The Epidemiology of Pickleball Injuries Presenting to US Emergency Departments

Abstract

Background:

The popularity of pickleball as a recreational and competitive sport has increased dramatically over the last decade in the United States.

Hypothesis:

To evaluate trends in pickleball injury rates and specific injury characteristics.

Study Design:

Descriptive epidemiology study.

Level of Evidence:

Level 3.

Methods:

The National Electronic Injury Surveillance System database was queried from 2014 to 2023 for national weighted injury estimates and injury characteristics from recreational pickleball players presenting to US emergency departments.

Results:

Annual national estimates of pickleball-related injuries increased significantly (P < .001) from 2014 (1313; CI, 550-2078) to 2023 (24,461; CI, 3837-45,086). A transient 19.3% reduction in injury rates occurred in 2020, coinciding with the COVID-19 pandemic. Most injuries affected people aged 60 to 79 years, with nearly equal sex distribution (51.2% men vs 48.8% women). Most patients were discharged, although 5 deaths due to cardiac arrest were reported. Women had higher odds of upper extremity injuries (odds ratio [OR], 1.66), hand/wrist injuries (OR, 3.22), and fractures (OR 3.03). Men experienced more lower extremity injuries (OR, 1.71), trunk injuries (OR, 1.28), lacerations (OR, 1.71) and strains/sprains (OR, 1.87). Women were more likely to fall (OR, 2.08), while men were more often hit (OR, 1.92) or overexerted themselves (OR, 1.89). Older adults, aged 60 to 79 years, had increased odds of wrist/hand injuries (OR, 1.47) and fractures (OR, 1.75), with falls being 2.10 times more likely in this cohort. People aged 40 to 59 years had higher odds of lower extremity injuries (OR, 2.09), whereas those <19 years had higher odds of dislocation (OR, 5.25), head injury (OR, 1.95), and laceration (OR, 2.83).

Conclusion:

Pickleball injuries affect predominantly older adults, with distinct sex and age-related patterns.

Clinical Relevance:

There is a need for age and sex-specific injury prevention strategies to enhance safety in pickleball participation.

Pickleball, characterized by its combination of tennis, table tennis, and badminton, has experienced exponential growth over the past decade in the United States. According to the Sports and Fitness Industry Association’s 2023 ‘State of Pickleball: Participation & Infrastructure Report,’ participation rates have increased 85.7% year-over-year, reaching 8.9 million participants nationally in 2023, ¹⁴ compared with 2.8 million in 2017. ⁹ This surge is likely multifactorial and secondary to a combination of increased media coverage, national court construction efforts, national and community tournament offerings, as well as demographic trends.

The USA Pickleball Association, established in 2005 as the national governing body for the sport of pickleball in the United States, hosted its inaugural USA Pickleball National Championships in 2009. Drawing over 2.6 million television viewers for the 2023 National Championships, ¹⁵ the associated media coverage has spurred numerous state and local community competitions, prompting the need for nationwide infrastructure modifications and new court construction. Traditionally, pickleball has been popular among older people due to its low impact nature, accessibility and social offerings. According to Greiner, ⁹ in 2017 75% of core participants (defined as those playing ≥8 times per year) were aged ≥55 years, with 42% of all participants >65 years considered core participants. However, recent years have seen a significant change in age demographics, with the majority of participants now aged 25 to 34 years, with an average participant age of 35 years. ¹⁴ In addition, the 18- to 24-year and >65-year age groups are now tied for the second-highest participating age group. ¹⁴

Despite its relatively low-impact nature, pickleball is not without its injury potential. As pickleball court construction efforts have expanded and participation rates have soared, there is a growing need to comprehensively examine the epidemiology of pickleball-related injuries to inform injury prevention strategies, enhance player safety, and promote the long-term sustainability of the sport.

In this study, we describe historical national estimates (NEs) of pickleball-related injuries presenting to US emergency departments. The purpose of this study is to investigate trends in pickleball injury incidence, alongside common injury characteristics, mechanisms of injury, and disposition patterns of pickleball players in the United States.

