Equinox Marathon Start, 2025. Photo: Todd Paris Abstract We review race participation for Running Club North races between 2006 and 2026, examining demographic changes across the period, and the post-pandemic recovery. Finisher records for 12 races from 2006 through 2026 (115,945 records) come from my races database, with the race-year as the unit of analysis. We fit hierarchical models in rstanarm: binomial models for the proportion of the field in each group, and negative binomial models for how many people of each group finished. The group models estimate an overall trend and a pandemic shift together, so the shift is determined independent of any trend already present. The participant models compare 2015–2019 with 2022–2026. Over twenty years the 60+ group rose (odds ×2.70, 95% credible interval 1.62–4.38) and the 40–49 group fell (×0.73, 0.53–0.96), as did the 50–59 group (×0.58, 0.35–0.92). The younger bands vary so much from race to race that their trends can’t be identified. Post-pandemic the odds a finisher was 20–29 fell (odds ratio 0.76, 0.64–0.90), and the odds a finisher was a woman also fell (odds ratio 0.87, 0.75–0.96). The 40–49 group rose a little (odds ratio 1.12, 1.001–1.25). For the Gold Discovery Run the field halved after the pandemic (rate ratio 0.53, 0.39–0.74) while its make-up moved the way the series did. The field has gotten older at the top and thinner in the middle over two decades. On top of those trends, post-pandemic races have lost runners in their twenties, and the percentage of finishers who were women fell. Introduction I keep a database of Interior Alaska race results, going back decades for some races. After the 2020 and 2021 seasons were cancelled or run under restrictions, it has taken several years for participation levels to return. We are interested in examining how the composition of Running Club North races is changing over time and after the pandemic. These are two different questions, and when examining the effect of the pandemic, we need to remove the overall trend to understand the post-pandemic participation changes independent of it. To keep those apart, we fit an overall trend and a pandemic shift in the same model for each group. Because race sizes differ dramatically, we allow the model to determine the weight of each race. Data The records come from my races database, which is also available from Running Club North’s website. It combines chip-timing exports, results scraped from race websites, and older printed results I’ve transcribed into one table with a row per finisher: name, gender, birth year, finish time, race, event and date. Races that changed names, and runners who changed names, are reconciled through lookup tables. We used races from 2006 through 2026. Relay entries are excluded, since they are teams rather than individuals. Ages outside 3 to 95 were treated as missing, which affects 418 of 152,490 records, 403 of them ages 0 to 2, probably from mistyped birth years. The 2020 season was almost entirely cancelled and many weren’t run in 2021, so both years are dropped rather than folded in with the rest. To be usable, a race-year had to have at least 25 finishers with at least 90% of them having both an age and a gender, and a race had to have at least three usable seasons in each of two five-season windows, 2015–2019 (32,641 records) and 2022–2026 (29,588). That leaves 12 races and 115,945 finisher records (Table 1). An overall trend needs races recorded nearly every year, so the group models use only the 7 races with at least 12 usable seasons from 2006 through 2019. The participant count and new runner models compare only the two windows, so they use all 12. Note The Chena River Run’s 2006 results were uploaded with age classes instead of ages, with ages 18–29 in a single class. That means we can’t match those classes with our under-20 and 20–29 classes, so that race-year was excluded from the models for these two groups. Methods We used binomial models for proportions, such as the fraction of finishers who were women or in their twenties, and negative binomial models for participant counts. The groups considered were six age bands (under 20, 20–29, 30–39, 40–49, 50–59, 60+), and gender. Age bands are shares of the field, so they aren’t independent of each other: if one group is increasing, the others are dropping by the same amount overall. For counts, we chose 7 groups ahead of time: the whole field, women, men, and women and men separately in the 20–29 and 30–39 bands, so that a drop in one gender is compared against the same age band in the other. Gender is as recorded at registration. There were 24 non-binary finishers, which is not a large enough sample size to include in the gender comparisons. Every model uses the race-year as the unit rather than the finisher: 114 race-years in the two windows, and 130 for the group models over the full span. Each group model has a term for the overall trend, an indicator for post-pandemic seasons (2022 on), and a term for each race-year because race-years vary more than a simple binomial model expects. The participant count and new runner models cover only the two windows, so they have the pandemic indicator but no overall trend. Each race gets its own intercept and pandemic shift, and in the group models its own overall trend, drawn from a common distribution whose spread the model estimates. That spread decides how far any one race is pulled toward the others, so a big race with a tight estimate counts for more than a 60-finisher race with a wide one. Outputs We are using Bayesian models, fit with rstanarm. Instead of one estimate