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Boys - Seneca Valley XC Ranking Team Analytics

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416 rankings published • 1,929 athletes ranked • 30,000 race performances • 750,000 calculations • 0 opinions

All-Time Analytics: Boys Girls Boys and Girls Combined

Mocorunning's XC rankings date back to the 2006 season. Click a team name to see current season stats versus all-time stats for this school.

Boys - All-Time Highest End-of-Season (EOS) Z-ScoresA

Rank Name School Season Points EOS Rank Z-Score
1 Alejandro Berrio Seneca Valley 2023 204.70 1 2.58
2 Brian Marshall Seneca Valley 2006 164.20 16 0.87
3 Saaim Hamdani Seneca Valley 2025 90.10 33 0.19

Boys - All-Time Most Weeks Ranked #1¹

Rank Name School Grad Year Weeks
1 Alejandro Berrio Seneca Valley 2024 2

Boys - All-Time Most Weeks Ranked Top 10¹

Rank Name School Grad Year Weeks
1 Alejandro Berrio Seneca Valley 2024 7
2 Brian Marshall Seneca Valley 2007 2

Boys - All-Time Most Weeks Ranked¹

Boys - All-Time Highest Point Totals - Freshmen²

Rank Name School Date Ranking Points
No data found for this selection.

Boys - All-Time Highest Ranked Athletes - Final Season Ranking Only³

Boys - All-Time Highest Ranked Freshmen

Rank Name School Date Achieved Peak Rank
No records found for this selection.

Boys - All-Time Highest Ranked Freshmen - Final Season Rankings Only

Rank Name School Date Achieved EOS Rank
No records found for this selection.

Boys - All-Time Highest Debut Ranking - Freshmen

Rank Name School Grade Date Debut Rank
No rankings found for this selection.

Boys - All-Time Greatest Individual Ranking Improvement in a Week

Rank Week Name School Grade R1 R2 Improvement
1 2016 Week 8 Bryan Midlam Seneca Valley 12 61 42 +19 spots
2 2025 Week 7 Saaim Hamdani Seneca Valley 12 54 39 +15 spots
3 2023 Week 5 Alejandro Berrio Seneca Valley 12 16 2 +14 spots
4 2017 Final Boubacar Barry Seneca Valley 11 85 79 +6 spots
5 2025 Week 5 Saaim Hamdani Seneca Valley 12 53 48 +5 spots
6 2023 Week 4 Alejandro Berrio Seneca Valley 12 20 16 +4 spots
6 2025 Week 4 Saaim Hamdani Seneca Valley 12 57 53 +4 spots
8 2006 Week 2 Brian Marshall Seneca Valley 12 12 9 +3 spots
8 2025 Final Saaim Hamdani Seneca Valley 12 36 33 +3 spots
10 2021 Week 10 John Klansek Seneca Valley 12 60 58 +2 spots
10 2025 Week 9 Saaim Hamdani Seneca Valley 12 38 36 +2 spots
12 2017 Week 9 Boubacar Barry Seneca Valley 11 81 80 +1 spots
12 2023 Week 10 Alejandro Berrio Seneca Valley 12 2 1 +1 spots
12 2025 Week 8 Saaim Hamdani Seneca Valley 12 39 38 +1 spots
15 2006 Week 10 Brian Marshall Seneca Valley 12 15 15 +0 spots
15 2023 Week 6 Alejandro Berrio Seneca Valley 12 2 2 +0 spots
15 2023 Week 7 Alejandro Berrio Seneca Valley 12 2 2 +0 spots
15 2023 Week 8 Alejandro Berrio Seneca Valley 12 2 2 +0 spots
15 2023 Week 9 Alejandro Berrio Seneca Valley 12 2 2 +0 spots
15 2023 Final Alejandro Berrio Seneca Valley 12 1 1 +0 spots
21 2006 Week 4 Brian Marshall Seneca Valley 12 9 10 +-1 spots
21 2006 Final Brian Marshall Seneca Valley 12 15 16 +-1 spots
21 2018 Week 2 Boubacar Barry Seneca Valley 12 51 52 +-1 spots
21 2023 Week 2 Alejandro Berrio Seneca Valley 12 17 18 +-1 spots
25 2006 Week 6 Brian Marshall Seneca Valley 12 10 12 +-2 spots
25 2016 Final Bryan Midlam Seneca Valley 12 74 76 +-2 spots
25 2018 Week 1 Boubacar Barry Seneca Valley 12 49 51 +-2 spots
25 2023 Week 3 Alejandro Berrio Seneca Valley 12 18 20 +-2 spots

