-complete collection of cricket’s head and neck injury mechanisms—while mercifully leaving him alive and able to walk. With him possibly out of the upcoming second Test in Guwahati, I began wondering: are there ways to prevent these incidents, or at least reduce their impact?
Let’s look at the systemic issues that makes so many cricketers prone to these injuries.
A primer on these injuries A head and/or neck injury can result in a wide spectrum of medical consequences—ranging from mild, temporary symptoms to life-threatening or permanently disabling outcomes. Here’s a table:
Major blow/ trauma to neck, severe vertebral fracture, direct ball impact
Partial or complete paralysis, loss of sensation, loss of bladder/bowel control, breathing problems
Vertebral Artery Dissection (a tear in the wall of the vertebral artery in the neck, which can lead to a blood clot that disrupts blood flow to the brain)1819
Ball impact to neck, rotation injury (rare, catastrophic, eg. Phil Hughes)
Stroke symptoms: weakness, speech difficulty, visual loss; can cause fatal brain bleed (subarachnoid)
Lacerations (tears/ cuts on the skin) & Contusions (a bruise where blood vessels are damaged, causing bleeding under the skin without an open wound)2021
Ball, bat, or ground strike to head, neck or face
Pain, swelling, bleeding, bruising; can mask deeper fracture or brain injury; risk of infection
Concentration, memory deficits, fear of fast bowling, nightmares, performance decline, depression, anxiety
Concussion vs non-concussive impacts A study of elite Australian cricketers over 12 seasons recorded 199 traumatic head and neck injury events, with the incidence increasing to 7.3 per 100 players after helmet regulations were introduced in 2016.262728 Contusions were the most common injury type (41%), with the face being the most frequently injured location (63%), followed by the neck (22%) and skull (15%).262728 Victorian hospitals alone treated 3,907 head, neck, and facial cricket injuries over a decade, with a notable increase from 367 to 435 cases during the 2014/15 season.262728 The burden extends beyond elite cricket. Hospital admission data shows an incidence of 1.2 head and neck injuries requiring hospitalization per 1,000 participants across all participation levels.262728 Males experience significantly higher injury rates (1.3 per 1,000 participants) compared to females (0.4 per 1,000), with the 10-14 age group being the most frequently hospitalized.27
Evidence suggests that batters who suffered helmet strikes without diagnosed concussion experienced significant batting performance decline for up to 3 months, and that performance dropped from +0.24 standard deviations above average to -0.24 below average—a total decline of approximately 0.48 standard deviations, a statistically meaningful performance decline.293031 (DON’T PANIC HERE’S AN ILLUSTRATIVE EXAMPLE WITH MADE UP NUMBERS: This means there might be a reasonable chance, let’s say around 30–40%, that a player who usually averages 50 could instead average something like 42–45 for the next few innings, not because their skill disappeared, but because the non-concussive head impact can affect timing, confidence, decision-making, and overall performance.)
Further, research using computerised cognitive testing on concussed cricketers shows:38
Detection speed (recognising a stimulus) slows by 27 milliseconds
Identification speed (processing what you see) slows by 49 milliseconds
Working memory (holding information while making decisions) slows by 53 milliseconds
No one familiar with cricket needs any explanation about what this means for elite cricketers facing a hard cork ball coming in at 140 kmph: on lucky days it can be the difference between middling the ball or edging to slip. On a bad day it can mean a dead cricketer.
Paradoxically, concussed players showed no significant performance decline, perhaps because they received structured return-to-play protocols, possibly with psychological support.29
This is just more evidence that the sport does not take head/ neck injuries seriously enough: unless it is a concussion, it’s nothing. Compare this to any other physical injury- a sprained ankle receives appropriate treatment, just like a broken one, yet unless there is a proven concussion, it is either seemingly assumed no injury has taken place at all, or it requires no further support. Are we surprised? After all, the box was invented and widely used long before helmets were.3233 Given the documented primate instinct to protect our heads above all else during danger,34 it’s no wonder that when we fail at this, such as when a ball strikes us in the noggin despite our best efforts, the psychological consequences can be severe and lasting.