and a p-value, each one produces a distribution of plausible values for every coefficient, and the more uncertainty there is, the wider that distribution. We report the middle of the distribution (the median) along with a 95% credible interval (95% CrI below), which is the range the middle 95% of those values fall in. If the credible interval doesn’t include the “no effect” value, we treat the change as clear. Most of the results are odds ratios (OR). An odds ratio of 1 means nothing changed, 0.75 means the odds fell by 25%, and 3.00 means they tripled. For participant counts the equivalent is a rate ratio (RR), where 0.50 means half as many people. In the tables and in the parentheses below, each one is the estimate followed by its 95% credible interval, so “OR 0.76, 95% CrI 0.64–0.90” means the odds fell by about a quarter and the plausible range runs from 0.64 to 0.90. I also report P(decline), which is the share of that distribution sitting below no change, or in other words the probability the parameter really did go down. A P(decline) of 0.97 means 97% of the plausible values are declines. The priors used in the models are weakly informative: normal(0, 1) on the year and change terms, which is generous (a coefficient of 1 is an odds ratio of 2.7), normal(0, 2.5) on intercepts in the group models and normal(0, 5) in the count models, and the rstanarm defaults for covariances. Each model ran four chains of 2,000 iterations with half discarded as warm-up. The analysis used R version 4.6.1 (2026-06-24) with dplyr (1.2.1) and rstanarm (2.32.2). Results Races Table 1: Races meeting the criteria. 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} #njphdfdmcj .gt_footnote { margin: 0px; font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #njphdfdmcj .gt_sourcenotes { color: #333333; background-color: #FFFFFF; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; } #njphdfdmcj .gt_sourcenote { font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #njphdfdmcj .gt_left { text-align: left; } #njphdfdmcj .gt_center { text-align: center; } #njphdfdmcj .gt_right { text-align: right; font-variant-numeric: tabular-nums; } #njphdfdmcj .gt_font_normal { font-weight: normal; } #njphdfdmcj .gt_font_bold { font-weight: bold; } #njphdfdmcj .gt_font_italic { font-style: italic; } #njphdfdmcj .gt_super { font-size: 65%; } #njphdfdmcj .gt_footnote_marks { font-size: 75%; vertical-align: 0.4em; position: initial; } #njphdfdmcj .gt_asterisk { font-size: 100%; vertical-align: 0; } #njphdfdmcj .gt_indent_1 { text-indent: 5px; } #njphdfdmcj .gt_indent_2 { text-indent: 10px; } #njphdfdmcj .gt_indent_3 { text-indent: 15px; } #njphdfdmcj .gt_indent_4 { text-indent: 20px; } #njphdfdmcj .gt_indent_5 { text-indent: 25px; } #njphdfdmcj .katex-display { display: inline-flex !important; margin-bottom: 0.75em !important; } #njphdfdmcj div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after { height: 0px !important; } Race Seasons Span Finishers Women (%) Median age Midnight Sun Run 19 2006–2026 57,385 56.8 31 Chena River Run 19 2006–2026 15,037 56.8 35 Beat Beethoven 19 2006–2026 12,536 55.2 34 Equinox Marathon 18 2006–2025 8,142 47.4 39 Mosquito Meander 15 2006–2026 7,129 62.5 33 HooDoo Half Marathon 8 2016–2025 4,004 54.6 35 Santa Claus Half Marathon 19 2006–2026 3,293 56.5 39 Water Walk and Run 10 2015–2026 2,361 59.0 33 Gold Discovery Run 19 2006–2026 2,243 48.6 42 Jim Loftus Mile 17 2006–2026 1,675 45.4 39 Golden Heart Trail Run 15 2010–2026 1,542 47.5 40 Alaska Endurance Trail Run 9 2016–2026 598 49.2 40 Overall trends Three age groups moved between 2006 and 2026, independent of the pandemic (Figure 1, Table 2). The odds a finisher was 60+ nearly tripled, the largest move of the three, taking that group from 6.4% of the field to 10.1%. The odds for the 40–49 group fell by about a quarter, and for the 50–59 group by roughly two fifths (P(decline) 0.98). Figure 1: Each age band’s share of the field, seven core races. Points are seasons; the line is the fitted trend with the pandemic change held out, so it runs unbroken across the shaded 2020–21 gap. Solid and coloured where the credible interval excludes no change (red falling, blue rising), grey and dashed where it doesn’t. Table 2: Overall trend in each age band’s share of the field, and in women’s share of women and men, 2006–2026, net of the pandemic shift. Odds ratios over the twenty years, with 95% credible intervals. #mubtxlrvlz table { font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji'; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } #mubtxlrvlz thead, #mubtxlrvlz tbody, #mubtxlrvlz tfoot, #mubtxlrvlz tr, #mubtxlrvlz td, #mubtxlrvlz th { border-style: none; } #mubtxlrvlz p { margin: 0; padding: 0; } #mubtxlrvlz .gt_table { display: table; border-collapse: collapse; line-height: normal; margin-left: auto; margin-right: auto; color: #333333; font-size: 13px; font-weight: normal; font-style: normal; background-color: #FFFFFF; width: 100%; border-top-style: none; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #A8A8A8; border-left-style: none; border-left-width: 2px; 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} #mubtxlrvlz .gt_footnote { margin: 0px; font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #mubtxlrvlz .gt_sourcenotes { color: #333333; background-color: #FFFFFF; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; } #mubtxlrvlz .gt_sourcenote { font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #mubtxlrvlz .gt_left { text-align: left; } #mubtxlrvlz .gt_center { text-align: center; } #mubtxlrvlz .gt_right { text-align: right; font-variant-numeric: tabular-nums; } #mubtxlrvlz .gt_font_normal { font-weight: normal; } #mubtxlrvlz .gt_font_bold { font-weight: bold; } #mubtxlrvlz .gt_font_italic { font-style: italic; } #mubtxlrvlz .gt_super { font-size: 65%; } #mubtxlrvlz .gt_footnote_marks { font-size: 75%; vertical-align: 0.4em; position: initial; } #mubtxlrvlz .gt_asterisk { font-size: 100%; vertical-align: 0; } #mubtxlrvlz .gt_indent_1 { text-indent: 5px; } #mubtxlrvlz .gt_indent_2 { text-indent: 10px; } #mubtxlrvlz .gt_indent_3 { text-indent: 15px; } #mubtxlrvlz .gt_indent_4 { text-indent: 20px; } #mubtxlrvlz .gt_indent_5 { text-indent: 25px; } #mubtxlrvlz .katex-display { display: inline-flex !important; margin-bottom: 0.75em !important; } #mubtxlrvlz div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after { height: 0px !important; } Group 2006 (%) 2026 (%) OR over 20 y 95% CrI P(decline) under 20 25.9 25.8 1.43 0.57–3.94 0.18 20-29 14.8 18.3 0.82 0.46–1.48 0.78 30-39 18.2 20.5 1.22 0.91–1.58 0.08 40-49 19.5 17.0 0.73 0.53–0.96 0.99 50-59 15.5 8.2 0.58 0.35–0.92 0.98 60+ 6.4 10.1 2.70 1.62–4.38 < 0.01 Women 58.0 51.8 1.02 0.84–1.31 0.42 The groups didn’t all move the same way. The 60+ group went up while the two bands below it went down, so the field hollowed out in its forties and fifties rather than simply getting older across the board. The percentage of women no clear trend. Across the whole twenty years the odds a finisher was a woman changed by ×1.02 (95% CrI 0.84–1.31; Table 2, bottom row), with women averaging 55.5% of the field. The pandemic Independent of each group’s overall trend, 3 of 7 groups shifted after 2021 (Figure 2, Table 3). The odds a finisher was aged 20–29 fell by 24% (OR 0.76, 95% CrI 0.64–0.90, P(decline) > 0.99), and the odds a finisher was a woman fell by 13% (OR 0.87, 0.75–0.96, P(decline) > 0.99). The 40–49 group went up (OR 1.12, 1.001–1.25). The 30–39 group probably fell (P(decline) 0.93) and the under-20 group probably rose (P(decline) 0.09), but both of those intervals include no change, and the 50–59 and 60+ groups show nothing at all. Figure 2: Post-pandemic change in each group’s share, net of its own 2006–2026 trend. Points are medians with 95% credible intervals, red where the interval sits below no change and blue where it sits above. The number at the right is P(decline). Table 3: Post-pandemic change in each group’s share, net of its long-term trend. #ppsvvklkqv table { font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji'; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } #ppsvvklkqv thead, #ppsvvklkqv tbody, #ppsvvklkqv tfoot, #ppsvvklkqv tr, #ppsvvklkqv td, #ppsvvklkqv th { border-style: none; } #ppsvvklkqv p { margin: 0; padding: 0; } #ppsvvklkqv .gt_table { display: table; border-collapse: collapse; line-height: normal; margin-left: auto; margin-right: auto; color: #333333; font-size: 13px; font-weight: normal; font-style: normal; background-color: #FFFFFF; width: 100%; border-top-style: none; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #A8A8A8; border-left-style: none; 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border-top-style: solid; border-top-width: 2px; border-top-color: #D3D3D3; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #D3D3D3; vertical-align: middle; } #ppsvvklkqv .gt_from_md > :first-child { margin-top: 0; } #ppsvvklkqv .gt_from_md > :last-child { margin-bottom: 0; } #ppsvvklkqv .gt_row { padding-top: 5px; padding-bottom: 5px; padding-left: 5px; padding-right: 5px; margin: 10px; border-top-style: none; border-top-width: 1px; border-top-color: #D3D3D3; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; vertical-align: middle; overflow-x: hidden; } #ppsvvklkqv .gt_stub { color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: initial; text-transform: inherit; border-right-style: solid; border-right-width: 2px; border-right-color: #D3D3D3; padding-left: 5px; padding-right: 5px; } #ppsvvklkqv .gt_stub_row_group { color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: initial; text-transform: inherit; border-right-style: solid; border-right-width: 2px; border-right-color: #D3D3D3; padding-left: 5px; padding-right: 5px; vertical-align: top; } #ppsvvklkqv .gt_row_group_first td { border-top-width: 2px; } #ppsvvklkqv .gt_row_group_first th { border-top-width: 2px; } #ppsvvklkqv .gt_summary_row { color: #333333; background-color: #FFFFFF; text-transform: inherit; padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; } #ppsvvklkqv .gt_first_summary_row { border-top-style: solid; border-top-color: #D3D3D3; } #ppsvvklkqv .gt_first_summary_row.thick { border-top-width: 2px; } #ppsvvklkqv .gt_last_summary_row { padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #D3D3D3; } #ppsvvklkqv .gt_grand_summary_row { color: #333333; background-color: #FFFFFF; text-transform: inherit; padding-top: 8px; padding-bottom: 8px; 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} #ppsvvklkqv .gt_footnote { margin: 0px; font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #ppsvvklkqv .gt_sourcenotes { color: #333333; background-color: #FFFFFF; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; } #ppsvvklkqv .gt_sourcenote { font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #ppsvvklkqv .gt_left { text-align: left; } #ppsvvklkqv .gt_center { text-align: center; } #ppsvvklkqv .gt_right { text-align: right; font-variant-numeric: tabular-nums; } #ppsvvklkqv .gt_font_normal { font-weight: normal; } #ppsvvklkqv .gt_font_bold { font-weight: bold; } #ppsvvklkqv .gt_font_italic { font-style: italic; } #ppsvvklkqv .gt_super { font-size: 65%; } #ppsvvklkqv .gt_footnote_marks { font-size: 