Methods

This study is exempt from Institutional Review Board approval. We retrospectively reviewed cases of pickleball-associated injuries in the National Electronic Injury Surveillance System (NEISS), between 2014 and 2023. The NEISS database is a national database maintained by the US Consumer Product Safety Commission (CPSC), allowing the CPSC to oversee and document product and/or activity-related injuries that present to US emergency departments. It is publicly available, deidentified, and published annually on an accessible governmental website. ¹⁵ It provides a nationally representative probability sample from approximately 100 US hospital emergency departments stratified by hospital size and geographic location, which allows weighted NEs for queried injuries to be derived. Many reliable, reproducible epidemiological studies have been published with this database.^1,6,10,12,13 Specific data collection methodologies, quality control precautions, and other general information are freely available on the CPSC website. ¹⁵

We queried each yearly sample in the NEISS database from 2014 to 2023 for injuries classified as associated with pickleball (Product Code: 3235 — “Other ball sports (activity/apparel/equipment)”). This yielded a total of 20,121 unique cases during this period. One author searched the subsequent free-text narratives to assign variables and exclude cases that were unrelated to the sport of pickleball, given that NEISS code 3235 is not unique to pickleball. The excluded sporting activities were the following: “lacrosse,” “dodgeball,” “kickball,” “bocceball,” “spikeball,” and “cricket.” Overall, 18,399 cases unrelated to the sport of pickleball were identified and excluded.

Information regarding the pickleball player’s age (years), sex, body part injured, injury diagnosis, mechanism of injury (MOI), and disposition (hospital admission versus discharge versus died) were extracted for analysis. The following age groups were used: ≤19, 20 to 39, 40 to 59, 60 to 79, and ≥80 years. Body parts injured were categorized as follows: upper extremity (shoulder, upper arm, elbow, lower arm), wrist/hand (wrist, hand, fingers), lower extremity (upper leg, knee, lower leg, foot, toes), ankle, head (head, neck, face, mouth, ears, and eyes), trunk (upper and lower trunk, hip, and pubic region), and other. Separate categories were included for ankle and wrist/hand due to their relevance to the sport of pickleball. Injury diagnosis included fractures, lacerations (lacerations, foreign bodies, punctures, and/or avulsions), strains/sprains, contusions/abrasions, dislocations, concussion, and other. MOI included fall, hitting and/or striking a surface, being hit and/or struck, overexertion, and other. Pickleball players that were treated and transferred or treated and admitted/hospitalized were categorized as being hospitalized, while pickleball players that were treated/examined and released, held for observation, or left without being seen were considered not hospitalized.

Statistical Analysis

Weighted NEs and 95% CI were calculated using the complex samples function of IBM SPSS Statistics for Windows Version 29.0 (IBM Corp). Bivariate comparisons between variables were conducted using chi-square analysis with strength of association assessed using odd ratios (OR) with 95% CI. In cases where there are >2 categories, all ORs constitute a comparison between the group of interest and all other categories consolidated into a single group. Simple linear regression analysis was utilized to determine significance of trends in the total national survey estimates and participation over time. An alpha value <0.05 was considered to indicate statistical significance.

Results

Between 2014 and 2023, 1722 unique cases presented to NEISS represented US emergency departments, resulting in an NE of 100,704 (standard error [SE], 32,803; 95% CI, 35,211-166,197) pickleball-related injuries. Among these cases, 11 people sustained a cardiac arrest, with 5 unfortunately succumbing before arrival at the hospital or in the emergency department. The age range of these people was 64 to 77 years. No other fatal episodes were reported during this period. Furthermore, the annual NEs of pickleball-related injuries presenting to US emergency departments increased significantly (P = .001) from 2014 (n = 1313; CI, 550-2076) to 2023 (n = 24,461; CI, 3837-45,086). Figure 1 illustrates the historical trends for the national annual estimate of the number of pickleball-related injuries presenting to US emergency departments.

Figure 1.

NE of pickleball injuries presenting to US emergency departments between 2014 and 2023. Data extracted from NEISS. NE, National estimate; NEISS, National Electronic Injury Surveillance System.