Feeling all wrong in the head Following his 2014 facial fracture from Varun Aaron’s bouncer, Broad suffered ongoing nightmares and flashbacks for months, even during sleep deprivation.35 His jaw clicked involuntarily, and he saw balls flying at his face in the middle of the night, a form of post-traumatic stress that affected his batting technique for years afterward.35 His confidence was “knocked big time,” and his post-injury batting statistics show measurable decline, particularly his reluctance to play front-foot drives, as he now camps perpetually on the back foot anticipating short balls.3536
Broad’s quality of life went down significantly due to this injury and there’s no knowing if he’ll ever quite be free of this particular demon. Who knows when it might come knocking at his mental doors again? Why does it matter- well, it matters because he’s a person and we don’t want him to be unwell. It also matters because it shows something cricket rarely acknowledges: psychological injuries are also performance injuries.
Cumulative trauma and CTE24 Critically, research increasingly shows it’s not just diagnosed concussions that matter—repeated subconcussive impacts (hits that don’t cause immediate symptoms) carry serious long-term risks. Research on chronic traumatic encephalopathy (CTE, a brain disease that is thought to be caused by repeated head injuries) associates with repetitive head impacts over years that trigger neurodegenerative disease. The CDC’s guidance on traumatic brain injury emphasises that repeated head impacts can produce brain changes detectable on neuroimaging even without concussion symptoms. Studies tracking athletes show that the number of years exposed to contact sports—not the number of diagnosed concussions—most strongly predicts brain pathology severity. To really understand what this means, here is what CTE manifests as: progressive memory loss, mood disturbances, aggression, dementia, and in approximately 45% of CTE cases, full dementia develops. Approximately 66% of CTE patients over age 60 develop dementia, and the number of years of exposure to contact sports (not the number of concussions) is significantly associated with severity.
This means every helmet strike suffered matters. Every bouncer that rattles a helmet. Every collision. Every seemingly “minor” blow that is waved off, often enough by the players themselves. These accumulate over years and decades, potentially causing permanent brain changes long before symptoms appear. And let me tell you something macabre: CTE can only be definitively diagnosed post-mortem.37
All this brings us back to Shubman and a very obvious cricketing: rest. Gill has played an almost uninterrupted international schedule, often under immense leadership pressure. Because better rest means better recovery, it’s not difficult to wonder whether Gill’s ICU trip could have been prevented had his workload and injuries been managed better.
Workload management Sleep restriction has been definitively demonstrated to negatively impact attention and reaction time.39 In cricket, batters and fielders with sleep disturbances or excessive match load develop more muscle strains and are more likely to suffer slips, misfields, or head impacts, while fast bowlers with insufficient rest between spells or days have higher rates of stress fractures, shoulder injuries, and muscle tears.
Research shows that reaction times slow by 26-215 milliseconds (depending on the individual) after concussion injuries. Critically, even athletes cleared for return-to-sport still demonstrate reaction time deficits compared to healthy controls, meaning their brains haven’t fully recovered despite being medically cleared.404142
In cricket, unlike many sports, everyone must be batting-ready—even bowlers and lower-order players face 90-mph deliveries with potentially milliseconds to react. When fast bowlers complete bowling spells without adequate recovery, their neuromuscular function is compromised for up to 24 hours (This means their muscles don’t fire as well, coordination is compromised, and they become more prone to awkward movements that cause injuries. Studies using countermovement jump testing (a standard assessment of neuromuscular readiness) show measurable declines lasting a full day after intense bowling.43
But as previously mentioned, exhaustion leads to lower reaction times, because sleep deprivation and cognitive fatigue directly impair neural processing speed:4445 so, a cricket ball traveling at 90 mph and reaches the batter in approximately 400-500 milliseconds, which is the total available response time to any batter. A 26-millisecond slowdown in reaction time means that the batter now has 5-6% less available time to respond (that is, because sleep deprivation and cognitive fatigue directly impair neural processing speed, a 26-millisecond slowdown in reaction time means the batter has 5–6% less time to respond.).46 For a fatigued player this could easily be the difference between playing the ball and getting hit.