75%; vertical-align: 0.4em; position: initial; } #ppsvvklkqv .gt_asterisk { font-size: 100%; vertical-align: 0; } #ppsvvklkqv .gt_indent_1 { text-indent: 5px; } #ppsvvklkqv .gt_indent_2 { text-indent: 10px; } #ppsvvklkqv .gt_indent_3 { text-indent: 15px; } #ppsvvklkqv .gt_indent_4 { text-indent: 20px; } #ppsvvklkqv .gt_indent_5 { text-indent: 25px; } #ppsvvklkqv .katex-display { display: inline-flex !important; margin-bottom: 0.75em !important; } #ppsvvklkqv div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after { height: 0px !important; } Stratum OR 95% CrI P(decline) under 20 1.19 0.91–1.62 0.09 20-29 0.76 0.64–0.90 > 0.99 30-39 0.91 0.78–1.04 0.93 40-49 1.12 1.001–1.25 0.03 50-59 1.07 0.89–1.25 0.20 60+ 0.95 0.80–1.16 0.72 women vs men 0.87 0.75–0.96 > 0.99 The chances a finisher was a woman, flat for the fourteen seasons before the interruption, has been below its old level in every season since (Figure 3). Figure 3: Women as a share of finishers, seven core races. Points are seasons; the grey dashed line is the fitted trend with the change held out, dashed because the trend isn’t different from zero. The shaded band is the 2020–21 gap and the horizontal dashed line is parity. A group sitting below its overall trend in recent years can mean two different things: a group that dropped once and stayed down, or a group that is still dropping. Those call for different responses, so they’re worth separating. Fitting a change at 2022 and a slope for the seasons after it in the same model (Table 4) shows that the two losses have different shapes. The 20–29 group dropped after the pandemic (change OR 0.72, 0.60–0.87) and has neither recovered nor kept falling (×1.033 per year, 0.982–1.092). Those runners left and haven’t come back. The female:male finishers ration shows no clear drop (OR 0.93, 0.80–1.03) but a steady slide since: ×0.964 per season (0.937–0.990), which means the shortfall was small in 2022 and is largest in 2026. Table 4: The change after 2021 split into a drop at 2022 and a drift per year since. #dcsdfeagsz table { font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji'; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } #dcsdfeagsz thead, #dcsdfeagsz tbody, #dcsdfeagsz tfoot, #dcsdfeagsz tr, #dcsdfeagsz td, #dcsdfeagsz th { border-style: none; } #dcsdfeagsz p { margin: 0; padding: 0; } #dcsdfeagsz .gt_table { display: table; border-collapse: collapse; line-height: normal; margin-left: auto; margin-right: auto; color: #333333; font-size: 13px; font-weight: normal; font-style: normal; background-color: #FFFFFF; width: 100%; border-top-style: none; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #A8A8A8; border-left-style: none; 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border-top-style: solid; border-top-width: 2px; border-top-color: #D3D3D3; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #D3D3D3; vertical-align: middle; } #dcsdfeagsz .gt_from_md > :first-child { margin-top: 0; } #dcsdfeagsz .gt_from_md > :last-child { margin-bottom: 0; } #dcsdfeagsz .gt_row { padding-top: 5px; padding-bottom: 5px; padding-left: 5px; padding-right: 5px; margin: 10px; border-top-style: none; border-top-width: 1px; border-top-color: #D3D3D3; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; vertical-align: middle; overflow-x: hidden; } #dcsdfeagsz .gt_stub { color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: initial; text-transform: inherit; border-right-style: solid; border-right-width: 2px; border-right-color: #D3D3D3; padding-left: 5px; padding-right: 5px; } #dcsdfeagsz .gt_stub_row_group { color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: initial; text-transform: inherit; border-right-style: solid; border-right-width: 2px; border-right-color: #D3D3D3; padding-left: 5px; padding-right: 5px; vertical-align: top; } #dcsdfeagsz .gt_row_group_first td { border-top-width: 2px; } #dcsdfeagsz .gt_row_group_first th { border-top-width: 2px; } #dcsdfeagsz .gt_summary_row { color: #333333; background-color: #FFFFFF; text-transform: inherit; padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; } #dcsdfeagsz .gt_first_summary_row { border-top-style: solid; border-top-color: #D3D3D3; } #dcsdfeagsz .gt_first_summary_row.thick { border-top-width: 2px; } #dcsdfeagsz .gt_last_summary_row { padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #D3D3D3; } #dcsdfeagsz .gt_grand_summary_row { color: #333333; background-color: #FFFFFF; text-transform: inherit; padding-top: 8px; padding-bottom: 8px; 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} #dcsdfeagsz .gt_footnote { margin: 0px; font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #dcsdfeagsz .gt_sourcenotes { color: #333333; background-color: #FFFFFF; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; } #dcsdfeagsz .gt_sourcenote { font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #dcsdfeagsz .gt_left { text-align: left; } #dcsdfeagsz .gt_center { text-align: center; } #dcsdfeagsz .gt_right { text-align: right; font-variant-numeric: tabular-nums; } #dcsdfeagsz .gt_font_normal { font-weight: normal; } #dcsdfeagsz .gt_font_bold { font-weight: bold; } #dcsdfeagsz .gt_font_italic { font-style: italic; } #dcsdfeagsz .gt_super { font-size: 65%; } #dcsdfeagsz .gt_footnote_marks { font-size: 75%; vertical-align: 0.4em; position: initial; } #dcsdfeagsz .gt_asterisk { font-size: 100%; vertical-align: 0; } #dcsdfeagsz .gt_indent_1 { text-indent: 5px; } #dcsdfeagsz .gt_indent_2 { text-indent: 10px; } #dcsdfeagsz .gt_indent_3 { text-indent: 15px; } #dcsdfeagsz .gt_indent_4 { text-indent: 20px; } #dcsdfeagsz .gt_indent_5 { text-indent: 