Boys - All-Time Most Ranking Entries and Re-Entries

Rank Name School Grad Year Ranking Entries
No records found matching these criteria.

Boys - All-Time #1 Ranked Athletes Per School

Rank School Unique Athletes
1 Seneca Valley 1

Boys - All-Time Top 10 Ranked Athletes Per School

Rank School Unique Athletes
1 Seneca Valley 2

Boys - All-Time Ranked Athletes Per School

Rank School Unique Athletes
1 Seneca Valley 7

Boys - All-Time Athlete-Weeks Ranked #1 Per School

Rank School Athlete-Weeks
1 Seneca Valley 2

Boys - All-Time Athlete-Weeks Ranked Top 10 Per School

Rank School Athlete-Weeks
1 Seneca Valley 9

Boys - All-Time Athlete-Weeks Ranked Per School

Rank School Athlete-Weeks
1 Seneca Valley 51

Boys - Most Athletes From One Team in a Week¹⁰

Rank Week School Athletes Ranked
1 2016 Week 4 Seneca Valley 2 athletes
2 2006 Preseason Seneca Valley 1 athletes
2 2017 Week 8 Seneca Valley 1 athletes
2 2017 Preseason Seneca Valley 1 athletes
2 2021 Week 9 Seneca Valley 1 athletes
2 2023 Week 1 Seneca Valley 1 athletes
2 2025 Week 1 Seneca Valley 1 athletes


Mind the toggle! Comparing boys and girls is not usually how we think about things, but this page offers boys and girls as a combined query option because it is very interesting to those who cherish school program performance.

AAll-Time Highest End-of-Season (EOS) Z-Scores - Z-score is a universally accepted statistic used to measure how far an individual performance deviates from the group baseline, normalized by the overall volatility or spread of the group. The Z-score is the number of standard deviations a specific data point is above or below the mean of its dataset or population. A z-score is a way to measure how normal or unusual a specific number is compared to the rest of the group. In this cross country ranking, it is how much a runner excels compared to other ranked runners (who are all considered very good). A negative Z-score is below average, which is fine in this context since there is a high bar to become ranked at all. A z-score of zero is average for a ranked runner. Z-Score = 1 is "Above Average": The value is 1 standard deviation above the mean. Z-Score = 2 is "Unusual / Exceptional": The value is 2 standard deviations above the mean. The runner has outperformed 98% of the group. Z-Score = 3 is "Extremely Rare / An Outlier": The value is 3 standard deviations above the mean. This is an extreme rarity. The runner outperformed 99.9% of the group. In data science and statistics, any data point with a Z-score of 3 or higher is officially flagged as an outlier - a number so high it almost looks like a typo. Z-Score = 4 is "Legendary": The value is 4 standard deviations above the mean. This is a "Black Swan" event. The odds of a Z-score reaching 4 naturally in a normal distribution are about 1 in 30,000. If you see a 4, it means the performance completely shattered the standard scale of competition.

More: Z-score is calculated using end-of-season (EOS) points. The ranking's point scale has shifted over the decades which makes a simple point total metric an unreliable indicator of best runners; however, Z-score remains a reliable metric for comparing the dominance of runners across the decades. Z-score is still limited by the same factors that limit this ranking system as a whole. Did the elite runner run their hardest in every race, or did they jog a few races to get to the post season? Did the elite runner log enough honest races by the state championship meet for their score to reflect their maximum ability? For the truly elite who value post-season races above all else, not always. Conversely, it is possible for elite athletes to "pad the stats" by beating up on a "weak" crop of ranked runners during any given year. Hence, why Z-score is a dominance metric.