Sudden workload spikes add to general fatigue issues. Sports scientists measure this through a metric called Acute:Chronic Workload Ratio (ACWR), and it is used to predict injury risk. It’s calculated in the following way:4748
Acute workload = work done in the past 7 days
Chronic workload = average work over the past 4 weeks
ACWR = acute divided by chronic
Research shows that when ACWR exceeds 1.5 (meaning you’re doing 50% more work this week than your 4-week average), injury risk spikes dramatically. Above 2.0, players face 5-8 times greater injury risk. Professional teams using GPS tracking to monitor ACWR have reduced injury rates significantly—yet this technology remains underutilis
ed, particularly at international level where scheduling pressures often override medical best practices.
ICC’s concussion guidelines4950 The International Cricket Council (ICC) mandates structured on-field assessment (SCAT6) at match breaks, end of play, and at 24 and 48-hour intervals. Players diagnosed with concussion must be immediately removed and cannot return the same day. Return-to-play protocols typically take at least 7 days and include: 24 hours relative rest, light aerobic exercise, light training, and progressively returning to full participation—but junior players (under 18) must wait a minimum of 14 days after symptom clearance before competitive play.
In June 2025, the ICC introduced a mandatory minimum seven-day stand-down for any player diagnosed with a concussion,51 and teams must now nominate designated concussion replacements before a match52.
The ICC has also set specific standards that all approved helmets must meet. These are (BS 7928:2013 + A1:2019 standard, which includes tests for neck protectors):5354
Faceguard penetration testing at realistic ball impact speeds
Testing against both men’s (5.5 ounce) and junior (4.75 ounce) cricket balls
Neck protector impact testing specifically designed to reduce basal skull and neck injuries
Also, currently the Marylebone Cricket Club (MCC, the body that makes laws for cricket) has concluded after that law changes are not necessary, instead emphasising umpire discretion under Law 41.6, which allows umpires to call dangerous short-pitched deliveries as no-balls if bowlers exceed shoulder height or if the batter lacks skill to face them safely.5556 One would imagine this would cover all scenarios, however, we know this is not the case.
A bit about helmet design Cricket helmets need to meet three competing requirements: protection, visibility, and weight. An improvement in one area is likely to compromise the other two.
When a batter walks out to face 140 kmph bowling, what they need most is clarity. They need to see the ball early and track it right out of the bowler’s hand. That means the helmet can’t be too big, too heavy, too bulky, or too close around the eyes. At the same time, protection demands more coverage, especially around vulnerable areas like the jaw hinge and lower skull. And then there’s weight: add too much carbon fibre or too thick a liner, and the helmet becomes a neck injury waiting to happen, not to mention general discomfort and possibly compromising the athlete’s ability to move their head.
We also have evidence of serious blind spots in helmet design: before Phil Hughes passed in 2014, no major manufacturer seriously considered that the most catastrophic head injury in cricket might come from below the helmet and behind the ear, simply because nothing of the sort had been recorded before. It took Hughes’ fatality for the entire cricket world to realise how vulnerable that area actually was-5758 something any trainee doctor is likely to know. Suddenly, manufacturers scrambled to create neck guards, which remain optional to this day. I shudder to think whose blood is going to buy us the next development in helmet technology.
A hard outer shell of ABS, fibreglass, or carbon fibre
A foam liner, usually EPS or multi-density foam
A steel or titanium grill
Padding around the jaw and chin
They perform very well against linear acceleration (straight-line impacts), but many of the worst brain injuries come from rotational acceleration,6162 when the head violently twists rather than just moves backward: traditional helmets aren’t great at stopping such injuries, and current testing standards often don’t measure it.636465 By the way, learning this has made me genuinely grateful that Gill walked away from his third injury.