25px; } #dcsdfeagsz .katex-display { display: inline-flex !important; margin-bottom: 0.75em !important; } #dcsdfeagsz div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after { height: 0px !important; } Stratum Change at 2022 Drift per season since under 20 1.05 (0.78–1.48) 1.092 (1.046–1.140) 20-29 0.72 (0.60–0.87) 1.033 (0.982–1.092) 30-39 1.01 (0.87–1.15) 0.940 (0.909–0.970) 40-49 1.09 (0.97–1.22) 1.015 (0.988–1.046) 50-59 1.18 (0.97–1.42) 0.941 (0.906–0.974) 60+ 1.06 (0.88–1.33) 0.935 (0.898–0.971) women vs men 0.93 (0.80–1.03) 0.964 (0.937–0.990) The under-20 group has been rising since 2022 (×1.092 per season, 1.046–1.140), and because the groups have to add up to the whole field, the downward drifts in the 30–39, 50–59 and 60+ groups may be partly the arithmetic counterpart of the rise in younger runners. Participant counts The group models explain what the field looks like; participant counts describe how many people are no longer showing up (Figure 4, Table 5). These are straight pre- and post-pandemic comparisons with no trend term, so they include any long-term trend between the two windows. Figure 4: Change in a typical season’s finishers between 2015–2019 and 2022–2026, by age band and gender. Bars are mean annual counts per race summed across the twelve races; labels are the percent change. Table 5: Change in participant count per race between 2015–2019 and 2022–2026, across the twelve races in both windows. Rate ratios with 95% credible intervals. #tauttfiasy table { font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji'; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } #tauttfiasy thead, #tauttfiasy tbody, #tauttfiasy tfoot, #tauttfiasy tr, #tauttfiasy td, #tauttfiasy th { border-style: none; } #tauttfiasy p { margin: 0; padding: 0; } #tauttfiasy .gt_table { display: table; border-collapse: collapse; line-height: normal; margin-left: auto; margin-right: auto; color: #333333; font-size: 13px; font-weight: normal; font-style: normal; background-color: #FFFFFF; width: 100%; border-top-style: none; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #A8A8A8; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; } #tauttfiasy .gt_caption { padding-top: 4px; padding-bottom: 4px; } #tauttfiasy .gt_title { color: #333333; font-size: 125%; font-weight: initial; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; border-bottom-color: #FFFFFF; border-bottom-width: 0; } #tauttfiasy .gt_subtitle { color: #333333; font-size: 85%; font-weight: initial; padding-top: 3px; padding-bottom: 5px; padding-left: 5px; padding-right: 5px; border-top-color: #FFFFFF; border-top-width: 0; } #tauttfiasy .gt_heading { background-color: #FFFFFF; text-align: left; border-bottom-color: #FFFFFF; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; } #tauttfiasy .gt_bottom_border { border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #D3D3D3; } #tauttfiasy .gt_col_headings { border-top-style: solid; border-top-width: 1px; border-top-color: #16202B; border-bottom-style: solid; border-bottom-width: 1px; border-bottom-color: #16202B; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; } #tauttfiasy .gt_col_heading { color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: normal; text-transform: inherit; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; vertical-align: bottom; padding-top: 5px; padding-bottom: 6px; padding-left: 5px; padding-right: 5px; overflow-x: hidden; } #tauttfiasy .gt_column_spanner_outer { color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: normal; text-transform: inherit; padding-top: 0; padding-bottom: 0; padding-left: 4px; padding-right: 4px; } #tauttfiasy .gt_column_spanner_outer:first-child { padding-left: 0; } #tauttfiasy .gt_column_spanner_outer:last-child { padding-right: 0; } #tauttfiasy .gt_column_spanner { border-bottom-style: solid; border-bottom-width: 1px; border-bottom-color: #16202B; vertical-align: bottom; padding-top: 5px; padding-bottom: 5px; overflow-x: hidden; display: inline-block; width: 100%; } #tauttfiasy .gt_spanner_row { border-bottom-style: hidden; } #tauttfiasy .gt_group_heading { padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: initial; text-transform: inherit; border-top-style: solid; border-top-width: 2px; border-top-color: #D3D3D3; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; vertical-align: middle; text-align: left; } #tauttfiasy .gt_empty_group_heading { padding: 0.5px; color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: initial; border-top-style: solid; border-top-width: 2px; border-top-color: #D3D3D3; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #D3D3D3; vertical-align: middle; } #tauttfiasy .gt_from_md > :first-child { margin-top: 0; } #tauttfiasy .gt_from_md > :last-child { margin-bottom: 0; } #tauttfiasy .gt_row { padding-top: 5px; padding-bottom: 5px; padding-left: 5px; padding-right: 5px; margin: 10px; border-top-style: none; border-top-width: 1px; border-top-color: #D3D3D3; border-left-style: none; border-left-width: 1px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 1px; border-right-color: #D3D3D3; vertical-align: middle; overflow-x: hidden; } #tauttfiasy .gt_stub { color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: initial; text-transform: inherit; border-right-style: solid; border-right-width: 2px; border-right-color: #D3D3D3; padding-left: 5px; padding-right: 5px; } #tauttfiasy .gt_stub_row_group { color: #333333; background-color: #FFFFFF; font-size: 100%; font-weight: initial; text-transform: inherit; border-right-style: solid; border-right-width: 2px; border-right-color: #D3D3D3; padding-left: 5px; padding-right: 