BHypothetical All-Time Team Clash Based on Z-Score - This section uses only the highest end-of-season Z-score per athlete. The scoring table ranks runners by highest end-of-season (EOS) Z-score and uses standard cross country scoring of five scoring runners and two displacers. In this table, athletes are grouped by season so it essentially ranks the best single season teams in the ranking's history based on Z-score. Deviating from classic cross-country scoring, runners from incomplete teams are counted as displacers. This makes it more fun to look at for schools that do not have many years with 5+ ranked runners. Click the scoring breakdown to see the names of the athletes who comprise the top five from that school for that given year. Most people will probably prefer to see the best boys teams or girls teams. If you happened to select "Boys and Girls" from the toggle menu, it will indeed select a team of boys and girls from a given year. Boys and girls can compete on a level playing field of standard deviations. Take it or leave it! Remember from above that Z-score is a dominance metric which is a statistical proxy for best runners compared to the mean if every runner runs their hardest in every race.

CLargest Consecutive Season Z-Score Improvement calculates each runner's end-of-season Z-score year by year and compares each season to the immediately previous season only. It keeps only positive gains, then ranks the largest increases first to highlight the biggest single-year jumps in dominance.

DGreatest Career Z-Score Improvement evaluates multi-year development across an athlete's full tracked career window by comparing debut season end-of-season (EOS) Z-score to career end-of-season Z-score. It includes only positive growth with at least two varsity seasons and ranks the largest career gains first.

¹The Most Weeks Ranked stat is based on the # of rankings published. It is not based on calendar weeks. It is not consecutive weeks. The number of rankings published each season varied. There are typically 10 to 12 rankings published each season.

²The Highest All-Time Point Totals stat is not meant to infer a hierarchy of best runners. The point system evolves and cannot be compared across seasons. 2006 had inflated point totals relative to subsequent seasons due scoring changes after the first full season. The pandemic also shook things up with just a few races run in spring 2021. The ranking shown in this list is the rank at the time of the peak point total and not necessarily the peak ranking of that runner.

³The All-Time Highest Ranked Athlete stat displays the highest peak ranking by the top athletes for this school. The 'final season ranking' only includes rankings from the final ranking published each season. The final ranking of each season incorporates the most data and emphasizes championship races. EOS = End of Season. In the 'final season ranking' list, an athlete may be listed once per season.

The All-Time Highest Ranked Freshmen stat lists the peak ranking for athletes in grade 9. The 'final season ranking' only includes rankings from the final ranking published each season. The final ranking of each season incorporates the most data and emphasizes championship races. EOS = End of Season.

The Highest Debut Ranking stat shows the highest rankings at which individual athletes first appeared in the rankings. The original 2006 preseason rankings are excluded.

The Greatest Individual Ranking Improvement in a Week identifies and ranks the individuals with the greatest ranking improvement in a single week. The athlete must be ranked both weeks to be considered. It excludes newly ranked runners. It excludes the ranking transition from final season rankings to the next preseason rankings.

Progress is not linear for everyone. The Most Ranking Entries and Re-Entries stat shows athletes that had setbacks and kept working their way back onto the ranking at least two times after their initial debut. It is very common for athletes to fall off the rankings and get re-added later.

The Most Ranked Athletes Per School stat adds the total number of unique athletes per school to ever achieve a #1 ranking, a top 10 ranking, or to ever appear on the ranking.

The Most Athlete-Weeks Per School stat adds the total number of weeks that all individual athletes for each school were ranked #1, top 10, or ever ranked. For example, if athlete 'X' was ranked for 30 weeks in their high school career, and athlete 'Y' from the same school was ranked for 15 weeks in their high school career, that school would have accumulated 45 all-time athlete-weeks.

¹⁰The Most Athletes Ranked From One Team in a Week identifies and ranks the teams that have had the most runners ranked simultaneously. A team may be listed once for each year. The earliest week in the season where the team achieved the most runners for the season is shown.

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