To recount, at the moment, the ICC requires helmet’s to be tested for whether the ball can penetrate the grill, peak velocity impacts, protection against both senior and junior cricket balls, and for neck guard impacts.54
What we’re missing: tests for rotational concussion risk, no requirement for repeat-impact safety (a helmet can pass the test once and still weaken after a few blows), and there is no measurement system or guideline that helps medics determine how long a player should be out of the game in case of non-concussive injuries. Or even repeat non-concussive traumas that happen within a short timeframe like Gill’s.
The technology cricket isn’t using66676869707172 In American football, ice hockey, and even rugby, athletes now routinely wear helmets or mouthguards that contain:
accelerometers
gyroscopes
rotational-force sensors
radio transmitters to send impact data to support staff
The moment an athlete suffers a dangerous hit, medical personnel get an alert. There’s no argument, no debate, no “I feel fine, I’ll carry on.”
Cricket could have this tomorrow if our administrators took this issue seriously enough. The technology is cheap, lightweight, and has already been validated in other sports.
A smart cricket helmet could tell the physio: this was a 75g impact with significant rotational acceleration. Used in combination with a standardised medical guideline from the ICC, that player could be removed immediately and rested for as long as required. And maybe if this happens, there may be a cultural shift where we wouldn’t need a Ravindra Jadeja falling about being dizzy during an innings break, and then have the team management answer batshit questions about whether the substitute was a like-for-like replacement.7374
There are also exciting innovations happening which don’t involve adding meters to the helmet, such as 3D-printed lattice structures which deform in controlled ways to absorb and dissipate energy more efficiently than traditional foam (they’re already used in some of the safest American football helmets)757677and multi-impact liners, which maintain their protective performance across several blows7879.
I’ve done a tabular comparison of existing international cricket helmets with those used in F1 races and NFL matches in Appendix 2, if you want to scroll down.
Risk Compensation I just want to note a human tendency that has been verified by research: the safer we feel, the more risk we take. It has been demonstrated repeatedly:
Ice hockey players hit harder when facial cages are added83
American football players tackle more aggressively with better padding8485
There’s no clear, modern (2020s) empirical study linking helmet use leads to increased aggressive shot-making or riskier batting in cricket, but humans are humans, and so hopefully any future studies about the use and usefulness of protective gear in cricket will take this into account.
So what to do? Here are my suggestions as a non-medically trained fan:
A. Medical Safety Protocols
Collaboration between ICC and doctors who specialise in cranial trauma, neck injuries, etc. (whether concussive or not), and sports medicine specialists from other sports with more advanced athlete support for such injuries to study and understand all such injuries better and release recommendations that are either endorsed or updated annually as required.
An athlete who has suffered two head/neck injuries within the space of 30 days (or whatever number medical professionals agree on) should automatically be placed on a two-week mandatory medical rest.
A full set of medical tests and scans at a hospital (not just by the team physio) after every head/neck injury.
Actual regular sports medicine assessments, not just after injuries occur.
Independent medical oversight that is not influenced by team selection pressures (either from the team or the athlete themselves).
MANDATORY MENTAL HEALTH SUPPORT for any injured players, and also for those returning from these kinds of injuries.
B. Monitoring & Injury Tracking
Mandatory biomechanical screening to identify high-risk movement patterns for each athlete.
Career-long injury tracking to identify cumulative trauma patterns and to strengthen vulnerable areas before injuries happen.
Smart helmet or wearable impact monitoring to quantify dangerous blows and guide medical care.
C. Workload Management
Workload management for all cricketers, no matter how important they seem to be for a particular team or cricket ecosystem.
The use of ACWR and/ or other sports science metrics to identify and prevent dangerous spikes in workload.