5px; vertical-align: top; } #tauttfiasy .gt_row_group_first td { border-top-width: 2px; } #tauttfiasy .gt_row_group_first th { border-top-width: 2px; } #tauttfiasy .gt_summary_row { color: #333333; background-color: #FFFFFF; text-transform: inherit; padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; } #tauttfiasy .gt_first_summary_row { border-top-style: solid; border-top-color: #D3D3D3; } #tauttfiasy .gt_first_summary_row.thick { border-top-width: 2px; } #tauttfiasy .gt_last_summary_row { padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #D3D3D3; } #tauttfiasy .gt_grand_summary_row { color: #333333; background-color: #FFFFFF; text-transform: inherit; padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; } #tauttfiasy .gt_first_grand_summary_row { padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; border-top-style: double; border-top-width: 6px; border-top-color: #D3D3D3; } #tauttfiasy .gt_last_grand_summary_row_top { padding-top: 8px; padding-bottom: 8px; padding-left: 5px; padding-right: 5px; border-bottom-style: double; border-bottom-width: 6px; border-bottom-color: #D3D3D3; } #tauttfiasy .gt_striped { background-color: rgba(128, 128, 128, 0.05); } #tauttfiasy .gt_table_body { border-top-style: solid; border-top-width: 2px; border-top-color: #D3D3D3; border-bottom-style: solid; border-bottom-width: 2px; border-bottom-color: #16202B; } #tauttfiasy .gt_footnotes { color: #333333; background-color: #FFFFFF; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; } #tauttfiasy .gt_footnote { margin: 0px; font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #tauttfiasy .gt_sourcenotes { color: #333333; background-color: #FFFFFF; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; } #tauttfiasy .gt_sourcenote { font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #tauttfiasy .gt_left { text-align: left; } #tauttfiasy .gt_center { text-align: center; } #tauttfiasy .gt_right { text-align: right; font-variant-numeric: tabular-nums; } #tauttfiasy .gt_font_normal { font-weight: normal; } #tauttfiasy .gt_font_bold { font-weight: bold; } #tauttfiasy .gt_font_italic { font-style: italic; } #tauttfiasy .gt_super { font-size: 65%; } #tauttfiasy .gt_footnote_marks { font-size: 75%; vertical-align: 0.4em; position: initial; } #tauttfiasy .gt_asterisk { font-size: 100%; vertical-align: 0; } #tauttfiasy .gt_indent_1 { text-indent: 5px; } #tauttfiasy .gt_indent_2 { text-indent: 10px; } #tauttfiasy .gt_indent_3 { text-indent: 15px; } #tauttfiasy .gt_indent_4 { text-indent: 20px; } #tauttfiasy .gt_indent_5 { text-indent: 25px; } #tauttfiasy .katex-display { display: inline-flex !important; margin-bottom: 0.75em !important; } #tauttfiasy div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after { height: 0px !important; } Stratum RR 95% CrI P(decline) women 20-29 0.61 0.38–0.998 0.98 women 30-39 0.82 0.56–1.20 0.86 women 0.83 0.60–1.18 0.87 men 30-39 0.89 0.65–1.21 0.79 total 0.89 0.66–1.20 0.78 men 20-29 0.92 0.63–1.37 0.66 men 0.96 0.74–1.26 0.64 All of these intervals are wide. The twelve races differ so much in how far their fields came back that total field size shows no clear change at all (RR 0.89, 95% CrI 0.66–1.20). Women aged 20–29 have the lowest point estimate and the only interval that excludes no change (RR 0.61, 0.38–0.998), while men the same age barely changed (0.92, 0.63–1.37). Those two intervals overlap considerably, so counts can’t reliably tell the genders apart. New and regular runners A field can shrink because fewer people try the race or because fewer of them come back. Every finisher is labelled a newcomer if this season is their first appearance anywhere in the database, and a returning runner otherwise (Table 6). Table 6: Newcomers and returning runners between the windows. The first two rows are rate ratios; the third is the odds that a finisher is a newcomer. #zduerjdnxc table { font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji'; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } #zduerjdnxc thead, #zduerjdnxc tbody, #zduerjdnxc tfoot, #zduerjdnxc tr, #zduerjdnxc td, #zduerjdnxc th { border-style: none; } #zduerjdnxc p { margin: 0; padding: 0; } #zduerjdnxc .gt_table { display: table; border-collapse: collapse; line-height: normal; margin-left: auto; margin-right: auto; color: #333333; font-size: 13px; font-weight: normal; font-style: normal; background-color: #FFFFFF; width: 100%; border-top-style: none; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #A8A8A8; border-left-style: none; 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} #zduerjdnxc .gt_footnote { margin: 0px; font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #zduerjdnxc .gt_sourcenotes { color: #333333; background-color: #FFFFFF; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; } #zduerjdnxc .gt_sourcenote { font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #zduerjdnxc .gt_left { text-align: left; } #zduerjdnxc .gt_center { text-align: center; } #zduerjdnxc .gt_right { text-align: right; font-variant-numeric: tabular-nums; } #zduerjdnxc .gt_font_normal { font-weight: normal; } #zduerjdnxc .gt_font_bold { font-weight: bold; } #zduerjdnxc .gt_font_italic { font-style: italic; } #zduerjdnxc .gt_super { font-size: 65%; } #zduerjdnxc .gt_footnote_marks { font-size: 75%; vertical-align: 0.4em; position: initial; } #zduerjdnxc .gt_asterisk { font-size: 100%; vertical-align: 0; } #zduerjdnxc .gt_indent_1 { text-indent: 5px; } #zduerjdnxc .gt_indent_2 { text-indent: 10px; } #zduerjdnxc .gt_indent_3 { text-indent: 15px; } #zduerjdnxc .gt_indent_4 { text-indent: 20px; } #zduerjdnxc .gt_indent_5 { text-indent: 25px; } #zduerjdnxc .katex-display { display: inline-flex !important; margin-bottom: 0.75em !important; } #zduerjdnxc div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after { height: 0px !important; } Measure Scale Estimate 95% CrI P(decline) Newcomers, participant count RR 0.87 0.63–1.22 0.81 Returning runners, participant count RR 0.90 0.66–1.21 0.78 Newcomer share of the field OR 1.01 0.87–1.16 0.44 Both groups fell, and neither interval is decisive by itself. The third row shows the odds that a given finisher is a newcomer, which changed by OR 1.01 (0.87–1.16, P(decline) 0.44). The mix of new and returning runners looks about the same as it always did. Weighting The Midnight Sun Run is 50% of the finisher records in the comparison windows, and the four smallest races together are 5.4%. Figure 5 shows how the model adjusts individual results based on race size and the width of the confidence intervals. Figure 5: Post-pandemic change in the odds a finisher is a woman, by race. Open grey points are each race fit on its own, filled points are the model’s race-level estimates with 95% credible intervals, and the red diamond is the series estimate. The Santa Claus Half Marathon, Jim Loftus Mile and Gold Discovery Run have the most extreme estimates when each race is fit on its own, and they’re also the least certain, so the model pulls them a long way toward the middle. The Midnight Sun Run by itself returns 1.00, no post-pandemic shift at all once its own long-term decline in the ratio of female to male finishers is included, and the model moves it to 0.94. It’s the only one of the core races that doesn’t show the effect, and it has more finisher records than the other six put together. Before any pooling, 6 of 7 races point the same way, so the series-level number isn’t an artifact of one small race. For the 3 groups that did shift, the model’s race-level estimates are similar (Table 7), though that is partly the pooling itself pulling them toward the series. Every race’s 20–29 estimate falls between 0.74 and 0.78, and every 40–49 estimate between 1.08 and 1.17. The gender estimates spread a little wider, from 0.83 to 0.94, with the Midnight Sun Run at the top of that range. Table 7: Race-level changes (odds ratios with 95% credible intervals) for the groups that shifted, alongside the series estimate. #bjdoaqxonj table { font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji'; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } #bjdoaqxonj thead, #bjdoaqxonj tbody, #bjdoaqxonj tfoot, #bjdoaqxonj tr, #bjdoaqxonj td, #bjdoaqxonj th { border-style: none; } #bjdoaqxonj p { margin: 0; padding: 0; } #bjdoaqxonj .gt_table { display: table; border-collapse: collapse; line-height: normal; margin-left: auto; margin-right: auto; color: #333333; font-size: 13px; font-weight: normal; font-style: normal; background-color: #FFFFFF; width: 100%; border-top-style: none; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #A8A8A8; 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} #bjdoaqxonj .gt_footnote { margin: 0px; font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #bjdoaqxonj .gt_sourcenotes { color: #333333; background-color: #FFFFFF; border-bottom-style: none; border-bottom-width: 2px; border-bottom-color: #D3D3D3; border-left-style: none; border-left-width: 2px; border-left-color: #D3D3D3; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; } #bjdoaqxonj .gt_sourcenote { font-size: 90%; padding-top: 4px; padding-bottom: 4px; padding-left: 5px; padding-right: 5px; } #bjdoaqxonj .gt_left { text-align: left; } #bjdoaqxonj .gt_center { text-align: center; } #bjdoaqxonj .gt_right { text-align: right; font-variant-numeric: tabular-nums; } #bjdoaqxonj .gt_font_normal { font-weight: normal; } #bjdoaqxonj .gt_font_bold { font-weight: bold; } #bjdoaqxonj .gt_font_italic { font-style: italic; } #bjdoaqxonj .gt_super { font-size: 65%; } #bjdoaqxonj .gt_footnote_marks { font-size: 75%; vertical-align: 0.4em; position: initial; } #bjdoaqxonj .gt_asterisk { font-size: 100%; vertical-align: 0; } #bjdoaqxonj .gt_indent_1 { text-indent: 5px; } #bjdoaqxonj .gt_indent_2 { text-indent: 10px; } #bjdoaqxonj .gt_indent_3 { text-indent: 15px; } #bjdoaqxonj .gt_indent_4 { text-indent: 20px; } #bjdoaqxonj .gt_indent_5 { text-indent: 25px; } #bjdoaqxonj .katex-display { display: inline-flex !important; margin-bottom: 0.75em !important; } #bjdoaqxonj div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after { height: 0px !important; } Race 20-29 40-49 women vs men Jim Loftus Mile 0.76 (0.57–1.03) 1.09 (0.83–1.25) 0.83 (0.62–0.98) Santa Claus Half Marathon 0.74 (0.56–0.91) 1.12 (0.93–1.31) 0.83 (0.63–0.96) Gold Discovery Run 0.75 (0.59–0.96) 1.13 (0.96–1.35) 0.84 (0.65–0.97) Equinox Marathon 0.78 (0.65–0.97) 1.08 (0.91–1.23) 0.88 (0.76–1.00) Chena River Run 0.78 (0.64–0.98) 1.14 (1.01–1.29) 0.89 (0.79–1.00) Beat Beethoven 0.75 (0.61–0.92) 1.17 (1.04–1.37) 0.90 (0.80–1.01) Midnight Sun Run 0.74 (0.60–0.88) 1.14 (1.04–1.24) 0.94 (0.85–1.05) Population estimate 0.76 (0.64–0.90) 1.12 (1.00–1.25) 0.87 (0.75–0.96) Field size is one place where the races are very different: the twelve races varied so much in how far their fields recovered that the pooled estimate (0.89, 0.66–1.20) doesn’t describe any of them well. The estimated spread between races in the pandemic shift is 0.08 on the log-odds scale for the female:male ratio and 0.26 for the under-20 group, so races differ about 3 times as much in how their under-20 group shifted as in how their percentage of women finishers did. The Gold Discovery Run Gold Discovery is one of the seven races