Table 1 presents weighted NEs and demographics of pickleball-related injuries presenting to US emergency departments between 2014 and 2023. The distribution across age groups exhibited notable variations, with the majority of cases occurring in the 60- to 79-year age range (P < .001). In terms of sex distribution, men accounted for 51.2% and women for 48.8% of the NE, with no significant difference found (P = .17). Concerning disposition outcomes, 18.6% of cases resulted in hospitalization, 81.0% were discharged, and there were 5 reported deaths (0.3%). Significantly different disposition outcomes were observed (P < .01).

Table 1.

NEs of pickleball injuries presenting to US emergency departments between 2014 and 2023, stratified by age, sex, and disposition

Parameters	Cases Reported (n)	NE	SE	95% CI	P value
Total	1722	100,704 (100%)	32,803	35,211-166,197
Age, y					<.001*
≤19	67	2075 (2.1%)	800	478-3673
20-39	74	3529 (3.5%)	1103	1326-5731
40-59	282	15,161 (15.1%)	5934	3313-27,008
60-79	1201	74,282 (73.8%)	23,147	28,067-120,496
≥80	98	5657 (5.6%)	2109	1447-9868
Sex					.17
Male	873	51,587 (51.2%)	16,317	19,008-84,165
Female	849	49,117 (48.8%)	16,570	16,033-82,201
Disposition					<.01*
Hospitalized	295	18,769 (18.6%)	6071	6648-30,890
Discharged	1422	81,606 (81.0%)	26,756	28,185-135,027
Deceased	5	329 (0.3%)	171	–13 to −671

^*P value ≤ .05 denotes statistical significance. NE, national estimate.

Table 2 presents the overall NE totals, as well as the relative breakdown of body part injured, diagnosis, MOI, and disposition stratified for men and women, respectively. Analysis of the body parts injured revealed significant sex disparities. Upper extremity injuries (OR, 1.66; CI, 1.25-2.22) and injuries to the hand and wrist (OR, 3.22; CI, 2.44-4.35), were more common among women, whereas lower extremity injuries (OR, 1.71; CI, 1.35-2.18) were more prevalent among men. Fractures, lacerations, and strain/sprain injuries also showed varying sex distributions, with women more likely to sustain a fracture (OR, 3.03; CI, 2.44-3.85) and men more likely to sustain a laceration (OR, 1.71; CI, 1.12-2.63) or strain/sprain (OR, 1.87; CI, 1.49-2.35). Mechanisms of injury differed significantly between sexes, with falls more common among women (OR, 2.08; CI, 1.69-2.50) and being hit/struck (OR, 1.92; CI, 1.19-3.12) and overexertion (OR, 1.89; CI, 1.55-2.29) more likely to occur in the male population. Regarding disposition outcomes, although there was a trend towards an increased number of hospitalized men versus women, this was not a statistically significant finding (54.2% vs 45.8%, respectively; P = .18). There were no notable statistically significant differences between men and women for estimated discharge incidence or estimated death incidence.

Table 2.

NEs for body part injured, diagnosis, MOI, and disposition, stratified by sex (male/female)