D. Technical & Skill Interventions
Mandatory bouncer-playing classes for all cricketers. If bouncers are part of the game and cannot be curbed, we need to teach every cricketer how to play them. ICC can standardise these educational modules.
Annual board audits checking whether cricketers have received from each board have received these lessons.
Active field awareness training so players stop colliding. Collisions are so preventable.
E. Equipment, Technology & Design
Using all technology available for helmets that actively prevents ball-hit injuries.
Adoption of advanced materials (3D lattice structures, multi-density liners) to reduce both linear and rotational impact forces.
Exploring mandatory neck guards, redesigned to address current comfort and visibility issues.
F. Cultural Redo
A cultural shift that doesn’t look at injuries as weaknesses.
The cricketing ecosystem needs to stop simply mourning dead cricketers and start actively preventing these deaths.
Stop treating head and neck injuries as “part of cricket.” They’re not inevitable; they’re preventable.
In conclusion As a cricket fan, I’ve admired the several instances of cricketers putting their bodies on the line for … for what? A match? Rishabh Pant batting with a broken foot, Anil Kumble bowling with a broken jaw, Chris Woakes batting with whatever was going on with his shoulder, Cheteshwar Pujara wearing balls, Greame Smith walking out to bat with a broken hand, Phil Hughes dying. All these have something in common: cricket valorises suffering. We celebrate wounded heroes, but never ask why they had to be wounded in the first place.
Our dead: An incomplete list of cricketers dead due to head/ neck trauma. Truly, shame on us.
Cricket is a sport. It’s my favourite sport. It’s a wonderful, beautiful, demanding, meaningful sport. But it is still just a sport. Cricketers are human beings with futures, families, and brains that deserve protection. The solutions exist. The research is clear. The deaths are preventable. And it is well past time we started preventing these unnecessary deaths instead of mourning them.
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Appendices
Appendix 1: No surprises I don’t have access to Gill’s workload or any personal statistics, but I wanted to understand how correct my instincts were about my hypothesis regarding these three recent injuries and his workload. I’ve made some assumptions, and take everything with a healthy spoonful of salt, but here are my calculations.
I’ve used the following research-established numbers:90919293
ACWR Range
Risk Category
Injury Risk Multiplier
< 0.80
Undertrained
Moderate (fitness declining)
0.80–1.30
Optimal
Lowest injury risk
1.30–1.50
Elevated Risk
1.5–2× baseline risk
1.50–2.00
High Risk
3–5× baseline risk
> 2.00
Danger Zone
5–8× baseline risk
My assumption is that 1 hour of active cricket = 1 workload unit. This leads to the following table:
The weekly ACWR analysis (bold typography used for each of the injuries):
Week Starting
Activity
Acute Workload (7 day period in hours)
Chronic Workload (28-day avg. in hours/ week)
ACWR
Risk Zone
Jan 22
England T20/ODI start
16 hours (2 T20s + 1 ODI)
14 hours/ week baseline
1.14
Optimal
Apr 1
IPL mid-season
8 hours (2 T20s)
8.6 hours/ week
0.93
Optimal
Jun 1
Pre-England Tests
4 hours (1 T20)
8 hours/ week
0.50
Undertrained
Jun 20
England Test 1
35 hours (5-day Test)
14.5 hours/ week
2.41
Danger Zone
Jul 2
England Test 2
35 hours
22 hours/ week
1.59
High Risk
Sep 25
Pre-WI Tests
0 hours (rest)
12 hours/ week
0
Recovery
Oct 2-8
WI Test 1
35 hours
17.5 hours/ week
2.00
Danger Zone
Oct 10-16
WI Test 2 (injured)
21 hours (retired Day 3)
19 hours / week
1.10
Moderate
Oct 19-25
Australia ODIs
16 hours (2 ODIs)
28 hours/ week
0.57
Undertrained
Oct 26-Nov 1
Australia T20s
12 hours(3 T20s)
26 hours/ week
0.46
Severely Undertrained
Nov 9-15
Travel/prep
~7 hours (assuming light training)
21 hours / week
0.33
Undertrained
Nov 14-20
SA Test 1
35 hours
21 hours/ week
1.67
High Risk
Gill’s ACWR analysis
Now, make of the above whatever you will. Correlation is not causation and the ball-hit injury happened after a rest period so that injury doesn’t fit the ACWR model. However, given the above, I’m not sure I’d dismiss the injury-pattern as as just very poor luck: while ACWR may not fully explain all three injuries, the cumulative fatigue coupled with inadequate recovery protocols do seem to create demonstrable vulnerability.
