Tag: Research
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Which CS2 Pros Perform Better (or Worse) Against Top Teams?
Recently I’ve seen lots of discourse about degster, broky, and others performances against top teams. I wanted to research how players performed against different tiers of ranked teams to see if some narratives were justified. The first thing I did was collect data. I decided to use data from CS2 matches only (~20 months) to… Read more
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Is Vitality the Best Team on Every Map? An Analysis
Vitality is 45-8 since adding ropz in 2025 and half of those losses are by 2 rounds. They are the current #1 team in the world by such a large margin that it begs the question: are they the best team on every map? To answer that, we need to define ‘best.’ There are two… Read more
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How Much Better Do College Basketball Players Get Each Year?
Walter Clayton Jr was recruited to Iona in 2021 as an unranked college basketball recruit. He played 16 MPG as a Freshman for Rick Pitino, scoring 7.3 PPG. His Sophomore year he became a starter and quickly a star. He won MAAC player of the year and decided to transfer to Florida. As a Junior… Read more
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Entrying, Trading, AWPing, Flashes: What affects HLTV rating the most?
In competitive Counter-Strike, a player’s HLTV 2.1 rating is often used as the gold standard for individual performance. But which teamplay statistics affect this number and by how much? To answer this, I gathered a dataset of top 50 matches since 2024 (minimum 2,000 rounds, n=287), separated them by side and whether the player was… Read more
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Which NFL Quarterbacks Are Put in the Best Situations to Succeed?
Determining which quarterbacks are set up for success requires analyzing the factors that influence their performance. Using PFF grades, specifically Receiving and Pass Blocking grades, I evaluated how these external factors correlate with Passing grades. Correlations Between Factors: This data reveals a strong relationship between Passing grades and Receiving grades, with Pass Blocking grades playing… Read more
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How challenging is the transition between minor league levels?
To address this question, I analyzed 2024 data for professional baseball players who logged at least 50 plate appearances (PA) or faced 50 batters (TBF) at two or more levels. For hitters, I measured the difference in wRC+ between levels. For pitchers, I used FIP-. To get a final number I applied a weighted average… Read more
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Finding Expected Value of College Football Recruits
Question: How can we better evaluate college recruits using positional adjustments and expected value? To answer this, I analyzed recruiting data from 2013 to 2026, combining on3’s industry rankings with NFL Draft data and PFF grades. Here’s what I found: Using this data, I developed a model to assign each recruit an expected value on… Read more
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Rematch Win Expectancy (RWE): A Predictive Metric for Football Teams
Originally written in 2021. There may be some outdated information. Abstract: Rematch Win Expectancy (RWE) is a predictive metric, estimating the probability that Team X would defeat Team Y in a rematch based on the sustainable aspects of their original football game. RWE draws inspiration from Bill Connelly’s “Postgame Win Expectancy” but seeks to shift… Read more
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20-80 Scale for MLB Hitters – 2024 Edition
Numbers were calculated with data from 2021 to 2024 for players with a minimum of 200 PA. These tables are only for comparison on hitters from 2021 to 2024. Some adjustments were made when numbers were impossible to accomplish (-1.0 BB%). Many of the examples used were rounded to the applicable numbers. Data as of… Read more
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College Football Positional Value
Question: What is the order of importance for each college football position? To answer this I gathered data from the 2021, 2022, and 2023 college football seasons. For response variables I used yards per play and EPA for each offense, defense, and net. For explanatory variables I used PFF grades by position. When multiple players… Read more