Parameter	Cases reported (n)	NE total	Male	Female	P value
Total n	1722	100,704 (100)	51,587 (51.2)	49,117 (48.8)	-
Body part injured
Upper extremity	226	13,268 (13.2)	40.4 (0.60; 0.45-0.80)	59.6 (1.66; 1.25-2.22)	<.001*
Hand/wrist	257	14,663 (14.6)	27.2 (0.31; 0.23-0.41)	72.7 (3.22; 2.44-4.35)	<.001*
Lower extremity	349	20,197 (20.1)	61.3 (1.71; 1.35-2.18)	38.7 (0.58; 0.46-0.74)	<.001*
Ankle	95	5052 (5.1)	58.9 (1.42; 0.94-2.17)	41.1 (0.70; 0.40-1.06)	.10
Head/neck	317	17,767 (17.6)	54.6 (1.21; 0.95-1.55)	45.4 (0.85; 0.65-1.05)	.13
Trunk	397	24,891 (24.7)	55.4 (1.28; 1.02-1.60)	44.6 (0.78; 0.63-0.98)	.03*
Other	81	4866 (4.8)	61.7 (1.60; 1.01-2.54)	38.2 (0.63; 0.39-0.99)	.04*
Diagnosis
Fracture	473	26,640 (26.4)	31.1 (0.33; 0.26-0.41)	68.9 (3.03; 2.44-3.85)	<.001*
Laceration	35	5090 (5.1)	63.2 (1.71; 1.12-2.63)	36.8 (0.58; 0.38-0.89)	.01*
Strain/sprain	400	24,139 (24.0)	62.5 (1.87; 1.49-2.35)	37.5 (0.53; 0.43-0.67)	<.001*
Contusions/abrasions	138	8255 (8.2)	52.9 (1.10; 0.77-1.56)	47.1 (0.91; 0.64-1.30)	.59
Dislocation	43	2651 (2.6)	60.0 (1.50; 0.80-2.79)	40.0 (0.67; 0.36-1.25)	.19
Concussion	14	780 (0.8)	57.1 (1.30; 0.45-3.76)	42.9 (0.77; 0.27-2.22)	.63
Other	559	33,149 (32.9)	55.2 (1.31; 1.07-1.61)	44.7 (0.76; 0.62-0.93)	.008*
MOI
Fall	871	51,613 (51.3)	42.0 (0.48; 0.40-0.59)	58.0 (2.08; 1.69-2.50)	<.001*
Hit/strike	43	2249 (2.2)	46.5 (0.84; 0.46-1.55)	53.5 (1.19; 0.65-2.17)	.58
Being hit/struck	76	3371 (3.3)	65.8 (1.92; 1.19-3.12)	34.2 (0.52; 0.32-0.84)	.007*
Overexertion	713	42,583 (42.3)	59.9 (1.89; 1.55-2.29)	40.1 (0.53; 0.44-0.65)	<.001*
Other	19	887 (0.9)	57.9 (1.34; 0.54-3.35)	42.1 (0.75; 0.30-1.85)	.53
Disposition
Hospitalized	295	18,769 (18.6)	54.2 (1.19; 0.92-1.53)	45.8 (0.84; 0.65-1.09)	.18
Discharged	1422	81,606 (81.0)	49.9 (0.83; 0.64-1.06)	50.1 (1.20; 0.94-1.56)	.13
Deceased	5	329 (0.3)	80.0 (3.9; 0.44-35.0)	20.0 (0.26; 0.03-2.27)	.196

Data given as n (%) or n (OR; CI) *P value ≤ .05 denotes statistical significance. MOI, mechanism of injury; NE, national estimate.

Table 3 presents the overall NE totals, as well as the relative breakdown of body part injured, diagnosis, MOI, and disposition stratified for age category. Notably, the 60- to 79-year-old age group experienced the highest incidence of injuries. Analyzing specific body parts, wrist/hand injuries exhibited a heightened likelihood in the 60- to 79-year-old age group (OR, 1.47; 95% CI, 1.08-2.00), whereas lower extremity injuries were elevated significantly in the 40- to 59-year-old age range (OR, 2.09; 95% CI, 1.57-2.78). Conversely, head injuries were more prevalent among younger players (OR, 1.95; 95% CI, 1.14-3.33). In terms of diagnosis, fractures were notably higher in the 60- to 79-year-old age group (OR, 1.75; 95% CI, 1.37-2.24), whereas lacerations were more likely in the ≤19 years age bracket (OR, 2.83; CI, 1.36-5.90) and the 20- to 39-years age bracket (OR, 2.18; 95% CI, 1.01-4.67). Dislocations were also more prevalent in the ≤19 years age bracket (OR, 5.25; CI, 2.24-12.27) and the 20- to 39-year-old age bracket (OR, 3.07; 95% CI, 1.17-8.04). Analysis of MOI demonstrated a pronounced likelihood of falls in the elderly, particularly in those aged 60 to 79 years (OR, 2.10; 95% CI, 1.70-2.60) and ≥80 years (OR, 2.57; CI, 1.64-4.02). Conversely, overexertion injuries were more prevalent in the 20- to 39-year-old (OR, 3.78; 95% CI, 2.26-6.32) and 40- to 59-year-old (OR, 1.65; CI, 1.28-2.14) groups. The likelihood of being hit or struck was highest in the ≤19 years age bracket (OR, 17.21; CI, 9.72-30.45) and the 20- to 39-year-old age bracket (OR, 3.27; 95% CI, 1.56-6.84), whereas 20- to 39-year-olds were also more likely to hit/strike another object (OR, 3.84; CI, 1.57-9.41). Disposition outcomes revealed a higher tendency for hospitalizations in the 60- to 79-year-old age range (OR, 1.83; 95% CI, 1.35-2.47), whereas fatalities occurred predominantly in people >60 years.