The point isn’t that ACWR perfectly predicts all three injuries. It doesn’t. As a model it predicts risk of something happening rather than saying with surety that it will happen. However, perhaps it can tell us something about the impact of inadequate recovery windows, format transitions, and cumulative load overlapping issues that increase injury susceptibility, especially when combined with psychological stress from captaincy and the normal stochasticity of playing cricket at 140 kmph.
Appendix 2: Comparison table between helmets used in F1, NFL, and international cricket
Here’s a comparison between helmets used by F1 racers, elite American Football athletes, and international cricketers (I’ve used bold typography for features I think cricket helmets should have, and couldn’t find verifiable data for helmet weights):
Toughest shell. Built to survive high-speed crashes, resists hits from all angles and projectiles. Added ballistic strip on visor for extra protection.
Cutting-edge impact protection. Designed to absorb hits from all directions; includes special padding to prevent concussions and uses smart sensors.
Protects against fast balls and bouncers. Hard shell and grille stop balls entering; strong for head-on hits, but less effective for twisting injuries.
Visibility
Maximum: very wide visor, minimal distortion, designed for 180° vision at 300 km/h.
Wide and high field of view. Thin facebars ensure players see clearly, important for catching and dodging tackles.
High: grille and shell designed to allow batters to see the bowler and ball clearly, but some guard designs can slightly obstruct vision above/below.
Special Features
Fire-resistant, radio setup, multiple visor options for sunlight.
Smart sensors detect hard hits, customisable fit, extra light facemasks (titanium options).
Removable padding, neck guards added after recent fatalities, optional extra light titanium grille for better comfort.
Crash/Impact Testing
Most rigorous: tested for hits from race wrecks, flying debris. Top global safety standards.
Lab-tested for head injuries, including concussion risk—best for rotational/twisting impacts.
Tested for direct ball impacts, facial and neck injuries; not formally tested for twisting/rotational impacts yet.
Overall
Most protective helmet in any sport, a bit heavier but unbeatable for safety.
Best for head impacts and preventing concussions in team sports.Tech is advancing fast.
Lightest, adequate for direct hits, but not yet matching F1/NFL for twisting impact safety.
Comparison table between helmets used in F1, NFL, and international cricket
I’m not suggesting just using a helmet from another sport. I’m saying we can make our helmets much better right now if we wanted to.
I cannot believe I’ve put in appendices for a goddamn blog post.
Sources (I’ve removed the duplicates so there are fewer links than the numbered links above)
Cricket is a statistically oriented sport. Cricket fans are used to scrolling pages of statistics for their teams and players they wish to know more about. And yet, we don’t have reliable metrics for measuring and comparing fielding performances.
Fans know, of course, when we see a cohesive fielding performance, such as New Zealand’s against Pakistan during the inaugural Champions Trophy match in Karachi on Wednesday, 19 February 2025. We also know a sloppy one, such as India’s against Bangladesh the next day in Dubai. Greatness is always visible in the doing on a cricket field.
We fantasise about taking that perfect flying catch, or executing a a sharp run out when we play, but we still do not have a universally accepted set of metrics to really understand what a “perfect” catch is, or what makes a run out “sharp”. For a sport that’s managed to tame the nebulous Leg before Wicket dismissal into four measurable criteria (including the umpire’s decision), it sure is confusing why fielding continues to confound us so. Especially when cricket fans value it so.