recorded in nearly every season, so the models have an overall trend and a pandemic effect for it specifically (Figure 6, Table 8). It’s a small race, around 123 finishers in a typical 2015–2019 season, so its estimates get pulled toward the series by as much as the spread between races warrants. Between 2006 and 2026 two bands changed at Gold Discovery, both the same way they changed across the series. The 60+ group rose (×2.91 over twenty years, 95% CrI 1.78–4.73) and the 40–49 group fell (×0.60, 0.42–0.80). The under-20 group probably rose (×2.66, 0.98–7.20) and the 50–59 group probably fell (×0.67, 0.44–1.03), but both of those intervals include no change. Gender shows no trend (×1.08, 0.83–1.47). Net of those trends, the same two losses turn up here. The odds a finisher was aged 20–29 fell (OR 0.75, 0.59–0.96) and the odds a finisher was a woman fell (OR 0.84, 0.65–0.97). Figure 6: Gold Discovery Run: each age band’s share of the field, and women’s share of women and men, by season. Points are seasons; the line is the race’s own fitted trend with the change held out, coloured where the credible interval excludes no change. Labels give the twenty-year trend (left) and the post-pandemic change (right). Vertical scales differ between panels. Table 8: Gold Discovery Run: observed shares in each window, the race’s twenty-year trend, and its post-pandemic change, as odds ratios with 95% credible intervals. #jvkywbxvht table { font-family: system-ui, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif, 'Apple Color Emoji', 'Segoe UI Emoji', 'Segoe UI Symbol', 'Noto Color Emoji'; -webkit-font-smoothing: antialiased; -moz-osx-font-smoothing: grayscale; } #jvkywbxvht thead, #jvkywbxvht tbody, #jvkywbxvht tfoot, #jvkywbxvht tr, #jvkywbxvht td, #jvkywbxvht th { border-style: none; } #jvkywbxvht p { margin: 0; padding: 0; } #jvkywbxvht .gt_table { display: table; border-collapse: collapse; line-height: normal; margin-left: auto; margin-right: auto; color: #333333; font-size: 13px; font-weight: normal; font-style: normal; background-color: #FFFFFF; width: 100%; border-top-style: none; border-top-width: 2px; border-top-color: #A8A8A8; border-right-style: none; border-right-width: 2px; border-right-color: #D3D3D3; border-bottom-style: none; 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} #jvkywbxvht .gt_super { font-size: 65%; } #jvkywbxvht .gt_footnote_marks { font-size: 75%; vertical-align: 0.4em; position: initial; } #jvkywbxvht .gt_asterisk { font-size: 100%; vertical-align: 0; } #jvkywbxvht .gt_indent_1 { text-indent: 5px; } #jvkywbxvht .gt_indent_2 { text-indent: 10px; } #jvkywbxvht .gt_indent_3 { text-indent: 15px; } #jvkywbxvht .gt_indent_4 { text-indent: 20px; } #jvkywbxvht .gt_indent_5 { text-indent: 25px; } #jvkywbxvht .katex-display { display: inline-flex !important; margin-bottom: 0.75em !important; } #jvkywbxvht div.Reactable > div.rt-table > div.rt-thead > div.rt-tr.rt-tr-group-header > div.rt-th-group:after { height: 0px !important; } Stratum 2015–2019 (%) 2022–2026 (%) Trend over 20 y Post-pandemic shift under 20 3.1 5.6 2.66 (0.98–7.20) 1.32 (0.81–2.58) 20-29 16.2 12.5 0.89 (0.56–1.42) 0.75 (0.59–0.96) 30-39 25.1 25.2 1.17 (0.84–1.57) 0.91 (0.72–1.12) 40-49 22.0 22.3 0.60 (0.42–0.80) 1.13 (0.96–1.35) 50-59 20.7 16.7 0.67 (0.44–1.03) 1.05 (0.79–1.35) 60+ 12.8 17.7 2.91 (1.78–4.73) 0.97 (0.74–1.33) women vs men 51.9 43.6 1.08 (0.83–1.47) 0.84 (0.65–0.97) What sets Gold Discovery apart is its size, not its make-up. A typical field fell from 123 finishers a season in 2015–2019 to 61 in 2022–2026 (RR 0.53, 0.39–0.74), a bigger drop than the typical race in the series with probability 0.99. Every participant count group clearly fell except men aged 20–29, whose interval includes no change (RR 0.69, 0.37–1.18), and the steepest fall of all was among women that age (RR 0.30, 0.16–0.55). Women overall fell further than men (RR 0.45, 0.32–0.65 against 0.65, 0.46–0.92), which is the same thing the group model says. Discussion The first thing the analysis suggests is that the field has been aging at the top and thinning in the middle for twenty years. That’s the largest change in the data, and it has nothing to do with the pandemic. Second is the loss of runners in their twenties after the pandemic, which the model estimates for every race. In participant counts, women that age are the only group with a clear drop (RR 0.61, 0.38–0.998, P(decline) 0.98), while men that age barely changed (0.92, 0.63–1.37, P(decline) 0.66), although the two intervals overlap too much to tell the genders apart. The third effect is the percentage of women finishers, which has been dropping since the pandemic. The gender balance of these races was flat for fourteen seasons and has been falling since 2022. It holds in 6 of 7 core races, but not in the Midnight Sun Run, which is a very different race from the others because of its popularity and broad participation. Conclusion Between 2006 and 2026 the field at these races got older at the top and thinner in the middle. The odds a finisher was 60+ nearly tripled while the 40–49 and 50–59 groups fell, and all of that predates the pandemic. Net of those trends, two things did change after the pandemic. The odds a finisher is in their twenties fell 24% at the interruption and haven’t come back. And the percentage of women finishers, flat for fourteen seasons before that, has been falling since. Artificial Intelligence Disclosure Much of the analysis was done in concert with Claude Code, Opus model. All of the writing is my own, with review and critique (mostly in terms of how I stated methods and results) from Claude.