Table 3.

NEs for body part injured, diagnosis, MOI, and disposition, stratified by age

Parameter	NE total	<19 years	20-39 years	40-59 years	60-79 years	≥80 years
Total n	100,704 (100%)	2075 (2.1%)	3529 (3.5%)	15,161 (15.1%)	74,282 (73.8%)	5657 (5.6%)
Body part injured
Upper extremity	13,268 (13.2%)	4.1 (1.32; 0.68-2.55)	1.8 (0.37; 0.13-1.02)	14.2 (0.82; 0.55-1.24)	73.5 (1.23; 0.90-1.69)	5.8 (1.01; 0.56-1.85)
Wrist/hand	14,663 (14.6%)	3.9 (1; 0.50-1.99)	1.6 (0.32; 0.11-0.87)*	11.3 (0.61; 0.41-0.92)*	76.2 (1.47; 1.08-2.00)*	7.0 (1.3; 0.77-2.21)
Lower extremity	20,197 (20.1%)	3.4 (0.85; 0.45-1.61)	7.2 (2.09; 0.27-3.34)	25.5 (2.09; 1.57-2.78)*	60.4 (0.59; 0.46-0.76)*	3.4 (0.53; 0.29-0.99)*
Ankle	5052 (5.1%)	7.4 (2.08; 0.92-4.68)	16.8 (5.48; 3.01-9.96)*	17.9 (1.12; 0.65-1.92)	55.8 (0.53; 0.35-0.80)*	2.1 (0.343; 0.08-1.41)
Head	17,767 (17.6%)	6.3 (1.95; 1.14-3.33)*	3.5 (0.77; 0.40-1.47)	16.4 (1.00; 0.72-1.39)	66.9 (0.85; 0.66-1.10)	6.9 (1.30; 0.80-2.13)
Trunk	24,891 (24.7%)	1.3 (0.26; 0.10-0.65)*	2.3 (0.45; 0.22-0.91)*	13.6 (0.76; 0.55-1.04)	76.1 (1.51; 1.16-1.95)*	6.8 (1.29; 0.82-2.04)
Other	4866 (4.8%)	2.5 (0.61; 0.15-2.55)	6.2 (1.50; 0.59-3.82)	11.1 (0.63; 0.31-1.27)	75.3 (1.34; 0.80-2.25)	4.9 (0.86; 0.31-2.39)
Diagnosis
Fractures	26,640 (26.4%)	2.5 (0.57; 0.30-1.07)	1.5 (0.27; 0.12-0.58)*	11.0 (0.55; 0.40-0.76)*	77.8 (1.75; 1.37-2.24)*	7.2 (1.43; 0.93-2.21)
Lacerations	5090 (5.1%)	9.5 (2.83; 1.36-5.90)*	9.4 (2.18; 1.01-4.67)*	16.8 (1.04; 0.60-1.80)	57.9 (0.58; 0.38-0.88)*	7.4 (1.34; 0.60-2.98)
Strains/sprains	24,139 (24.0%)	3.3 (0.79; 0.43-1.46)	7.5 (2.36; 1.46-3.80)*	23.0 (1.78; 1.35-2.35)*	63.8 (0.70; 0.55-0.89)*	2.5 (0.36; 0.19-0.70)*
Contusions/abrasions	8255 (8.2%)	6.5 (1.84; 0.89-3.79)	2.2 (0.47; 0.15-1.52)	15.2 (0.91; 0.56-1.48)	68.1 (0.92; 0.63-1.34)	8.0 (1.49; 0.78-2.86)
Dislocations	2651 (2.6%)	16.3 (5.25; 2.24-12.27)*	11.6 (3.07; 1.17-8.04)*	14.0 (0.82; 0.35-1.97)	55.8 (0.54; 0.29-0.99)*	2.3 (0.39; 0.05-2.85)
Concussion	780 (0.8%)	14.3 (4.21; 0.92-19.2)	0.00 (1.05; 1.04-1.06)*	21.4 (1.40; 0.39-5.04)	64.3 (0.78; 0.26-2.34)	0.0 (1.06; 1.05-1.07)*
Other	33,149 (32.9%)	2.7 (0.60; 0.34-1.08)	3.8 (0.82; 0.49-1.37)	16.5 (1.01; 0.77-1.33)	70.8 (1.08; 0.87-1.35)	6.3 (1.17; 0.76-1.79)
MOI
Fall	51,613 (51.3%)	1.5 (0.22; 0.12-0.41)*	0.7 (0.08; 0.03-0.19)*	12.4 (0.55; 0.42-0.72)*	77.4 (2.10; 1.70-2.60)*	8.0 (2.57; 1.64-4.02)*
Hit/strike	2249 (2.2%)	4.7 (1.21; 0.29-5.12)	13.9 (3.84; 1.57-9.41)*	20.9 (1.36; 0.65-1.88)	55.8 (0.54; 0.29-0.99)*	4.7 (0.80; 0.19-3.38)
Being hit/struck	3371 (3.3%)	31.6 (17.21; 9.72-30.45)*	11.8 (3.27; 1.56-6.84)*	21.1 (1.38; 0.76-2.44)	34.2 (0.21; 0.13-0.34)*	1.3 (0.21; 0.03-1.55)
Overexertion	42,583 (42.3%)	3.7 (0.89; 0.54-1.48)	7.4 (3.78; 2.26-6.32)*	20.5 (1.65; 1.28-2.14)*	65.1 (0.69; 0.56-0.85)*	3.4 (0.44; 0.26-0.71)*
Other	887 (0.9%)	10.5 (2.97; 0.67-13.10)	0.00 (1.05; 1.04-1.06)*	15.8 (0.96; 0.28-3.31)	68.4 (0.94; 0.36-2.46)	5.3 (0.92; 0.12-6.96)
Disposition
Hospitalized	18,769 (18.6%)	1.4 (0.30; 0.11-0.82)*	0.3 (0.06; 0.01-0.46)*	9.5 (0.48; 0.32-0.73)*	79.3 (1.83; 1.35-2.47)*	9.5 (2.03; 1.29-3.21)*
Discharged	81,606 (81.0%)	4.4 (3.43; 1.24-9.50)*	5.1 (16.18; 2.24-116.87)*	17.9 (2.11; 1.40-3.19)*	67.7 (0.53; 0.40-0.72)*	4.9 (0.50; 0.32-0.80)*
Deceased	329 (0.3%)	0.00 (1.04; 1.03-1.05)*	0.00 (1.05; 1.04-1.06)*	0.0 (1.20; 1.17-1.22)*	100.0 (1.46; 1.41-1.51)*	0.0 (1.06; 1.05-1.07*