I’ve wondered what it would take to build parametres that measured fielding performance, and asked different cricket writers about how they would go about it too. At the moment I think such a measurement must include the following:
1. Define the deconstructed components of fielding
What are the parts that make the whole for fielding in cricket? I think we can break them down to getting in position, including speed and ball awareness; catching; throwing, with throwing itself divided into speed and accuracy; and field awareness.
2. Decide how we value different types of catching
Is slip catching the same as catching at point? Are they equivalent to a boundary catch? What about wicket keeping catches, with those padded cymbals for hands? And what happens when fields tag team a catch?
3. Scoring
Each fielder may be rated on the above, that is, scores for emplacement, for catching, and for throwing. Additionally, points can be deducted for errors and added for faultless execution, gymnastics-style.
Now for expanding upon the four criteria I mentioned in the first point above.
1. Emplacement- How a fielder gets into position.
a. Ball Awareness
A lack of ball awareness is most often evidenced in whether or not fielders are backing throws up. Overthrows are annoying, and often damaging. Dropped catches are also often about active attention, since players who expect the ball to come to them are also ready to field it, and ball awareness will allow us to gauge how attentive a player usually is.
b. Speed
Cricket already measures the amount of time a fielder had to react to an incoming catch, and we can certainly measure the distance the fielder is standing from the batter. Therefore, as middle school maths taught us, Speed = Distance/ Time. This will capture a fielder’s fitness and running ability, as well as their reaction time.
2. Catching- Self explanatory
Off the top of my head, I can count eight types of catches
i. Tag-Teamed Catches- When two or more fielders are involved in completing the same catch. Here players must be especially aware of each other and cognizant of throwing the ball before they drop it, or braced to catch one coming at an odd angle from the first catcher. I believe points should be assigned to all the involved fielders.
ii. Boundary Catches- Catches pouched so close to the boundary that the fielder must be aware of the ropes/ cushions.
iii. Outfield Catches- Catches outside the 30 yard circle, but before the ball reaches the boundary fielders. It may involve either infielders or boundary fielders running to the catch.
iv. Infield Catches- Catches at or within the 30 yard circle that do not include the ones detailed below.
v. Slip Catches- You know the ones.
vi. Keeper Catches- This is interesting because keepers have such a unique job. Of course they have the advantage of padding, but they often have to catch blind, and when diving can easily end up in front of first slip. They also must actively read the ball while it is being delivered, just like the batter.
vii. Close Catches- Any variation on Silly Point, Silly Mid Off, Silly Mid On, and Forward Short Leg.
viii. Caught and Bowled- When the bowler catches the ball during or soon after their follow through.
3. Throwing- collecting and getting the ball back to the pitch.
Throw Speed- easily measured.
Throw Accuracy- also easily measured.
4. Field Awareness
Poor calling is exasperating to watch and dangerous for the fielders themselves, and fielders need to be aware of which end of the pitch they should throw to.
So how will the scoring happen?
One way to do it is simply begin each match at zero for each fielder, and add points as they field, or misfield, as the numerator, and the number of opportunity they had to field as the denominator. Each act of fielding can have a predetermined value, and at the end of the match, I propose we bring all the scores down to a scale of 10.
A decision must be taken about whether each day in test cricket is rated separately, or whether performances are rated by innings, since both bring forth interesting insights into how different fielders manage sessions, innings, and days. A fifth continuous session of fielding is sure to differ from the first session in both execution, strategy, and energy.
This kind of a rating scale will take into account how often a fielder comes into play, and will account for how good they already are, given that they are likely to be placed according to their previously demonstrated abilities.
Of course, this will add to all the counting and mathematics we already do as cricket tragics, but as matches add up, we’ll have new stats to pour ourselves into and write articles about. I count that as a win.
Chasing Tales 