Data given as n (%) or n (OR; CI) *P value ≤ .05 denotes statistical significance. MOI, mechanism of injury; NE, national estimate.

Discussion

Pickleball has gained tremendous popularity in recent years, amongst people of all ages, but with this surge in participation comes an inevitable increase in pickleball-related injuries. The data presented here from 2014 to 2023 shed light on the scope and characteristics of these injuries, offering valuable insights for injury prevention and healthcare management strategies.

The significant rise in pickleball-related injuries over the past decade, as indicated by the annual NEs, highlights the importance of understanding the factors contributing to these incidents. Forrester ⁷ conducted a similar study to ours between 2001 and 2017, revealing a national injury estimate of 19,012 injuries over the 16-year period, averaging 1188 estimated injuries per year. They noted a consistent number of injuries each year, before a notable increase in reported injuries occurred between 2013 and 2017, despite an overall decline in injuries from other racquet sports, such as tennis and squash, during the same period.^3,4,7,8,11 Our data indicate that this upward trend has persisted, with a significant rise in injury incidence since then, averaging 10,070 estimated injuries per year over the last decade, with more estimated injuries in 2023 alone compared with their entire 16-year study period. This increase is likely attributed to the escalating population-level participation in pickleball.^14,16 Whereas the sport undoubtedly offers numerous health benefits, including improved cardiovascular health and enhanced coordination, this substantial spike in injuries prompts the need for a closer examination of safety measures and player education initiatives.

One of the most striking findings is the age distribution of people affected by pickleball-related injuries. The majority of cases occurred in the 60- to 79-year-old age range, aligning with the traditional demographic profile of pickleball enthusiasts, ⁹ and consistent with the injury incidence findings by Forrester. ⁷ This demographic trend specifically highlights the need for targeted injury prevention strategies tailored to older adults, such as specialized warm-up routines, proper technique instruction, and equipment modifications to accommodate age-related physical changes. Older adults, particularly those aged ≥60 years, also faced an increased risk of falls and fractures, emphasizing the importance of balance training and fall prevention strategies in this demographic. Conversely, younger players were more susceptible to head injuries and injuries resulting from high-impact collisions, despite pickleball being a noncontact sport, suggesting the need for perceptual awareness training and concussion initiatives among younger participants.

Moreover, the sex disparities in injury patterns also highlight potential areas for targeted intervention. Although male and female players were equally represented in the overall injury count, with no historical change noted, ⁷ distinct differences between sexes emerged in the types and mechanisms of injury. For instance, women exhibited a higher susceptibility to upper extremity injuries, falls, and fractures, whereas men exhibited a greater incidence of lower extremity injuries and injuries resulting from overexertion or being hit/struck by objects. These findings highlight the importance of sex-specific injury prevention approaches and equipment considerations to address the distinct vulnerabilities of male and female players. Given that women have a higher predisposition to developing osteoporosis, and consequentially sustaining fragility fractures after a fall, ¹⁷ it is crucial to disseminate health communication about modifiable risk factors for osteoporosis to elderly female and male pickleball players alike, ensuring optimal bone mineral density. ⁵ In addition, routine vision testing, polypharmacy review, and balance training, as mentioned previously, are all essential strategies to mitigate the risk of falls in this population group. ²

In terms of disposition outcomes, the increased likelihood for hospitalization and fatalities among older adults after a pickleball-related injury is consistent with previous literature, and once more emphasizes the severity of injuries sustained by this demographic. ⁷ This highlights the importance of prompt and appropriate medical care for older people involved in pickleball-related incidents and emphasizes the need for targeted rehabilitation programs to facilitate recovery and decrease the risk of future injuries and readmissions.

Limitations

This study is subject to several limitations. The NEISS database inherently poses several very important limitations that need to be acknowledged when interpreting findings. First, the estimation of national pickleball injuries in this study may underrepresent the true national landscape, as it relies solely on documented emergency department visits. Consequently, less severe pickleball injuries managed outside of emergency departments (eg, in primary care offices, urgent care centers, or by allied health practitioners elsewhere) were likely not captured, neither were minor injuries that did not prompt a healthcare visit. In addition, sampling bias is likely when using the NEISS database. The data are collected from a sample of hospitals across the United States, which may not always fully represent the general population or account for regional or geographical variations in evolving injury patterns. Finally, the accuracy and completeness of injury case reporting by hospital staff are crucial for reliable data. Given that pickleball does not have its own unique NEISS database code, pickleball cases were identified by author analysis of the provided free text narrative. Inconsistencies or errors in reporting from healthcare staff could potentially have led to missed cases in which the term pickleball was not included and thus skew the data.

Conclusion

In summary, the data presented here on pickleball-related injuries from 2014 and 2023 provide valuable insight into the epidemiology and characteristics of these injuries. Our findings highlight a continuing upward trend in pickleball injury rates, coinciding with reported participation rate growth, and reveal a complex interplay of age, sex, injury type, and MOI in these cases. This underscores the necessity for sex- and age-specific approaches to injury prevention. It should enable stakeholders to develop evidence-based strategies aimed at fostering safer participation in pickleball and reducing associated risks. Ultimately, this will enhance the overall health and wellbeing of players across all sexes and age groups.